Part II - Polycentricity and Urban Data

4 Community Land Trusts as a Knowledge Commons Challenges and Opportunities

Natalie Chyi and Dan Wu

Introduction

This chapter explores various aspects of community land trusts (CLTs), focusing on how this governance model effectively functions as an ownership structure for common pool resources. Indeed, understanding the incentives facing the owners of any communal ownership structure is vital for successfully creating and managing a CLT. These resource commons aspects are conceptually explained and explored through a descriptive account of current practices within the CLT sector.

A CLT is a nonprofit entity that holds and manages land for the benefit of a place-based community, acting as a long-term steward of the land and the assets on it. The CLT model is a classic example of Elinor Ostrom’s (1990) idea of a commons, in which a valuable resource (such as real estate) is owned collectively by a community of individuals. The CLT ownership structure creates unique challenges for the community of owners to effectively manage the resource. First, the resource management incentives facing each individual owner of the jointly owned commons resource is significantly different from those incentives facing a lone owner of a privately held resource. Second, the type of information that is needed for the group of owners to practice efficient stewardship of the commons resource is also significantly different from the type of information that is pertinent to the lone owner of a privately held resource. The implications of the unique incentive structure and information needs facing a CLT must be well understood to facilitate effective resource management efforts within and between CLTs.

While land is the primary pooled resource of a CLT, knowledge and data about its use are also valuable pooled resources, both among the owners of a CLT and among a group of CLTs within an organization. Producing knowledge resources and sharing the resulting information between CLTs, and even between CLT staff and their residents or partners, is understudied in the literature across disciplines. Yet leveraging such information in a manner that is compatible with the incentive structure facing the group of CLT owners is key to the success of any one CLT and influences the entire CLT sector.

For example, CLT administrators enable residents and owners to manage their communal resources more effectively through education. This includes activities such as coaching first-time lower-income homeowners through buying and operating a home, or training resident and community leaders in the technical skills needed to govern a CLT. Further, the livelihood and growth of the CLT sector depends on the documentation and sharing of useful information across CLTs. It also includes identifying advocacy priorities, best practices, and robust strategies to face macroeconomic stress factors, such as the Covid-19 shutdown of the economy. The benefits created through these efforts are shared throughout the residents of the CLT. Our mapping of these information flows highlights formal and informal mechanisms, privacy considerations, and channels for information dissemination that range from a simple phone call to digital data portals such as HomeKeeper.

The community, fellowship, and sense of responsibility between present and future members of a CLT provides another interesting example of a pooled cultural resource that exists within CLTs.

This chapter will provide an overview of the CLT model, then explore the CLT in both concept and reality as a land and housing commons, knowledge commons, and cultural commons. Our analysis is guided by the extant scholarship surrounding Ostrom’s design principles of the common pool resource model, and the Governing Knowledge Commons framework. Our methodology, detailed below, encompasses a broad literature review, as well as interviews with key staff across various CLTs and CLT networks, to document their practices and insights. We hope to contribute to existing knowledge commons scholarship by conceptualizing CLTs as knowledge commons, and using CLTs as a unique case study of community property governance and knowledge commons management as it fits within the classic commons literature. We also hope to contribute to the CLT community and practitioners by providing research and analysis in those areas where academic literature is rather scarce to nonexistent, to better understand current practices.

Methodology

We chose to conduct a case study on CLTs because of the parallel ways in which a physical and cultural commons has been understudied. Existing literature around the knowledge commons also tends to center a highly educated demographic, and we believe the CLT presents an example of how a cultural commons can act in service of marginalized groups.

In the writing of this chapter, we examined publicly available information on organization websites, articles, publications, reports, and videos. To supplement the lack of information across some of these themes, we also conducted key informant interviews with staff across individual CLTs and national/regional CLT networks. These discussions were especially helpful for understanding the informal networks of information sharing and practices between CLTs, as well as gaining insights into the effectiveness of their current practices.

A total of six persons, representing five separate organizations, were interviewed by video call. The organizations included: Grounded Solutions Network, Douglass Community Land Trust (DC), Chinatown CLT (Boston), Greater Boston Community Land Trust Network (Boston), San Francisco CLT (San Francisco), and other informal regional CLT consortiums or networks. These video call interviews lasted between thirty and sixty minutes, with additional questions asked during email exchanges.

These organizations were selected due to their relevance to our research question. Questions focused on information flows, community governance structures, and the impact of the Covid-19 pandemic. From our contacts, we learned how each of the organizations had addressed these issues. Furthermore, they are active, thriving community land trusts, allowing us to filter out organizations whose experiences are muddied by their lack of resources. The insights we gained from these interviews, whether as evidence of common trends or unique examples, are included in this chapter.

What Is a CLT?

A CLT is a nonprofit entity that either owns or leases land for community-beneficial uses, with a goal to preserve land for the public good and to meet community needs (Emmeus Davis 2007). In this way, CLTs are stewards of these shared resources, effectively separating landownership from land use and removing it from the speculative markets (Emmeus Davis 2017). CLTs allow more residents to benefit from the land through lease agreements (Thaden 2018). For example, CLTs often impose a resale restriction on price that is tied to inflation as part of the leasing agreement, which limits the opportunity for potential owners to speculate on the land. Such actions allow CLTs to keep this land both accessible and affordable to future generations.

Today, there are over 250 CLTs in the United States, mostly serving families living at low to moderate levels of income. For example, the average household income of shared equity homeowners in 2018 was only $41,207 (Wang et al. 2019). Almost three-fourths of CLTs have fewer than two full-time employees, and CLTs tend to rely heavily on volunteer labor (Wang and Rose 2018).

The majority of CLTs hold formal or informal relationships and partnerships with public, private, and charitable organizations, as well as through layering different types of organizations within their respective ecosystems. These partnerships may be via fiscal sponsorship, acting as a shareholding entity, participation in a governing board, the provision of technical assistance or services, or coordinated advocacy (Nicholas and Williams 2020). In particular, affordable housing projects require partnerships with a variety of actors that can help across the areas of real estate, construction, finance, and law. Local governments, charitable entities, or grassroots organizations may help to incubate or start a CLT as a tool for their organization to deliver on their vision of affordable housing or community control of land. For instance, Interboro CLT was started by four New York-based nonprofits (NYC Neighborhoods, Habitat for Humanity New York City, the Mutual Housing Association of New York, and the Urban Homesteading Assistance Board), with the mission to preserve diversity and provide affordable homeownership in NYC (Kunkler 2021). The City of Houston helped to launch the Houston CLT to promote long-term affordable housing in the city. These relationships come with varying degrees of control and trade-offs to consider.

While residents typically pay lease fees of $25–50 a month to the CLT, this revenue stream is insufficient to keep a CLT operating effectively. This makes CLTs dependent on external funders, such as grants from the US Department of Housing and Urban Development or private foundations focused on promoting affordable housing (Williams 2019a). Almost 40 percent of funding for shared equity homes between 1985 and 2018 came from public sources in the form of grants or development loans, while about 60 percent came from private sources, including buyers’ savings, conventional real estate loans from financial institutions, individual donations, and foundation grants (Wang et al. 2019). The organizations that were interviewed all sought and received donations from both community members and other organizations that had similar missions. Other sources included both public and private lenders, such as housing trust funds, CDFIs, and credit unions. Many municipalities and states have adopted affordable housing trust funds utilizing deferred or forgivable loans.

History and Philosophy of CLTs

The CLT model was inspired by older ideas of common ownership and different movements for the stewardship of land for wider community benefit around the world, including India, Israel, Mexico, Tanzania, and England (DeFilippis, Stromberg, and Williams 2018). In the United States, the CLT model is rooted in Henry George’s efforts at property reform and critique of the prevailing, individualist model of landownership, when civil rights activists merged George’s ideas with movements for community control. In 1969, the first CLT, New Communities, Inc., was founded in Georgia by a group of activists. New Communities was built on 5,000 acres of land, with the intention to decommodify land, provide for permanent community ownership of property, and give black farmers the opportunity to take and maintain control of basic resources.

New Communities was created as “a legal entity, a quasi-public body, chartered to hold land in stewardship for all mankind present and future while protecting the legitimate use-rights of its residents.” The community was conceptualized as a nested set of relationships, involving a resident community living within a trust, and a wider community of anyone who wanted or intended to be a resident or otherwise supported or identified with the trust. Ultimately, the CLT’s community included everyone who might support or benefit from the CLT’s mission, presence, and dramatic reorganization of landownership practices (DeFilippis, Stromberg, and Williams 2018).

The CLT movement reached urban areas in the 1980s as a way to combat increased property speculation in inner-city neighborhoods. Supporters felt that ongoing gentrification threatened the local community with mass displacement. In the 1990s, more favorable policies, increased funding opportunities, and shared learning across existing CLTs helped the CLT movement begin to thrive in the United States (Community Land Trust Network n.d.).

CLT as a Land Commons

CLTs manage so-called governance property, a term that describes many different forms of private property ownership (Alexander 2012). Governance property includes land shared with multiple owners who have the authority to make governance decisions about the land’s use, access, and transfer to other owners. This form of governance is a departure from the traditional model of property ownership common in most Western cultures, which aggregates the bundle of legal rights and entitlements into the hands of a single owner (Duncan 2002). Legal scholars recognize that this fee-simple model of property and resource ownership is increasingly ill-fitting for an interdependent and urbanized neighborhood in which most city-dwellers live. When public or private landownership is predominantly held with such monopoly ownership rights, this leads to significant challenges in leveraging urban property to create value for its users. This challenge is largely the result of the spatial relationships arising from the degree of population density and the proximity issues created by dense urbanization (Fennell 2016).

Contemporary land use requires a diverse collection of approaches to reserve land use opportunities for those who have fewer resources. The context, communities, and shared resources give rise to specific social dilemmas associated with shared use of the resources, given the communities’ needs and goals. Commons such as CLTs provide a means for addressing and overcoming those dilemmas. Land commons can provide the most vulnerable and marginalized communities access to urban resources by recognizing resource governance through property interests via a collective property right, which is needed for such groups to gain access to these lands and resources.

CLTs are one way that city governments are utilizing alternative land stewardship models to provide universal access to critical urban resources across all individuals and communities. Research by Lisa Alexander addresses how property stewardship is created through the CLT arrangement. The profit motive of the individual is replaced by allocating collective ownership rights in a way that gives resource stewards access and control over land and resources without a “fee simple” title. This removes wealth maximization as a primary motivator for resource allocation decisions and “connects stewards to economic resources and social networks that maximize their self-actualization, privacy, human flourishing, and community participation” (Alexander 2019).

Long-Term Resource Stewardship in Residential Real Estate

Typically, the land stewarded by a CLT is used to build and provide permanently affordable housing into the future. The CLT owns the land but not the housing units on the land. Moderately low-income individuals can purchase a CLT house if they have a decent credit history and can pay for the home, which is typically restricted in cost to make it more affordable. The purchase is often funded through a special mortgage that applies to the house but not the land. Further, the buyer pays a small lease fee to the CLT, which stewards the property over the long term. In return, the homeowner is responsible for maintenance of the land.

When the current homeowner chooses to sell to the next qualifying buyer, the future homeowners are informed of the terms of CLT housing ownership. The selling owners receive the equity that they have paid into the home, as well as a portion (usually less than a third) of the increased value of their home. In this way, CLTs enable homeowners to build equity while maintaining a source of affordable housing that is made possible through the ground lease (Williams, 2019a).

Grassroots organizations, activists, municipalities, and CDCs have all looked to CLTs as vehicles for promoting affordable housing and anti-displacement. Rising housing and land costs have exiled many families and devastated many communities, even in cities with the lowest unemployment rates (Williams 2019a). CLTs are an effective mechanism when land and housing values are rising rapidly because they remove the speculative component of property values and create ownership opportunities for low-income people for the long term. Once it is part of a CLT portfolio, speculators and developers cannot purchase the land. The inability of real estate giants to develop property into lucrative hotels and condos creates a CLT neighborhood that is less likely to become gentrified and unaffordable to lower-income families. Further, the CLT-held land itself will certainly remain more affordable and accessible. Community organizers and other activists have become enthusiastic about promoting the CLT model (Hawkins-Simmons 2014).

The Dudley Neighbors CLT in Boston is a good example of this. Dudley Square is in the Roxbury neighborhood of South Boston and was a predominantly low-income area. Many vacant and tax-defaulted lots plagued the neighborhood, similar to Chicago’s Large Lots Program. Boston-area government and prominent financial institutions neglected the area as the neighborhood deteriorated throughout the 1970s. Over 20 percent of the land was vacant by the 1980s, with the remaining citizens composed of impoverished African Americans, Hispanics, and other minority groups that lacked the necessary financial resources to relocate. The City of Boston decided to transfer ownership of about fifteen acres, amounting to 1,300 lots, to a CLT.

Dudley Square residents responded by incorporating as a nonprofit called the Dudley Square Neighborhood Initiative (DSNI). They created a plan to build an urban village that would not displace the existing residents. This CLT built over 200 affordable homes on the vacant lots, a community greenhouse covering 10,000 square feet of land, a playground, an urban farm, and many other attractive amenities. CLTS collaborated with other community and grassroots organizations to implement the community’s vision for local development. They employed the CLT model to organize and construct a permanently affordable housing community that exercised the control of land necessary to fulfill their vision (Hawkins-Simmons and Axel-Lute 2015).

The Lincoln Land Institute of Land Policy has studied fifty-eight shared equity homeownership programs across 4,108 properties, where nearly three-quarters were managed by CLTs. Their analysis indicates that shared equity models have successfully delivered ownership of affordable homes to lower-income families across multiple generations. This is usually attributed to a combination of stable, below-market ground-lease prices and price caps on the resale of homes. The same study found that a shared equity model like CLT “provides financial security and mitigates risks for homeowners facing housing market turmoil,” and suggested that they helped low- and moderate-income residents navigate the volatile housing market fluctuations of 2008 more successfully than other conventional housing models (Wang et al. 2019).

Data has shown that such programs are serving buyers that might otherwise not be able to afford to purchase a home (discount metric) by preserving affordability for multiple generations of buyers (resale metric). Further, these programs allow homeowners to build wealth by retaining a portion of the gains in house appreciation or retiring mortgage debt. These shared equity programs offer a reliable path to sustainable homeownership. Grassroots organizations and CDCs have created CLTs in cities like Atlanta, Philadelphia, San Francisco, and Seattle to counteract urban gentrification (Mironova 2019).

Long-Term Resource Stewardship in Nonresidential Real Estate

Sometimes, CLTs steward land for both residential and nonresidential purposes through agriculture projects, green spaces, commercial spaces, playgrounds, other public centers for recreation or social services. For example, the Dudley Street (DSNI) CLT includes urban farm sites, parks and open space, and commercial properties (Loh 2015).

Though less common, other CLTs steward land solely for nonresidential purposes. For instance, Southside CLT (SCLT) owns or directly manages twenty-one community gardens, manages another thirty-seven community gardens with partner organizations, owns or manages land used by twenty-five farmers to supply to various food businesses (restaurants, farmers’ markets, community-supported agriculture), and operates three production farms, across Rhode Island.

Local agencies, neighborhood churches, and private schools own and manage these gardens, and the SCLT assists them in providing both training and gardening resources. Their goal is to create community food systems for locally produced healthy food to be affordable and available to all, with a focus on serving low-income urban neighborhoods that may not have access to fresh produce. SCLT also aims to provide the people of Rhode Island with access to land, education, and resources to grow food in environmentally sustainable ways. For instance, they engage in youth employment and children’s summer learning programs, farmer training workshops and apprenticeships, hands-on training in food preparation and food growing. They match farmers with landowners who want to keep their land in production. Finally, they have advocated for increased investment in farmland access programs by the state of Rhode Island and founded the RI Food Policy Council to develop policies and partnerships to increase the capacity, visibility, and sustainability of the local food system (Southside Community Land Trust n.d.).

In another example, the Northeast Farmers of Color Land Trust (NEFOCLT) is a CLT as well as a conservation land trust. It was established to center the voices of and secure land for Black, Indigenous, and People of Color to farm, to conserve land by protecting native species ecosystems and engaging in regenerative farming and agroforestry, and to advocate for climate justice. NEFOCLT also collaborates with allied organizations to provide training and education in markets, business development, and financial planning. They have plans to acquire land to build a flagship community with incubator farms, commons for production, childcare, healthcare, and integrated ecosystem restoration (Farmers of Color Land Trust n.d.).

Nontraditional Property Rights

Some CLTs have attempted to use nontraditional property rights to retain community ownership over land. For example, Chinatown CLT (CCLT) has negotiated for ownership over easements (Lowe 2018). It has reclaimed municipal public land by cooperating with other community partners to convince the city government to undertake a disposition process for a public parcel of land, which is now set to become a multiuse development. This project encompasses 171 separate units of affordable housing. The effort was led by a local community development corporation collaborating with multiple for-profit partnerships and has received strong support from both community activists and residents who shared the project’s vision. It is an example of what can be developed by cooperative efforts between a local community development corporation and potential financial partners.

This is also an example of how a nonprofit CLT can assure public access to a given site without owning the land. It can do so by using an easement as a legal contract and entering in a deed. The CCLT now advises the community as it negotiates long-term public access through easements for an existing courtyard as well as a future branch library. This arrangement rectifies the broken promises given to residents who were promised access to public open spaces that were soon privatized into beautiful but privately gated courtyards. The Friends of the Chinatown Library will have secured an easement that ensures open public access to the library, and the CCLT will have an easement for open public access to a public courtyard.

CLTs might also fund or invest in other projects, where they do not own or lease the land. Sacramento CLT is working with other CLTs on a major project to turn a local creek and surrounding neighborhoods into a space that is walkable, bikeable, and safe. Here, they and other neighborhood groups involved receive funding and permission to act as stewards of public land (Sacramento Community Land Trust n.d.).

Community Governance

A critical component of a CLT’s mission is its efforts to promote a bottom-up style of democratic governance, which is a key component of land stewardship and community control over the land. Collaborative community governance is what gives historically marginalized people a way to participate in decision-making about how their neighborhoods are developed. Classic CLTs have two modes of community governance built into their organizational structures and bylaws. These were well-defined actions designed to keep the CLT aligned with the interests of its residents, and to be held accountable to both its residents and surrounding community or service area. This enables residents and those of the wider community (which could encompass a single neighborhood, multiple neighborhoods, town, city, or county) to influence critical decisions made by the CLT.

The first mode is having a governing board of directors that represents the interests of the people and locality that they serve. The governing board of a CLT has traditionally been “tripartite” in design. This means there is an equal number of seats for (1) homeowners leasing the land from the CLT, (2) surrounding community residents not living on CLT land, and (3) public and private sector stakeholders, such as public officials and nonprofit organizations providing assistance to the CLT or its homeowners. The governance structure of the typical CLT thus differs from the closed, private governance of other common-interest communities such as condos and cooperatives, since the boards of these entities consist only of private property owners (Wu and Foster 2020). Board directors are typically volunteers, and their roles and responsibilities are set out in a CLT’s bylaws. They serve as key advisers on critical organizational questions, and often help with the foundational work of setting up the CLT when it is first starting out (Bath et al. 2012).

Traditionally, directors are elected by the membership – one-third of the board is elected by members who live on the CLT’s land, another third is elected by general members who are part of the community but do not live on CLT-owned land, and the last third is elected by the total membership or the board itself to represent the public interest (Grounded Solutions Network 2018). For example, Dudley Square’s CLT board is represented by local and nearby residents who enforce lease agreements and other obligations of the lessors. The board is structured to reflect appropriate cultural or ethnic groupings that make up the Dudley community. The board has thirty-five seats, twenty of which are reserved for community residents. This group of twenty also comprises an equal number of representatives of the four main ethnic groups inside the community. Board members serve two-year terms, and are elected by the residents. The elected board vets and approves all decisions made by DSNI, but these decisions are always open to community input and participation (Wu and Foster 2020).

Note, however, that the makeup and selection method of the board of directors may differ based on why and by whom the organization was created. CLTs may be established by an existing housing organization, nonprofit, or local government, as described earlier, and likely will not give CLT residents the same representation as a classic CLT. In these situations, the CLT’s board of directors may be partially or wholly appointed by the “parent” organization (which may itself be a membership organization elected by the community) (Grounded Solutions Network 2018).

The second mode is having a membership that elects the board of directors, which is similarly designed to hold the CLT accountable to its residents and the place-based community it belongs to.

The membership typically has two categories: one with all residents who live on CLT-owned land, and another with general members who opt in to support the CLT and pay annual membership fees. However, the makeup of a CLT’s membership varies between different organizations and their aims. For instance, they may retain the two categories but place restrictions on them. TRUST South LA, to achieve their mission of preserving opportunities for local working-class residents to remain in their neighborhoods, restricts their regular membership to low-income people who live or work in the land trust area. (T.R.U.S.T. South LA n.d.). Douglass CLT wanted a dedicated membership that is familiar with CLTs, which means their current membership is relatively small. While all residents may become lessee members, they are not automatically enrolled, but must affirmatively opt in. They have also put a cap on lessee members from different developments in their housing portfolio, to ensure that the membership is not dominated by voices from one development.¹ Some CLTs may choose to add different membership classes – some organizations, such as SMASH, EBPREC, and Cooperation Jackson, have created a separate membership category for the staff of the organization.

At Douglass CLT, the key responsibilities of the membership involve attending the annual meeting and weighing in major decisions such as voting on the board of directors, bylaw changes or other changes to governing documents, or the sale of property. Members may also pay dues, review annual reports, or serve as board and/or special committee members. In addition to these, there are other opportunities for members to participate based on their skills or interests, such as organizing events or sourcing new properties (Douglass Community Land Trust n.d.).

Aside from these two iconic organizational structures, there are also other methods in which CLTs provide the community with methods for engagement, leadership, or control.

One such method is starting up specialty committees within the CLT, which means a wider group of interested members can learn and participate with more flexibility or based on specific interests. The San Francisco CLT has volunteer committees working in the areas of policy, membership, fundraising, finance, and projects (San Francisco Community Land Trust n.d.). Sacramento CLT has held working groups where members have convened around vacant public lands, tiny homes, and land acquisition strategies (Sacramento Community Land Trust n.d.).

Another method is participatory planning. Participatory planning involves engaging the community in what they want to see developed in addition to housing built on the land trust. This could be commercial projects, a greenhouse, or even developing agricultural land. For example, the priorities for Boston Chinatown’s development of the community land trust involved scouting out and developing a vision for remaining public parcels. This work involved engaging with communities about what they wanted to see there and how their community land trust’s priorities could be served.²

A tangible example of how such decisions are worked out in the CCLT involves the Reggie Wong Park. The homes of one group of residents abut the park, in an area that includes the leather district. They wished to retain access to the park for family use while another group of residents wanted to play nine-man volleyball in the park. Even though some tension has existed around determining the top priorities for developing the park, the residents still have highlighted the opportunity to remain unified in the mission. The CLT brokered an agreement that allowed every group to access the park and helped build a bridge of understanding between the two groups, especially by communicating the Chinese residents’ stories. They helped publish an op-ed about why volleyball was so meaningful to the Chinese residents there. This work enabled these two groups to coexist in their use of the park.³

Issues in Theory and Practice

While the CLT model has great potential to empower marginalized people and communities, and many CLTs in the past and present have successfully done so, it is important to acknowledge some limitations of CLTs today.

Academics have noted that the original goals for community ownership of land and local democracy may no longer be the priority for many CLTs today (DeFilippis, Stromberg, and Williams 2018). Rather, many practitioners and advocates have focused on aspects of the model most aligned with individual property ownership, and CLTs have shifted to act primarily as providers of affordable homes. The CLT acts as landowner, property manager, and steward of affordable units, with most of their staff devoted to housing development and stewardship (Hawkins-Simmons and Axel-Lute 2015). With affordable homeownership as the primary goal, CLTs may no longer see community control of land as the goal, and the provision of affordable housing as just one potential method of achieving this and serving the community.

Prominent CLT scholars have hypothesized that this shift is due to realities of funding, issues of scale, limited methods of successfully securing broader political support, industry perceptions of success, and limited staffing capacity (DeFilippis, Stromberg, and Williams 2018). Most CLTs are not self-sustaining, and are financially dependent on external funding sources, which come with their own stipulations and agendas (Mironova 2019). In recent years, the housing crisis and affordable homeownership has increasingly been prioritized on political agendas, with CLTs starting to gain traction as a model to achieve this. Many CLT funders have thus supported residential developments for this reason. Additionally, nonresidential developments are less lucrative and more logistically challenging (Williams 2019b). It can also be easier to measure or demonstrate the impact of residential developments – for example, via the number of affordable homes secured. This may be why funding for nonresidential land uses, such as for playgrounds or community gardens, are much more difficult to find or attain.

Theoretically, the goals of affordable housing, reducing displacement, and community control go hand in hand, as they are all methods to assist low-income or marginalized people. However, academics have argued that the ground lease provides limited community control when CLT land is used for housing. For example, even though CLTs own land in perpetuity, community control is only exercised when new land is acquired. After the CLT leases the land out, typically for housing purposes, it is no longer able to make decisions, exercise control over, or access the land, as that is now the right of the homeowner to the exclusion of the rest of the community (Williams et al. 2018).

Furthermore, the focus on a narrow goal like providing affordable housing, rather than a broader, more systemic approach to empowering marginalized people through community control of land, means that many CLT funders may miss all the other ways the local community’s needs can be met or its residents engaged (Williams 2019a). There is a myriad of ways that communities may need or want to use land beyond residential developments – urban agriculture, commercial development projects – which may serve different needs of local residents and aid the resiliency of the CLT itself. Indeed, one study has found that CLT involvement with urban agriculture or commercial development projects can drive economic development, diversify the CLT social base, build new partnerships, promote organizational resilience, and increase organizational visibility (Rosenberg and Yuen 2013).

Another difficulty is that the burden largely falls on the frequently understaffed CLT to actively maintain a culture of participation. It can often be difficult to engage the community, as a study has found that efforts by staff to involve homeowners in greater participation within the land trust were unsuccessful (Thaden and Lowe 2014). One study found that homeowners/people were drawn to CLTs because they needed a place to live, rather than to engage with the community (Kruger et al. 2020). In conversation with Douglass CLT, they found that it was difficult to show people that it was worth getting involved in. There is the constraint of time – residents have day jobs (potentially multiple jobs), childcare, and other responsibilities. They already interact with CLT staff for logistical practicalities. There is a second constraint of demonstrating to people that their efforts would have an impact. Participation can be particularly difficult with underrepresented people, who have previously felt used, or have not seen results from prior efforts in participation. Additionally, it may be intimidating for some to speak up or participate when they are put in a room with unfamiliar people, some of whom may have more assertive personalities.

Though these issues illustrate some challenges of the CLT structure and norms to achieve the goal of community landownership, CLTs have chosen this management structure to better serve local communities in ways that are not possible through traditional private landownership.

CLT as Knowledge Commons

The CLT sector is home to a large knowledge commons, where information is a nonrivalrous shared resource that is collectively owned and managed by the community. Many practitioners have highlighted this critical need “to have knowledge and technologies that are owned by the movement, to transfer these practices across organizations and within organizations to community members” (Shatan and Williams 2020, 42).

In the following section, we explore the knowledge commons and information flows (1) between different CLTs through national, regional, and local networks, through formal and informal channels and (2) between individuals within one single CLT, meeting the need for knowledge to be owned by the CLT movement.

The conceptualization and grouping of inter and intra CLT interactions draws from literature around cross-boundary information sharing, and why individuals or organizations share information at interpersonal, intra-organizational, and inter-organizational levels (Yang et al. 2011).

While CLT practitioners engage in interactions both between and within CLTs for the benefit of the CLT they serve, the type of information shared, parties involved, meeting forums, and nature of interactions differ greatly. Interactions between CLTs provide practitioners space to navigate common obstacles, share best practices, and find emotional support. Interactions within CLTs are more varied in purpose and encompass most interactions that make up the day-to-day operations, functioning, and management of a CLT.

Interactions between CLTs

Between different CLTs, knowledge is often freely shared, and inter-CLT relationships are characterized by a collaborative ethic. Several CLT practitioners we interviewed mentioned that this is something they appreciate about the CLT sector and movement: practitioners are excited to share information about what they’re doing, and what has or has not worked for them.

The success and expansion of the CLT sector relies on documenting and publicizing useful data, and sharing technical knowledge, skills, and advice that covers the creation and operation of a successful CLT, between different CLTs through formal and informal networks.

These networks provide CLT members tactical and strategic support. The shared knowledge provides a starting point for practitioners to work from, despite the varying political and social landscapes that each organization occupies. They can speak about best practices for grant writing, strategies to collaborate more effectively with partner organizations, how to navigate property taxes, trends they are seeing, and to problem solve on making the CLT model work on a granular level. The network can help prevent duplication of effort between members to hopefully free up capacity for other work, and also leverage work that they each are doing to have maximum benefit. The regular communication and coordination also help local CLTs to align on their advocacy goals and shared reputation as CLTs to tell a larger, cohesive story across the region, which is important to secure funding, favorable policies, and continue to advance the narrative around CLTs.

Not only are CLT networks important spaces to think and problem-solve; the network and other members can provide solidarity and emotional support. As one practitioner said, it can sometimes be difficult not to get overwhelmed by the logistics and realities of running an organization or stewarding land. The networks and regular meetings can help remind them of their collective mission, principles, and the goal of collective community control and stewardship that is at the heart of what they’re trying to accomplish.

Within the United States, there are various networks and organizations dedicated to supporting existing and emerging CLTs through sharing experiences, connecting expertise, and deepening their knowledge base and capacities.

National Organization

Inter-CLT networks include national organizations such as Grounded Solutions Network, a nonprofit that focuses on building inclusive communities and affordable housing solutions by supporting practitioners and policy-makers.

Part of its work includes providing dedicated support to the CLT sector by conducting and publishing research to explore emerging ideas, working with policy-makers to advocate for policy change or secure resources (Grounded Solutions Network 2017), providing technical assistance, and developing publicly available resources, including a toolkit and technical manual that are published on its website. It also supports and works more directly with CLTs through initiatives such as the CLT Accelerator Fund and Catalytic Land Cohort Initiative. It has also provided resources on topics such as Covid-19, and step-by-step guides to help CLTs plan for advocacy initiatives and build relationships with elected officials and congressional representatives (all websites can be found at Grounded Solutions Network n.d.). One CLT staff member we spoke to mentioned that the roundtables and events, especially the national conference that GSN holds, as one of the best ways practitioners can get together. These have continued online over video conferencing technology through the pandemic.

GSN also aims to collect data on members’ portfolios to “improve sector-wide impact measurement and learning” and “better understand trends and characteristics of shared equity programs and homes and build support for the field.” The HomeKeeper National Data Hub Dashboard is GSN network’s publicly available database designed to evaluate the performance of affordable homeownership programs like CLTs, with the ability to filter across regions, market conditions, and demographics⁴ (Homekeeper 2021a). It calculates metrics such as the discount metric, which shows how the programs serve buyers who may not otherwise be able to afford to purchase a home, and the resale metric, which shows how affordability is preserved for multiple generations of buyers. The data is provided by organizations that use the HomeKeeper Program Management application, which they collect as they administer their housing programs.⁵ As of April 2017, this dashboard reflects the data of 54 organizations, 80 affordable homeownership programs, 6,000+ permanently affordable homes, and 7,400 home sale transactions. The data collected on this platform is able to inform policy and research and show stakeholders and funders how CLT programs have helped communities across the country. In 2016, HomeKeeper Hub data was used to help convince the Federal Housing Finance Agency to incorporate shared equity homeownership as part of its Duty to Serve rule that requires Fannie Mae and Freddie Mac to increase lending to underserved homebuyers (Grounded Solutions Network 2017).

When organizations have differing information systems, it can be a challenge to integrate these systems, bridge inconsistent definitions, and thus share data between organizations (Yang and Maxwell 2011). Before HomeKeeper, there were no standard data collection practices within the CLT sector or between CLTs, and this platform has helped to facilitate low-friction information sharing and use between CLTs.

There are also various online resources and groups dedicated to collecting, developing, and centralizing resources for CLTs, including the Schumacher Center for a New Economics and Lincoln Institute of Land Policy, which act as other points of knowledge collection and sharing.

Regional and Local Networks

Coalitions also exist to serve CLTs within a more concentrated geography, with a focus on sharing resources and building capacity of CLTs in specific areas, and more regular live meetings between peers that are often facing similar political, legal, or geographical circumstances (Schumacher Center for New Economics).

For example, the Northwest CLT Coalition enhances the activities of CLTs in the Northwest region, including across the states of Washington, Oregon, Idaho, Alaska, and Montana, and currently has twenty-nine member organizations. The California CLT Network supports CLTs across the state of California, and has twenty-three CLT members. The Greater Boston CLT Network was founded in 2015 to serve current and emerging CLTs in and around the City of Boston, with eight CLT members and other community group members. Some of these coalitions are formally incorporated (there are currently at least eleven across the United States) (Schumacher Center for New Economics), and have dedicated staff members.

Others are more informal. One such peer-to-peer network was created when several practitioners met at a GSN conference where they were panelists. The similarities that drew them together were their shared locations on the Atlantic coast (New York City, Pittsburgh, South Florida), and similarly aged organizations (all relatively new CLTs). After first making contact at the conference, when they returned home they engaged in informal skill and information sharing on issues and strategies ranging across community education, financial acquisition methods, rehab acquisition, and property management.⁶

No matter the size or region, these coalitions are characterized by similar aims and tactics. To serve as a means for established and new CLTs to connect, support, and share resources, tools, and information, and to collaboratively engage in operational and technical skill-building, they organize regular live meetings, workshops, or working groups. They might produce resources specific to their region – for instance, five California CLTs worked together to release the Building Healthy Communities Community Land Trust report with recommendations to philanthropists, media, and other partners about scaling up the CLT movement in California (Hernandez, McNeill, and Tong 2020). They may also inform and advocate on policy issues together. For example, multiple California land trusts worked together to advocate for funding for SB 1079 Homes for Homeowners Not Corporations, and to develop Senate Bill 490 (Caballero) to establish funding sources for technical assistance and building acquisition and rehabilitation by community-based housing justice groups (Sacramento Community Land Trust). Networks may also provide education to the public about CLTs to promote understanding of the model and efforts around housing advocacy or organizing. Finally, they may apply for grants or funding together, or collectively invest in or fund projects, acquisitions, new CLTs, or site development.

While many of these relationships may have developed through in-person meetings or interactions, communications often take place through phone calls or emails. This is especially true in the wake of Covid-19. At CCLT, Covid-19 has actually strengthened the peer learning within the network, as practitioners have become more electronically connected and engaged in more policy advocacy, geared toward existing local housing programs, especially as the problem of housing has been exacerbated by the pandemic.

Personal Relationships

Communication between individual practitioners of different CLTs can be highly informal and personality based, as part of a personal social network rather than affiliation or membership within any network. While the purpose and content of these interactions may be similar to interactions between practitioners within a network, personal relationship interactions are characterized by the one-on-one size (rather than a large group), a more ad hoc tone of meeting, and the individuals may not have common membership to any organization. These relationships can arise through meeting at a CLT-related event, referral by another contact in the space, or when previously working together in a different job or region.

According to information theory, an individual shares information when they make the connection between acquired information and the information needs of another individual (Rioux 2005). An individual might share information to establish mutual awareness, educate on a common interest, or to develop rapport and strengthen the relationship (Marshall and Bly 2004).

This is reflected within the nature of interactions between CLT practitioners, which are often reactive. Practitioners often check in with each other when a problem comes up in their work, to understand whether their counterparts are currently facing or have previously faced the same issue. They might also review issues and problem-solve together. Similar to the abovementioned effects of being part of formal networks, having these touchpoints with other practitioners can help to establish mutual awareness of common issues and solutions to bring back to their own work and communities. More than larger group meetings, these one-on-one conversations can help to build rapport and strengthen the feeling of solidarity. This is because informal coordination is not defined by a set hierarchy or structure, and can therefore lead to greater flexibility, openness, and potentially more effective information sharing (Jarvenpaa and Staples 2002).

Interactions within CLTs

The next layer of interactions that we examine are the information flows that occur within any single CLT. For this section, we take a broad definition of what constitutes interactions within CLTs, including any interactions between formal members of a CLT (such as staff, board members, or residents), as well as with the broader place-based community of which the CLT is part.

While there has been extensive research on intraorganizational information-sharing flows, most of this literature has focused on the behaviors and sharing between the employees of an organization. This research has raised concerns around competition between employees, and lack of incentive to share information due to a company’s hierarchical structure and organizational culture (Tsai 2002). The CLT is a unique case study because almost none of the interactions we describe take place between CLT staff. This is because many CLTs have one or fewer full-time staff members (Wang and Rose 2018), and because the nature of a CLT job is external facing and requires intense communication with stakeholders outside their own organization. Rather, most interactions we have detailed take place between a CLT staff member and a stakeholder with different relationships, responsibilities, and viewpoints about the CLT. For example, a full-time CLT staff member is under an employment contract and paid for their work. On the other hand, board members have committed to responsibilities but are likely not financially compensated for that work, and most residents who are not in leadership positions have no obligation to participate in CLT governance at all. Many of the factors that influence quantity and quality of information sharing between employees of one organization therefore may not be relevant to CLTs or other NGOs that share similar circumstances. As such, the information flows we study within a CLT present new types of interactions that are less represented in information-sharing literature.

Next, we map out the common types of information flows within a CLT.

Internal CMS and Record Keeping

The HomeKeeper application, developed by Grounded Solutions Network and built on the Salesforce platform, is a web-based application and enterprise CRM system used by CLTs across the United States. It helps programs track, manage, and report on homeowner, property, and funding data, and to measure impacts of their work, all in one system. This helps standardize program administration among program staff, run daily operations, make program decisions, and tell an impact story (i.e., return on investment for sellers, the growth of community investment over time, and the extent of affordability created by the program). For instance, Athens Land Trust uses HomeKeeper to track individuals who are interested in their program. One staff member said he groups prospective homebuyers by income, and when a property becomes available in their price range, HomeKeeper allows him to quickly run a report and contact the group with information about the home (Grounded Solutions Networks 2017). This data is also aggregated and anonymized to feed up to the public HomeKeeper dashboard, described earlier.

Information Flows between CLT Staff and Residents

All Residents: Education for Personal Financial and Homeownership Resilience.

A key CLT stewardship strategy is the transfer of personal finance and home management knowledge from CLT stewards to CLT residents. This is one of the most significant and impactful information flows that occur within a CLT.

According to studies done by the National Community Land Trust Network, “85 percent of CLTs required general homebuyer education and 95 percent required a CLT-specific orientation” (Thaden 2010). These generally take the form of educational programs and workshops, as well as one-on-one consultations or advice. For example, 1Roof’s CLT program involves a Home Stretch workshop of homebuyer education, which helps attendees determine their readiness to buy a home, understand credit and its impact on the home-buying process, decide what type of mortgage is best for their needs, select the right home, understand the loan closing process, understand the roles of local professionals (i.e., local loan officers, realtors, home inspectors, closing agents, home insurance professionals), and learn about local mortgage loan and down-payment assistance programs (1Roof Community Housing 2019). The CLT-specific orientation at Douglass CLT provides education on what CLTs are, what shared appreciation is, and advice about whether a CLT model suits the individual and their situation (i.e., can they afford to buy something without economic restrictions instead?).

The NCLTN study also found that about half of CLTs offer post-purchase services, including ongoing monitoring and early issue spotting and intervention. These include financial literacy training, referrals to contractors for improvements and repairs, loan review and approval, and mandatory counseling for delinquent homeowners, which all “build homeowner competency and security.” Typically, CLT staff are often also in contact with residents as the situation arises on an ad hoc basis and provide hands-on assistance and counseling through phone calls and house visits. Residents will call about housing-related problems that have arisen, whether because the housing management company is not responding, they have a question about the land lease fee, or there is an emergency.

“These stewardship activities … address the challenges and risks that may arise over the course of a lower-income household’s acquisition and operation of a home” (Thaden 2010). This knowledge foundation and open flow of communication provided by the CLT is often thought of as key to the low rates of CLT mortgage foreclosures even in times of macro- and microeconomic distress.

A 2019 report published by the Lincoln Institute of Land Policy studied 58 shared equity homeownership programs and 4,108 properties (73 percent of which were CLTs) over the past three decades. It found that shared equity models like CLT “provides financial security and mitigates risks for homeowners facing housing market turmoil,” and suggested that they helped low- and moderate-income residents navigate housing market fluctuations in 2008 more successfully than other conventional housing models: 51 percent (of fifty-seven) seriously delinquent CLT homeowners were able to avoid foreclosure due to the help of their CLT in the 2009 financial crisis (Wang et al. 2019).

Anecdotally, similar results and strategies are already starting to show in regard to the impact of Covid-19, which has had similarly dire consequences in foreclosures and evictions. For example, Grounded Solutions Network representatives have noted that CLTs have been modifying rents to help residents and have advocated on behalf of residents to change interest payments. OPAL, a land trust in Washington state, has also mentioned a policy with residents of “pay what you can when you can,” and providing assistance by consulting with tenants for tailored advice, connecting them with existing resources, and thinking through payment plans.

In the eleven months between March 15, 2020 and February 12, 2021, when Covid-19 hit the United States, none of the 228 current CLT homeowners in the HomeKeeper system had suffered foreclosure (HomeKeeper 2021b). In comparison, between June and August 2020, 7 percent of people surveyed nationwide experienced eviction or foreclosure (US Census Bureau n.d.). These knowledge resources enable the economic development of residents and continued tenure of their homeownership.

Covid-19, Digital Tools, and Channels of Communication.

Due to Covid-19, residents are hard to contact, especially with stay-at-home and social distancing rules. The solutions that CLTs are using to mitigate this include manual reach-outs for early detection of risks, technology adoption (such as accepting virtual paperwork and e-signatures, building websites to push information out, member portals), and holding meetings online on video conferencing tools and virtual training. These projects were prioritized because of Covid-19, as organizations knew they couldn’t get people together traditionally. It is hard to meet anyone in person, and difficult to build trust and get people to participate if the relationship of trust was not already there.

This issue is exacerbated by the digital divide and the lack of residents’ access to or knowledge of technology. While CLTs as a sector are continuing to figure out how they bolster their tech (i.e., e-signatures), homeowners are within a certain income bracket, and their technology is not very good. Their main communications technology is phones. The question becomes: how do you bridge that divide of having a homeowner give you documents when those documents have to be photographs of paper without very good resolution? The issue is exacerbated for elderly people , as well as for those who are not native English speakers.

For example, CCLT has noted that the elderly feel less comfortable with technology, making it hard for them to participate. Historically, CCLT’s strongest resident involvement and connection has been with elderly Chinese-speaking residents who have not received a lot of education. However, they are now the most difficult sector to stay connected to. They may not have the tech, and if they have the tech, they can’t figure out how to use it. CCLT has worked together with other community organizations to produce bilingual guides to technologies and phone operating systems, as well as a Chinese language workshop. However, that often still involves patience and time to help someone with the tech, something that is often taken on by volunteers. There are also unique challenges to holding online meetings on video-conferencing tools in two languages, such as increased cross-talk.

Resident Leaders and Board Members: Building Leadership Capacity.

As part of a CLT’s community governance structures, there are also residents who are highly involved in leadership and functioning of the CLT – for example, board members or active residents who are highly involved in specialty committees.

CLTs rely on their membership or board of directors to help answer questions that may be very technical, legal, or financial, but many community members may not have the technical skills or experience. This means that CLTs face the challenge of making these questions accessible, and to pass this technical knowledge on to community members. CLTs therefore need to build and utilize their knowledge commons to create practical training and learning opportunities for their resident leaders to govern and manage the CLT in the long term. Capacity building is also crucial to having an equitable and representative board or membership that represents the community the CLT aims to serve (i.e., those with knowledge of the community’s needs, and recognized by the community as having this knowledge) (Community Land Trust Network 2018). Training can ensure technical skills or experience do not become a barrier to participation, while also equipping interested participants with the ability to address those needs and govern effectively (Bath et al. 2012).

Areas in which participants may receive training include budgeting, fundraising, legal agreements, property management, project management, effective board membership, transformative politics and racial justice, and an understanding of how to build relationships and run an organization cooperatively (Shatan and Williams 2020). Training may take the form of orientation for new board members, annual board retreats, attending or participating in CLT conferences or government programs, or organizing seminars through hired consultants or local community agencies. Knowledge may also be passed through informal conversations between members, and through written materials like the bylaws or strategic documents (Bath et al. 2012).

Douglass CLT has invested heavily in building the capacity of its board of directors, who are elected by the membership, and have remained the same fifteen members for the last two years. Douglass CLT has engaged in leadership training, organized technical education sessions, and brought board members to conferences where they spoke on panels and met others in the CLT network. They noted that the conference was crucial for them to make new connections and build their confidence as community leaders in their CLT.

Resident Leaders and Board Members: Engagement Obligations.

As part of their relationship with the membership and governing board, CLT staff engage them in important decision-making, keep them informed of upcoming events, and reach out when major issues arise. These responsibilities are typically outlined in the CLT’s bylaws.

A board itself may also further delineate roles within an executive committee of several officers, such as a chair, treasurer, and secretary, which the board itself elects. Given the specialized role that any individual board member may play, as well as each of their duties to participate, information flows also occur between the members and without any CLT staff. This may occur when ensuring that board members are fulfilling their responsibilities, and facilitating constructive communication between members (Bath et al. 2012).

While these boards are a critical resource, serving as key advisers and decision-makers, their time is limited given that they are often volunteers. As such, CLT staff must concisely detail and report to the board what is most important, providing them with the information they need, in a such a way that they can quickly digest and act on it.

Issues of privacy come into play with this information flow, as CLT staff must ensure that they keep personal information about residents private. This may be difficult as they may work with one individual in several capacities (as a resident, lessee board member, friend, etc.), and the appropriate boundaries of each capacity must be respected as they interact and share information. CLT staff must take care to not overcommunicate personal details or reveal potentially sensitive information to organizers on the ground, while still enabling those individuals to do their jobs. In practice, this means that CLT staff limit the information they share to a need-to-know basis, according to context – they may report to the board that people are behind on rent, and aggregate figures, but not the details of specific individuals who may be behind on rent and why. The motivations behind this behavior exemplify Helen Nissenbaum’s (2004) theory of contextual integrity, or the idea that privacy is maintained in information flows when those information flows conform with the norms, expectations, and accepted behaviors in a particular context. In this case, the context is the capacity in which each individual is acting in relation to the CLT, and the fact that this information exchange is occurring for the benefit of the CLT.

Interestingly, this parallels the situation of the CLT being unable to access or directly manage CLT land that is used for housing purposes (i.e., that is being leased to a private homeowner). Here, due to privacy concerns, members of the board may not be able to access or directly manage information about a resident that is collected by CLT staff. Just as CLT board members, staff, and other community members do not have access to CLT land that is leased out, many of these stakeholders also do not have access to specific homeowner information that could potentially influence aggregate homeowner group behavior in a way that would promote the best interests of the CLT and/or the community. However, while the inability to access CLT land used for housing purposes illustrates an inherent limitation to the CLT structure within the existing US laws of real property, the restriction of information flows due to privacy norms does not present the same barriers to a CLT’s goals. In fact, ensuring that privacy is maintained can build confidence and create a trusted network for sharing information between individuals (Razavi and Iverson 2006). It is also unclear whether having specific, detailed information about individuals would help decision-makers more than aggregated figures or trends that they already have access to, further reducing the impact of this privacy tradeoff.

Information Flows between CLT Staff and Partner Organizations

As described in a previous section, CLTs have relationships with various partner organizations, ranging from grassroots organizations, resident associations, social service agencies, community development groups, small landlords, the government, funders, developers, other CLTs, and other mission-aligned organizations (Shatan and Williams 2020). Some are peer organizations that work to produce programs jointly, and information flows equally between both parties in service of this. However, CLTs may have formal obligations to other organizations, such as reporting requirements to funders or the board, and the onus is on the CLT representative to share information in meetings or by preparing reports.

Information Flows between CLT Staff and Policy Stakeholders

CLTs also educate stakeholders in the public sphere (elected officials, politicians, political staffers, municipal workers) on the CLT model and its goals/benefits, and advocate for legislative priorities that support the CLT sector, housing, affordability, or other issues in their community. This is often done in partnership with other CLTs through CLT networks or other mission-aligned nonprofit organizations, but is also done by individual CLTs on issues specific to the concerns and lived experiences of their place-based community. This includes issues such as short-term rentals, vacant properties, parking permits for their cities or neighborhoods (Shatan and Williams 2020), improvements to the local food system, and farmland access programs (Southside Community Land Trust n.d.). This type of advocacy can work not only to inform policy stakeholders, but also to build trust and support for their work within their community.

Information Flows between CLT Staff and the Public

CLTs may educate the public about the CLT model and provide community services. This is especially true for nonresidential CLTs, as their use of the land they steward tends to benefit all residents in the area rather than just one homeowner, whether that is through a playground or community garden. Their programs also tend to gear toward educating and benefiting all in the community, rather than just the homeowners or residents in their portfolio. For example, SCLT in Rhode Island engages in publicly available youth employment and children’s summer learning programs, farmer training workshops and apprenticeships, and hands-on training in food preparation and food growing (Southside Community Land Trust n.d.). Other CLTs may hold publicly available classes introducing the CLT model or educating on the home-buying process in venues like the public library. Most CLTs today also have an online presence through a dedicated website or social media, where they may provide resources or communicate updates to the public and other interested parties.

CLT as Cultural Commons

Finally, in this section we explore the unique sense of community that acts as another shared resource within a CLT. In Labor and/as Love: Roller Derby as Constructed Cultural Commons, David Fagundes (2014) states:

community that roller derby provides can be regarded as a commons as much as shared knowledge about derby can. Fellowship is a nonrivalrous, incorporeal resource that is nonrivalrous and intrinsically nonexcludable, but is rendered excludable in that it is limited to those who are part of the relevant insular community (i.e., the roller derby world). Moreover, the sense of kinship that derby provides is something that its participants want to get out of their experience. In this sense, then, community is a resource that derby enables its members to extract.

This concept of fellowship also manifests itself among CLT homeowners in an unexpected way. One of the few studies done on what “community” means to CLT members found that few meaningful or long-term relationships form between residents of a CLT. After an individual completes the homeownership process and becomes a resident of the CLT, many just want to live their lives, rather than becoming more involved with the CLT. There is also not much interest in getting to know the other residents of a CLT, nor do they feel an affinity with other current residents (Kruger et al. 2020).

However, there was a nontraditional form of “community” that emerged within the studied CLTs: between the current homeowners and the CLT organization and future homeowners. “For homeowners, community was often defined as the ability of the CLT organization to provide the engagement and stewardship that will contribute to the long-term success and stability of the low-income homeowner through the challenges of homeownership” (Kruger et al. 2020, 649). The relationship is built through providing the types of stewardship activity described above, which help homeowners feel cared for by the CLT and feel secure in their homeownership, and also believe that the CLT will continue to exist and help future residents. In turn, this relationship of care and trust forms the basis of a kinship between present-day CLT homeowners and the future homeowners who will eventually occupy this land, and a responsibility to those individuals “of ensuring that said property would be taken care of so that a future family could enjoy the benefits of homeownership in the same manner that they are currently” (Kruger et al. 2020, 651).

By being a part of a CLT, many residents “derive satisfaction in knowing they – as CLT homeowners – can also care for and steward the future” (Kruger et al. 2020, 653). This unique feeling is like that described by Fagundes earlier – the sense of responsibility and kinship to future homeowners is a resource that CLTs enable its residents to gain.

This is because it is the proactive efforts of CLT staff and the management team that creates the sense of community toward future homeowners in the CLT managed community. The sense of community is not endogenously created through the homeowners interacting among themselves; rather it originates from the care and trust that homeowners form through interactions with the CLT management team. The ability to create “community” rests with the CLT, and thus may be considered another aspect of a cultural commons within the CLT model.

Conclusion

This chapter explored various aspects of CLTs, focusing on how this model effectively functions as an ownership structure for commons. Our parallel analysis on a CLT’s physical and cultural commons draws on Elinor Ostrom’s work on the governance of material resources, as well as information theory and the Governing Knowledge Commons framework. This work contributes to existing knowledge commons scholarship using CLTs as a unique case study of community property governance and knowledge commons management, and enables the CLT community and practitioners to better understand current practices by providing research and analysis in those areas where academic literature is scarce to nonexistent. Collective property rights and governance mechanisms are critical, but so are the types of strategies that serve as the bridge between the structure and its ability to overcome social dilemmas, given the communities’ needs and goals.

The CLT is a nonprofit, communally owned land management organization that employs a governing board to act as a long-term steward of its land by leasing it to private homeowners and other community-based organizations. This distinctive resource management structure is driven by the goal of benefiting all the people living in a localized community – particularly financially vulnerable individuals and traditionally underserved groups. However, the analysis reveals how this management structure also faces many challenges to align the motivations of the CLT board with the very people that the CLT exists to serve in order to achieve an optimal community land stewardship arrangement.

For example, while common ownership of land legally creates a variety of helpful restrictions that prevent real estate speculators from driving up property prices, it can also decrease the financial incentives of lessees to efficiently invest in preserving and improving the land upon which they reside. Additionally, the governing CLT boards typically have representation from the homeowners and other stakeholders from the area to better serve the needs of the local community. Yet these same boards also depend on public and private contributors to financially sustain their operations, which makes them potentially beholden to the influences of entities outside the community. Moreover, the focus on housing and the ground lease structure can limit the potential of the CLT to manage its property more effectively for the benefit of the local community.

This land commons management structure creates additional challenges for the CLT board that arise from both an information commons and a cultural commons. First, CLTs rely on interorganizational information flows where knowledge sharing creates greater efficiencies. This includes valuable advice on designing and executing various intraorganizational processes that exploit this common knowledge and expertise.

Second, a culture has been created between existing CLTs around the country that has produced many examples of endogenous mutual support in this information-sharing effort, including examples of mutual encouragement between separate CLT management teams to address overwhelming challenges, such as the Covid-19 pandemic. Yet this contrasts with the culture that has developed between the CLT board and the private homeowners and other lessees residing on CLT lands. Many empirical observations indicate that an edifying culture results only after proactive engagement is implemented by CLT management, specifically actions that invest in the ongoing success of the homeowners and the other lessees.

Ultimately, there are many real-world success stories of CLT organizations achieving the very goals they were designed to fulfill. These organizations have chosen this management structure to serve local communities better in ways that are not possible through traditional private landownership, and they have overcome the difficult challenges inherent in managing a common pool resource. A greater understanding of how CLTs have surmounted these challenges can assist future efforts to establish new CLT organizations.

5 Smart Tech Deployment and Governance in Philadelphia

Brett M. Frischmann and Marsha Tonkovich

Introduction

This case study focuses on smart tech deployment and governance in Philadelphia. In 2019, the City of Philadelphia launched a new smart city initiative, SmartCityPHL. SmartCityPHL includes a roadmap of strategies, processes, and plans for deployment. In many ways, the new initiative is remarkable. It is ambitious yet pragmatic; it outlines a set of guiding principles along with deliberative and participatory processes; it is broadly inclusive of people and values – as reflected in its simple definition of a smart city: “a city that uses integrated information and communication technology to support the economic, social, and environmental goals of its community.” On its face, and perhaps in comparison with other smart city initiatives, SmartCityPHL provides an exciting roadmap. But the 2019 initiative was not the first smart city project in Philadelphia. There is, in fact, a long history of Philadelphians turning to supposedly smart technology to solve community problems.

As with many smart city case studies, it is difficult to choose a starting date or focal point to study. After all, Philadelphia has long relied on data and technology in many different sectors, ranging from education to policing to traffic management. A longitudinal history across many sectors and decades would tell a fascinating story that could fill volumes. We will not dig that deeply or widely, however. Instead, we choose two nested “action arenas” as focal points.

First, we examine the macro-level action arena, which concerns city-wide governance of smart tech deployment, reflected in the set of smart city initiatives culminating in the current SmartCityPHL program. We briefly outline the descriptive characteristics of this action arena, and then we discuss the imagined and actual pictures of Philadelphia as a smart city from 2011 to 2016 and compare them with what has emerged over the past five years. This comparative analysis usefully highlights different applications of smart tech and conceptions of the smart city as well as evolving norms, goals, strategies, and governance.

Second, we examine one meso-level action arena, which concerns city-wide governance of vacant property management. In this context, smart tech deployment plays varied roles. We first describe a complex array of historical and contextual factors that shape the vacant property crisis in Philadelphia, and then we focus on stakeholders, knowledge problems, and potential smart tech solutions. We explore some useful implementations of smart tech, primarily data sharing and mapping tools. We also identify a series of governance challenges, including some concerning political structure, coordination of organizational responsibilities, and community inclusion.

Methodology

For both action arenas, we examine smart tech deployment and governance. Our primary aim is description, not normative or empirical outcome evaluation. We used the GKC framework, described in Chapter 1, to structure our mixed methods research.

The team reviewed dozens of publications, including academic articles, government reports, industry papers, newspaper articles, and websites. As is further described in the Appendix, we used a content analysis process to review these documents. Along with our team of research assistants, we developed a coding system based on the Governing Knowledge Commons (GKC) framework and relevant subject matter topics. The assistants coded the documents, and we used AtlasTI, a software program, to organize and analyze the data. The team then developed reports and charts describing the frequency of key concepts. The Appendix contains additional detail regarding the coding process, as well as summary charts.

After a protocol review by the Villanova University IRB, we conducted twelve semi-structured interviews with professionals directly involved in smart tech deployment in Philadelphia. We used the GKC framework to provide structure and generate interview questions. We recorded, transcribed, and summarized the interviews, which averaged sixty-four minutes. The research assistant team then coded the content of these interviews using the same process outlined above. Finally, we integrated the background and interview information in our main findings outlined in this chapter. Prior to publication, we used a member checking process to ensure accuracy of the interview citations and quotes; we shared the draft study with interviewees for review and additional feedback.

Background Context

To situate our discussion of Philadelphia’s smart city approaches, we briefly describe some of background facts concerns the social, economic, and political context (Table 5.1). With a population of nearly 1.6 million (US Census QuickFacts Philadelphia 2021),¹ Philadelphia is America’s sixth largest city, recently dropping one ranking behind Phoenix (Castronuovo 2021). Philadelphia’s population is among the poorest of any major US city, second only to Detroit (Statista 2022). The city also has relatively low levels of educational attainment and workforce participation and a relatively high unemployment rate, connecting to a median household income that is nearly $16,000 less than the national median (US Census QuickFacts Philadelphia 2021; US Census QuickFacts United States 2021; St. Louis Federal Reserve 2022). Philadelphia is home to nearly 700,000 employed persons and its major industries are healthcare and education (33 percent of employment), government (14 percent), and professional and business services (15 percent) (Bureau of Labor Statistics 2022). Of the total Philadelphia jobs, nearly 100,000 are in the service sector, which on average in Philadelphia pays $10.71 per hour (Harknett and Schneider 2018).

Table 5.1. Socioeconomic background Philadelphia

	Philadelphia	United States
Population (July 2021)	1,576,251	331,893,745
Proportion without high school degree	14.3%	11.5%
Proportion in labor force	61.5%	63%
Median household income	$49,127	$64,994
Unemployment level (Dec. 2021)	6.3%	3.9%
Persons in poverty	23.1%	11.6%
Proportion with a computer	88.5%	91.9%
Proportion with broadband subscription	80.5%	85.2%

Sources: US Census QuickFacts, Philadelphia 2021; US Census QuickFacts, United States 2021; St. Louis Federal Reserve 2022.

Likely due at least in part to its economic challenges, the citizens of Philadelphia generally have reduced access to computers and the internet when compared to the nation overall. The percentage of households with a computer is 3 points lower than the nation and is lower than many other major American cities such as Houston (91.5 percent), Phoenix (93.8 percent), New York (90.8 percent), or Chicago (90.4 percent) (US Census QuickFacts: Houston 2021, Phoenix 2021, New York 2021, Chicago 2021). Philadelphians also have reduced access to the internet, with a little less than 20 percent of its population lacking a broadband subscription, again lower than the nation and the other major US cities previously mentioned (US Census QuickFacts Philadelphia, Houston, Phoenix, New York, Chicago, United States 2021).

The City of Philadelphia is governed by a home rule charter first adopted in 1951. This type of governance allows the city to have direct control over all municipal matters not explicitly denied by the state constitution, rather than the more traditional model where municipalities are only allowed to act in ways expressly provided for by the state. The home rule model has given the City incredible flexibility in governing its citizens and wide discretion to adopt new technologies to solve problems. Philadelphia functions as a consolidated city and county government. It is considered a mayor–council form of government, with separate elections for each of these types of political leadership (National League of Cities n.d.). The Philadelphia City Council plays a significant role in local public policies.²

Smart City Planning and Governance (Macro-Level Action Arena)

Philadelphia has always used technology to solve problems, provide public services, and otherwise manage its affairs. Over the past few decades, the city’s approach to deploying supposedly smart technologies and becoming a “smart city” has evolved. For this study, we examine how the City of Philadelphia has approached smart tech deployment over the past decade. City planning is a complex topic. The politics alone are daunting. To avoid getting mired in those details, we maintain focus on the city’s evolving strategic plans, practices, and governance for using “smart tech” to improve public services and achieve other community objectives, including becoming a twenty-first-century smart city.

At the macro-level of city-wide planning and governance, there is an incredibly wide range of shared resources, but the most important for the purposes of our study appear to be expertise, political capital, shared commitments and values, various types and collections of data (including personal information), and various forms of information technology (IT), sensors, communications networks, and other components of smart tech. Although not sharable because it is rivalrous, financial capital is also important because its allocation is a significant indicator of priority. We discuss specific shared resources in more detail in the sections that follow.

Community members can be described very broadly, but with respect to city planning and governance, we can differentiate the entire Philadelphia community from smaller subgroups directly involved with and affected by city planning. We can distinguish government, industry, academic, and citizen groups. Within those groups, we can draw further distinctions based on political, socioeconomic, instrumental (e.g., job function), or other characteristics. For example, for government, we can differentiate elected officials, departments, bureaucrats, and various government employees and contractors providing public services. At this level of abstraction, it might not be useful to delineate community members. We discuss community members further in the sections that follow.

At the macro-level, laws, regulations, policies, and norms all play a role in governance. Politics and public opinion also play important roles. For smart tech, procurement and privacy policies supply basic rules-in-use, some of which we discuss below. We discuss two additional sources – a series of Executive Orders and the SmartCityPHL Roadmap.

Smart City Planning and Governance: 2011–2016

In Philadelphia, the smart city imagined around 2011 was optimistic and familiar, essentially what was pitched in so many marketing materials and TED talks. Mayor Michael Nutter championed smart tech and the idea of Philadelphia becoming a smart city, both to solve local problems and to compete globally. In speeches, such as his 2012 keynote speech at IBM’s Smarter Cities Summit, Nutter incorporated “a common rhetorical theme in the … presentation of Philadelphia as a smart city, a theme enrolled in an ongoing, entrepreneurial economic growth agenda that oriented the city towards globalized enterprise” (Wiig 2016, 537). Themes of modernization and technological advancement permeated the rhetoric surrounding Philadelphia’s smart city initiatives. Creating a “[p]erception of Philadelphia as an innovative place with a dynamic economy was crucial to maintaining forward momentum to turn the city into a vibrant node in the globalized economy, instead of a failed, nineteenth and twentieth century industrial power” (Wiig 2016, 548).

The mayor’s ambitious agenda was exemplified by two distinct and very different agenda items (meso-level action arenas worthy of more detailed, independent study): the city’s engagement with IBM on the Digital On-Ramps project, and a series of Executive Orders issued by the Mayor’s Office.

Digital On-Ramps

Like many cities, Philadelphia has faced and still faces major obstacles in delivering educational and workforce training services to its citizens (Wiig 2016, 541). It is a rather complex social problem. Could smart tech be the solution?

In 2011, Philadelphia was one of twenty-four cities chosen to receive a Smarter Cities Challenge grant from IBM. This IBM reward led to a direct consultation. A team of IBM experts spent a few weeks working on a report that delivered recommendations on how the city could use smart tech to increase literacy and improve employment opportunities in Philadelphia. The solution IBM recommended, and advised on, was Digital On-Ramps (DOR) (Wiig 2016, 536).³ DOR was “a workforce education portal that would link unemployed or underemployed residents to online, easily accessible training modules for work in emerging industries of the globalized economy” (Wiig 2016, 540). According to IBM’s Smarter Cities Challenge Report, “[DOR] will provide Philadelphians with a framework for delivering comprehensive education and workforce training to youth and adults, using a blended learning approach” (IBM 2011, 4). The initiative was a part of an “ongoing, entrepreneurial economic growth agenda that oriented the city towards globalized enterprise” (Wiig 2016, 536). Incorporating familiar “rhetoric of the smart city, wireless, ubiquitous computing offered the potential to connect residents to digitized information that could take the place of civic services formerly found in physical locations, [in this case,] to move educational services from schools and community centers to a digital application” (Wiig 2016, 541). The DOR program sought to create

one of the largest and most effective citywide human capital management systems in the United States. The vision for DOR is that it will allow citizens to access education, training and support to assist them in developing literacy, digital literacy and workplace skills. The ultimate goal is to put unemployed citizens back to work, and help employed people advance to better paying jobs and careers.

(IBM 2011, 39)

Could an online portal and smartphone app deliver these services and meet the ambitious goals set by IBM and the Nutter administration?

No, at least not at that time.⁴ “[A] workforce education application could never, on its own, provide pathways for jobs for the 500,000 the Mayor claimed were in need of new skills” (Wiig 2016, 548). Nutter praised the initiative in his 2012 speech as if it had already been successful, but it had “neither recruited a single participant nor secured a job for anyone” (Wiig 2016, 536). According to Shelton, Zook, and Wiig (2015, 21), the DOR was driven mostly by hype, and “the smart city … acted primarily as a promotional vehicle.” The potential of the program to spark a substantial “change to the endemic poverty, marginalization, and social polarization in Philadelphia was present, but the smart city discourse relied too much on the possibility of new industries locating in Philadelphia in the near future because of the presence of a trained workforce, rather than on providing jobs for residents in need” (Wiig 2015, 536).⁵

One might say that IBM and others sold “tech solutionism” (Morozov 2013), and Philadelphia, at least Mayor Nutter, bought it.

A more charitable interpretation of the events is that the Nutter administration submitted a grant proposal, received a grant, ran a pilot, and learned that the smart tech intervention was not enough. As we discuss later, perceptions and expectations about smart tech varied among community members and have evolved with this and other experiences. However one interprets the DOR story, our study strongly suggests that community members learned and adapted their expectations (as will be discussed).

Smart Tech Planning and Governance via Executive Order

Alongside the DOR project, Mayor Nutter adopted a pragmatic governance approach rooted in conventional public administration.⁶ He issued a series of Executive Orders, which set goals, clarified responsibilities, provided direction, generated positions and working groups, and paved the way for smart tech deployment and data sharing in Philadelphia.

Mayor Nutter’s Executive Orders⁷ have their roots in EO 11-93 issued September 15, 1993 by Mayor Rendell. That order established the Mayor’s Office of Information Services (MOIS), which had the responsibilities of:

(1) establishing a strategic information technology plan, (2) establishing an IT steering committee to support strategic changes across the city, (3) to perform the needed assessment, development, operations, and maintenance of information systems applications across the city, and (4) establishing and operating an end user information center to provide re-engineering assistance and training in City standard IT policies.

The MOIS lasted until May 28, 2008, when Mayor Nutter signed EO 08-08, which established the Division of Technology (DOT). EO 08-08 focused on bringing Philadelphia into the digital era through the establishment of key positions and committees to oversee technology-based decisions. On July 6, 2009, Mayor Nutter signed EO 06-09, which effectively restated EO 08-08 with more explanation of various roles and responsibilities.

On August 22, 2011, Mayor Nutter signed EO 12-11, which took the existing DOT and restructured it into the Office of Innovation and Technology (OIT). OIT had the same responsibilities as the DOT, modified with language concerning interdepartmental cooperation and communication. EO 12-11 remains the guiding order on the structure and goals of OIT, which includes bridging the use of technology and information systems across city departments. EO 12-11 requires OIT to manage “[(1)] City telecommunications and information technology contracts, competitive bids, and requests for proposals … [(2)] establish information security policies … [and (3)] establish a Five-Year Strategic and Financial Plan defining … policies, procedures, processes, [and] guidelines … for Citywide telecommunications and information technology operation” (Executive Order 12-11, Information Technology, of August 22, 2011). The new OIT included several key positions and bodies including the Chief Innovation Officer (CIO), and the Technology Advisory Committee (TAC). The CIO serves as the head of the OIT and is responsible for managing the city’s technology and information systems as well as software acquisitions. The TAC serves to “provide strategic advice and counsel to the Office of Innovation and Technology and the CIO” (Executive Order 12-11, 4) It is comprised of thirteen people including the Managing Director, who serves as Philadelphia’s Chief Operating Officer, the Mayor’s Chief of Staff, the Finance Director, the Budget Director, the City Solicitor, the CIO, and several deputy mayors of various departments throughout the city.

Working in tandem with EO 12-11, chapter 21-2500⁸ of the Philadelphia Code and Home Rule Charter requires that the Managing Director of the TAC produce and submit an annual information technology strategic plan to city council. According to the ordinance, the plan must “summarize and evaluate the current state of the City’s telecommunications and information technology infrastructure and detail and analyze the costs and benefits of the City’s plans for the acquisition, management, and use of telecommunications and information technology over the next five fiscal years” (Philadelphia Home Rule Charter § 21-2502).

On April 26, 2012, Mayor Nutter signed EO 1-12, which introduced five main goals for the City of Philadelphia concerning data use and transparency: the formation of an open data working group, the governance of data by an advisory board, an open government plan, an open data policy, and a social media policy. These five sections created policies and positions for administrators to do work involving data that has subsequently shaped Philadelphia’s data policies and plans over the last several years, including the SmartCityPHL Roadmap, which we discuss below. Notably, EO 1-12 established the Chief Data Officer (CDO), who is responsible for spearheading the open data initiative for the city.

EO 1-12 established an Open Data Policy in Philadelphia. The policy has eight main components, including the establishment of an Open Government Portal for sharing information related to the Executive Order, the establishment of an Open Data Catalog where each department in the city is required to catalog their data to determine if it needs to be shared in the Open Government Portal. The order also made clear the need for city departments to announce a timeline for the release of their data, the desire for public feedback as a mechanism for citizens to request data or share input about what information should be published, the identification of high-value datasets, and a six-month evaluation of the city’s progress toward fulfilling the open data initiative laid out in the Executive Order.

EO 1-12 directly led to the publishing of various governance documents articulating the city’s position on data collection and use as well as recommendations for how departments can share data either with each other or with the public. For example, as a result of EO 1-12, the City of Philadelphia published an Open Government Plan (GitHub 2013), which included themes of transparency, public participation, and collaboration.

The CIO and the CDO also published the Open Data Guidebook for city agencies. It describes best practices for preparing and sharing data across city departments and with the general public. The guidebook includes requirements for data structure to be compatible with the city’s metadata catalog, which is a repository for descriptive information concerning published datasets. The guidebook also supplies a methodology and reasoning for why publishing data is helpful for a city government:

By releasing open data, city departments may help to stimulate new and innovative ideas from our local technology community. There is great potential for open data to act as the fuel for new solutions and even new businesses that can address common problems or challenges facing those that live in, work in or travel to the City of Philadelphia.

(Headd 2016, 2, 3)

EO 1-12 also led to collaboration with OpenDataPhilly, which is a private initiative managed by software firm Azavea. OpenDataPhilly is an online portal where people can request or publish datasets. The Open Data Guidebook specifies OpenDataPhilly as a place for city data to be published, after release by the CDO.

The Data Services Team within OIT provides a citywide data inventory online that describes every dataset that exists within city government and provides a mechanism for citizens to provide comments on whether the dataset should be released.

Not all datasets are released. Those that are released comply with standards set out in the Open Data Guidebook, which include anonymizing data, conducting a review, adding descriptive metadata, and ensuring data accuracy. As shown in the figures from the city’s metadata catalog website, many have been released on a range of different subjects (Figure 5.1).

Figure 5.1. City of Philadelphia Metadata Catalog website

EO 12-11 and EO 1-12 stayed as the guiding force of Smart City initiatives in Philadelphia until February 4, 2019, when Mayor Kenney signed EO 2-19, The SmartCityPHL Initiative. That order formally established the SmartCityPHL initiative under the auspices of OIT, subject to the guidance of an advisory committee whose goal is to “guide and support the implementation of the key actions outlined in the SmartCityPHL Roadmap” (Kenney 2019, 2). OIT is responsible for maintaining the city’s open data⁹ programs and managing the SmartCityPHL initiative.

Pragmatism Reflected in Procurement and Departmental Operations

Apart from the agenda and actions of the Mayor’s Office, various city departments procure and deploy smart tech as needed in their day-to-day operations. The types of technology run the gamut, but generally include basic ICTs. Many departments have their own IT experts and make independent planning, procurement, and deployment decisions. We have not canvassed all departments and their activities,¹⁰ but many interviewees emphasized how, in the 2010–2015 timeframe, different city departments approached data and technology independently, in a piecemeal, siloed, and trial-and-error manner. The primary considerations were pragmatic, focused on existing needs, available budget, and compliance with general procurement rules.

The procurement process for the City of Philadelphia is outlined in Philadelphia Code § 17-100. These procurement rules concretely define how bidders submit proposals to the City of Philadelphia to obtain contracts for work with the city. As the city has increased procurement of smart technology, it has adapted procurement rules to ensure that technology-based projects meet standards set by the various Executive Orders discussed earlier. For example, the city requires that bidders meet data standards that comply with the city’s Application Programming Interface (API) standards, the ability to integrate data into the city’s data store, and the ability to provide the data to the city in a non proprietary format. The city also maintains licensing terms and metadata requirements for publishing and maintaining data for the city’s use or for release to the public, which complies with the OpenDataPhilly project standards. According to one interviewee, with respect to data, “the default in city contracts is that the city owns it. And a sort of policy default is that whatever we can eventually make public we do” (Hecht 2021a). Generally, if there is concern or uncertainty over whether a certain field in a dataset can be made public, the law department, which has a data privacy review board, is consulted (Carolan 2021). Some datasets have been withheld from the public to prevent reidentification.

One example of departmental independence with respect to smart technology is the police department’s use of facial recognition technology. Since 2012 (Lipp 2015), the department has used JNET facial recognition software, which relies on a database of photos pulled from specific, official sources (such as drivers’ licenses).¹¹ Without any public oversight, the police department had run its own trials of the controversial facial recognition software, Clearview AI, which draws photos from a wider range of sources, including surveillance and security videos, social media sites, and the statewide criminal database. In March 2020, the Philadelphia City Council passed a resolution calling for the Philadelphia Police Department as well as state and federal law enforcement officials to “establish clear boundaries and issue transparent policies regarding the use of facial recognition technology to ensure that this technology does not lead to racial biases in policing practices and outcomes or infringe on individuals’ civil liberties” (Jones Jr 2020, 2). While nonbinding, the City Council resolution reflects public concerns about the exacerbation of existing biases in law enforcement practices by using facial recognition software and recent studies showing the disparity in the accuracy of facial recognition technology when used on women and people of color (Buolamwini and Tinnit 2018: Grother, Ngan, and Hanaoka 2019; Grother, Quinn, and Phillips 2011).

Smart City/Tech Planning and Governance Dilemmas

Our study revealed three major dilemmas in Philadelphia’s approach to smart tech planning and governance in the 2010–15 timeframe.

First, community members began to recognize and reject smart city/tech rhetoric plagued by hype, unrealistic expectations and promises, and a failure to be grounded in realities of Philadelphia communities.

Second, and related to the first, there was a disconnect between the smart tech planners and users (mostly government actors but also vendors and consultants, such as IBM in the DOR story) and smart tech beneficiaries, including residents, businesses, and visitors. As one interviewee put it, to cut “through the hype … you need to know the people who are actually going to have to use that technology in city government and the people who are going to be most impacted by that kind of change … engaging them in the conversation, understanding what their current condition is, what they’ve tried in the past, and then also what they would like to address moving forward.”

Third, while the independent, pragmatic approach taken by many city departments was understandable and laudable, it also created redundancies and inefficiencies. Interviewees described departments as “siloed” and emphasized the need for better interdepartmental communication and coordination. One interviewee suggested that an obstacle to better coordination was simply political, as different administrations have different agendas. A similar observation was made regarding political differences across departments. Finally, interviewees suggested that “red tape” and bureaucracy impeded smart tech deployment.

Awareness of these three dilemmas began to surface and manifest demand for a new approach to smart tech planning and governance, which is reflected in the SmartCityPHL Roadmap.

Smart City Planning and Governance: 2016–2021

By 2016, the aspirational smart city promoted by Mayor Nutter, IBM, and many others in 2011 seemed to have faded and been replaced with something quite different. Expectations and imaginations changed with experience. Pragmatism in the day-to-day operations of city government coupled with lessons in what smart tech and data could actually do (and not do) tempered exuberant optimism and hyped rhetoric. The DOR story was just one factor, among many. The shift in outlook and approach emerged gradually, beginning around 2014. While this observation surfaced in various interviews, we highlight the narrative of Ellen Hwang, who led the drafting process for the SmartCityPHL Roadmap and became the first Smart City director with OIT. In speaking with us, Ms. Hwang (2021) recalled her first job for the City of Philadelphia as part of the innovation management team in OIT:

[I was] tasked to think about process, how folks within the city of Philadelphia, [were] thinking about how they approach problem solving and how can they arrive at different solutions that perhaps they would not arrive at. [I was] assigned a lot of work around procurement reform, which [is] really how I ended up entering the Smart City [field]: what are we buying, what are we getting services for, who are the companies that keep wanting to talk to the city of Philadelphia, what are they pitching to us, how do we wrap our heads around all this new technology … and what’s our criteria for evaluating that?

Ms. Hwang (2021) explained a particularly influential experience (which another interviewee also mentioned). OIT had used the city’s “Small Contracts, Big Ideas” website to post Requests for Information (RFIs) as a “a good way for us to communicate things that government wants to learn about from folks who want to engage in procurement with the city.” One RFI concerned leased towers on several building sites that the city could be using more productively. Specifically, “thinking about … smart technology, … we cast a huge wide net, kept it super vague, and that RFI process, produced … over 200 responses.” Ms. Hwang (2021) then emphasized:

that’s when it started, this dialogue around … the process of figuring out how to consume all [the] responses that came in and engage a wide stakeholdership within city government, including the streets department, transportation, infrastructure systems, IT, a chief administrative office, and a few other departments … everyone works together in the city in some ways, and in other ways, totally not, and certainly in reviewing RFI and RFPs, … it’s [typically] a bit more siloed.¹² …

And so this was a kind of an experiment to see when we adopt technology is there a better process for reviewing? And if there is, what are the criteria that we’re looking for to evaluate these things? And so we had to develop essentially an Excel spreadsheet that kind of mapped out all the responses we got, here’s how they relate to city government, here’s who might be most interested in what solutions, but then how do we have dialogue on it.

Ms. Hwang and her team convened interdepartmental meetings to “review these opportunities and to provide a strategic lens at seeing is there actually something bigger that we weren’t thinking about when we first set out to think about these tower leases?” She explains that mindset: “initially it was, how do we maximize assets that we have, tech assets that we have as a city for other things, and it ended up becoming what it is today … [the SmartCity PHL] initiative and having more cross-departmental dialogue around how do we actually adopt technology, and in a way that actually is meaningful and is actually going to improve city services.” During the conversation, she reiterated and emphasized the word actually, drawing a stark contrast with speculation and hype about smart tech. Yet the message was not pessimistic. Rather, as we discuss below, it resonated with the incremental, pragmatic, problem-solving approach to smart tech seen in the SmartCityPHL Roadmap.

In addition to improving interdepartmental coordination and communication, Ms. Hwang emphasized how the RFI-for-leased-towers experience demonstrated the need for the city to better leverage its resources, including limited budget, by being “more opportunistic about what is actually happening outside of city government.” This included building better relationships with industry and the community. She explained that the marketplace moved ahead of government and at the same time bombarded the government with proposals. “There was a lot of confusion on how to even just manage the sheer [number] of companies that were coming to city government.” To be more opportunistic and deal better with vendors and proposals, the community needed shared “terminology and education” about smart tech, and this required engagement and relationship-building – “everything that feeds into a good governance model.”

“From the beginning in 2016, the city approached the challenge strategically. Rather than tackle individual projects piecemeal, as so many cities have done, Philadelphia’s Office of Innovation and Technology (OIT) decided to create a roadmap that would guide and ensure long-term coordination of its wide-ranging projects” (Knowledge at Wharton 2018). Emily Yates, the current Smart City director for Philadelphia, described the roadmap as “a more organized approach to how we operate as a smart city and how we want to grow as a smart city.”

This shift to a strategic, holistic, city-wide plan required an assessment of what was already being done. OIT identified a variety of different projects, often siloed from each other. Figure 5.2, from the SmartCityPHL Roadmap, resulted from a thorough inventory of the city’s many existing smart tech assets and initiatives.

Figure 5.2. City of Philadelphia SmartCityPHL Roadmap (p. 5), Survey of Existing Assets and Initiatives

Notably, many of these assets/initiatives constitute meso-level action arenas for which further GKC-based case study research would be useful. We discuss DataBridge in the next subsection and in our discussion of the meso-level action arena concerning Vacant Property Management.

To create a roadmap, the city established the SmartCityPHL initiative in early 2017, designated OIT as the lead department, and formed a working group including various city offices and departments. At the outset, the roadmap identifies four guiding principles – being locally inspired, innovative, equitable, and collaborative – and explains the methodology used to develop the roadmap – including an assessment of existing assets and initiatives, focus group interviews, identification of gaps and opportunities, working group brainstorming sessions, benchmarking against peer cities, and engagement with external stakeholders. The principles reflect a different set of community goals and objectives than had animated the smart tech vision in prior years.

The roadmap integrates smart city/tech planning and governance processes. It outlines three macro-level strategies: (1) building the policy foundation and governance infrastructure for meso-level projects and initiatives, (2) establishing consistent processes for engaging community members, and (3) developing sustainable funding mechanisms. We briefly describe the first two strategies, both because they relate most directly to the governance concerns of this case study and because they are developed in more detail in the roadmap; the discussion of funding is quite limited.

Smart City Foundations: Governance Structure, Policies, and Master Strategy

According to the SmartCityPHL Roadmap, “[a] strong governance structure is arguably the most important foundational element to smart city success” (City of Philadelphia 2019, 8). The roadmap establishes the following model: Executive leadership, which sets “vision and direction,” a Smart City director, who “collaborates and partners to inform and implement activities,” an Internal Working Group, which “collaborates and partners to inform and implement activities,” and an External Advisory Committee, which “provides advisory services, research, funding, solutions, and workforce capacity” (City of Philadelphia 2019, 8). In addition, according to Emily Yates (2021), the current Smart City director, “We are working to establish a task force, a third-party validation of sorts, so it will not be comprised of people in the Smart City advisory committee, it will be comprised of academics … to ensure that we are thinking of all community members.”

This structure, shown in Figure 5.3, aims to “drive … collaboration and standardization … [and to] solidify the City’s decision-making process, reporting structures, and roles and responsibilities of participating members.” While, at first glance, this new structure may seem to centralize decision-making and other governance powers within OIT, it does not go that far. Rather, it provides a central “hub” within city government for strategic development, coordination, communications, policy development and evaluation, and expertise regarding data, IT, and other related components of smart tech. Departments continue to have their own IT staff and make their own procurement, deployment, and other decisions regarding data and smart tech. The Smart City director and staff facilitate collaboration and function, at times, as consultants for other departments. During interviews, this role stood out for the city’s many different datasets (and also, to some extent, for network infrastructure, which we do not cover in this study).¹³

Figure 5.3. City of Philadelphia SmartCityPHL Roadmap (p. 8), Governance Structure

Hank Garie (2021), the city’s geographic information officer, explained that various programmatic or departmental datasets had been “messy” both for “historical” reasons and because IT professionals in different departments had been comfortable working in multiple databases without coordinating with one another.¹⁴ This resulted in a lack of consistency in data standards. Other interviewees discussed the example of the water, streets, and fire departments possessing separate databases: “It makes it really difficult to figure out how to deploy services … you have electricity, and then you have a cable company, and … some … are public companies, and some … are private companies, and they’re all dealing with the same property but nobody can talk about the same property.” (We discuss this example further in the meso-level action arena section.)

Efforts by the OIT CityGeo team to address these types of concerns resulted in the creation of DataBridge, an integrated data warehouse and platform for geospatial and select non-geospatial data. DataBridge enables data sharing and provides city-wide infrastructure for analytics and applications.¹⁵ OIT maintains the infrastructure, consisting of various pooled resources including technical know-how, software, and deployment managers. In alignment with the city’s general commitments to open data, transparency, and providing useful smart tech applications to the public, DataBridge aims to enable appropriate data flow to the city’s open data applications. Data flow enabled by DataBridge is shown in Figure 5.4.

Figure 5.4. City of Philadelphia DataBridge

As seen in the figure, DataBridge enables different communities to publish and access data, and it also serves as the backbone for department-specific applications. DataBridge thus serves the administration, city departments, vendors, and partners that use the service to publish data, and it also serves the broader community that uses applications, such as OpenDataPhilly, OpenMaps, and CityAtlas.

Over the past ten years, the geographic information system (GIS) management team mostly focused on sharing data for “mapping, analysis, and city services.” In recent years, this department has focused on developing a secure and reliable foundation to coordinate, organize, and share city data internally and with the public. One interviewee suggested that the recent shift in the dialogue surrounding smart technology and data over the past two years has led departments to be “less skittish” about releasing data; it has become a “habit” for departments to publish their data. The interviewee explained that growth in literacy surrounding data publishing and the existence of mutual trust among stakeholders are catalysts in this culture change.

Coordination among stakeholders is critical to successful data sharing. For example, Kistine Carolan (2021) of OIT created a spreadsheet of all stakeholders to be informed and “kept in the loop” prior to the publication of any datasets. “[W]e’ve got a spreadsheet [of] all the stakeholders. And [it indicates] here’s the place in the process where we need to plug these people in, so that we make sure that when that data set hits the streets nobody’s caught by surprise.” At times, OIT may resolve conflicts among stakeholders. Hank Garie (2021) described a disagreement among the police department, the Mayor’s Office, and the press office about whether to share/publish crime data.

At the end of the day, the data out there is open data, and it’s been well received, and those people who had some concerns were able to back off and say “Okay for the public good, we’ll put out the data.” So it was very much a negotiated solution, but everybody who needed to be at the table had an opportunity to weigh in and express their concerns.

The regularly updated crime incident dataset is hosted on OpenDataPhilly alongside several visualizations for viewing and understanding the dataset. The dataset contains crime data from 2006 through to the present; each reported crime is categorized along with the block number where the incident occurred.

The SmartCityPHL Roadmap also recognizes that privacy and security policies are fundamental. The city has had privacy and security policies in place, as well as data-sharing agreements among departments, and the roadmap states high-level commitments to continue revising and updating those policies in light of changing circumstances and to “better understand the concerns of community members and privacy advocates when initiating smart city projects” (City of Philadelphia 2019, 9).

In addition, the roadmap calls for the development of a “formal master data strategy,” which, among other things, would include creating a formal inventory; establishing governance standards and technology specifications, and requirements for procurement, upgrades, and vendors; and workforce training. The master strategy would be guided by the following questions:

• What are we trying to understand?

• How will we manage sensor data?

• Who owns and manages the data?

• How will we secure the data?

• How will we analyze and operationalize the data?

Throughout our interviews, we heard that OIT has been and still is working on these policies and the master data strategy. Some interviewees noted that the pandemic had caused a shift in attention and priority and, as a result, progress on these issues had been delayed. (We do not delve further but note that this is another action arena ripe for further GKC-focused study.)

Community Challenges and Engagement

Beyond structure, policies, and strategy, the roadmap grounds the city’s approach to smart technology in pragmatism, which had been present and rising in prominence in prior years (as previously discussed). According to the roadmap, “it is important that any smart city project the City pursues is grounded in a challenge or problem that aligns with its broader mission and purpose.” To ensure such grounding and alignment, the roadmap outlines, as seen in Figure 5.5, a process for selecting and evaluating “appropriate and feasible smart city projects.”

Figure 5.5. City of Philadelphia SmartCityPHL Roadmap (p. 16), decision-making process

The roadmap effectively outlines an applied version of comparative institutional analysis. “The first step is to establish a problem statement that conveys a challenge we are facing or trying to solve” (City of Philadelphia 2019, 17) and then “solution paths need to be identified” (City of Philadelphia 2019, 17). This step entails compiling a comprehensive list of ideas and potential solutions, drawing on internal and external sources. “Once we gather a long list of solutions, we will evaluate and prioritize them through criteria based on [a series of] questions” (City of Philadelphia 2019, 17). This approach highlights issues present in the city, and directly works to target initiatives toward solving the identified issues, seeking to achieve tangible improvements in the actual lives of community members.

Notably, the pragmatic process envisioned in the roadmap is a statement of strategy and does not constitute a binding rule and, to our knowledge, has not yet become a widely followed norm. Throughout the city, departments choosing to pursue smart tech projects need not follow these steps precisely. It remains to be seen whether/how the strategy and process become internalized.

The practical orientation to evaluating projects is further developed in the so-called Pitch + Pilot Program, usefully summarized in Figure 5.6 (from the roadmap).

Figure 5.6 City of Philadelphia SmartCityPHL Roadmap (p. 18), Pitch + Pilot

Pitch and Pilot, according to Emily Yates (2021, 13:40:48), is “[in] its very essence, a mechanism that was developed via the roadmap to create a more transparent way for the city to engage with the private sector to solve municipal challenges through tech and data.” It is a work in progress with a very limited budget, intended to be experimental and incremental. To date, the program has supported a handful of projects, summarized in Table 5.2.

Table 5.2. Pitch and Pilot programs

Program	Partnership	Purpose
Urban Mining Initiative	Metabolic (Netherlands-based company)	Piloting an urban mining tool “to predict the amount of waste from demolished buildings that could be reused in new construction and where construction demand exists to use those materials” (Hecht 2021b).
Sustainability and Waste Management Initiative	Retrievr (a New York-based startup company)	a. The aim of this partnership is to aid Philadelphia in reaching its “zero-waste” goal, which involves eliminating the use of conventional incinerators and landfills by 2035. b. Clothing and electronics collected by Retrievr are resold for reuse and recycling. c. There was a three-month pilot period, which began in May 2020 and ended in July 2020. Retrievr continues to offer collection services to Philadelphia residents.
Health Equity and Spatial Justice Initiative: Improving built environments	State of Place	a. State of Place’s software uses street view images already collected by the City to process over a hundred and fifty micro-scale built environment data points, from crosswalks to park benches” (Hecht 2021b). b. The pilot sought to use artificial intelligence to examine street view images and generate built environment data. c. Used to identify opportunities for urban design changes.
Street improvements	GoodRoads (North Carolina-based company)	a. 1,200-mile pilot project. b. Provided low-cost devices to be attached to city vehicles for collection of roadway images. The street department would then be able to receive more quickly and consistently notification of areas in need of repair/inspection.
(Impending project) To provide services that support meal distribution	TBD	City officials have announced a new challenge involving the creation of a platform to provide logistical support for meal distribution.

Finally, we note that the SmartCityPHL Roadmap places emphasis on engaging the community, through efforts such as forming subcommittees like the Citizens and Communities Subcommittee, which is “comprised of community-facing departments” and will be dedicated to “shaping and leading community engagement strategies and ensuring that solutions and projects will improve the lives of residents” (City of Philadelphia 2019, 8). In the second step of the governance process, identifying solution paths, the city will not only internally generate solutions, it will also “engage with a broader community to identify interesting and potentially impactful smart city solutions” (City of Philadelphia 2019, 16). Also among the factors utilized to evaluate and prioritize potential projects is community impact (City of Philadelphia 2019, 16). The criterion will ask whether “the program tangibly improves the experiences and outcomes of the community” (City of Philadelphia 2019, 16). Aspects of the roadmap such as these highlight the emphasis placed on community needs and involvement. Yet during our interviews, when we asked about how members of the broader community (beyond government) were actually involved in planning and decision-making processes, there was very little to report. Some interviewees acknowledged that there was less community engagement than promised or intended. The pandemic, we were told, made community outreach and engagement much more difficult. But, we were also told, it remains a pillar of the roadmap and the strategic plan, and it would be a priority going forward.¹⁶

City-Wide Use and Governance of Smart Tech in Managing Vacant Property (Meso-Level Action Arena)

We now turn to vacant property management as the relevant context for a meso-level action arena.¹⁷ How should Philadelphia address the causes and effects of wide-scale abandonment of thousands of residential and commercial properties within the city? How might data and smart technologies help? What are the opportunities and governance challenges? These difficult questions are hardly unique to Philadelphia. A similar set of concerns is playing out in rustbelt and eastern cities across America, including Detroit, Baltimore, Pittsburgh, Cleveland, Chicago, and Buffalo (Sisson 2018). The genesis of the vacant property crisis and how local leaders choose to address the problem may vary across cities. To situate our analysis in a broader background, we present a brief history and explain the general vacant property management problem. Then we describe how Philadelphia has approached the use and governance of supposedly smart technologies, including data, in managing vacant properties throughout the city. While each city is unique, the lessons from this Philadelphia case may be useful for other communities facing significant vacant property challenges.

Background

History and Context

Like many other American cities, Philadelphia experienced significant population growth in the nineteenth and early twentieth centuries (Biggest US Cities n.d.), bringing exponential growth in commercial and residential properties. As noted by Schilling and Hodgson (2013, 7), “Known as the ‘workshop of the world,’ Philadelphia was home to a growing manufacturing economy that spurred population growth, which in turn sparked private investment in the housing market and municipal services.” In the latter half of the twentieth century, concurrent phenomena brought about the vacant property crisis. First, technological evolution and globalization resulted in deindustrialization of urban neighborhoods nationwide. As a result, inner city factories closed, and many jobs were lost. For example, in Philadelphia, “In 1880, 52% of city jobs were in manufacturing, falling to 30% in 1950, 10% in 2000 and 3.5% today” (Center City District & Central Philadelphia Development Corporation 2017, 3).

A second factor driving the increase of vacant properties in American cities was the growth of suburbs. The interstate highway and improved public transit allowed workers whose jobs remained in the city to live in the suburbs and easily commute. Coupled with the “white flight” phenomenon in some cities, suburban growth may have led to abandonment of many inner-city residential units and a significant population loss. From 1960 to 2021 Philadelphia’s total white population fell by more than 62 percent or more than 900,000 residents and white persons changed from approximately 73 percent of the city’s population in 1960 to approximately 35 percent in 2021 (US Census Bureau 1966, 2021).

The migration of white residents from the city to surrounding suburbs drastically impacted northeast Philadelphia as the percentage of white residents fell from 92 percent in 1990 to 58.3 percent in 2010 (Pew Charitable Trusts 2011). Suburban growth, as well as other social and economic changes, led to significant overall population loss in Philadelphia. For example, at the height of its population in 1950, Philadelphia had approximately 2.071 million people (US Census Bureau 1950, 38-15). The population declined more than 23 percent to approximately 1.584 million by 2019 (US Census Bureau 2019). For comparison, the population of select Philadelphia suburban counties grew by 334 percent (Bucks County), 230 percent (Chester County), and 135 percent (Montgomery County) over the same period (US Census Bureau 1950, 38-15; US Census Bureau 2019).

A third factor in vacant land in some cities was the federal redevelopment policies of the 1950s to 1970s, especially the Urban Renewal Program. This program was enacted in 1949 to remove “blight” in American cities. Nationwide, “renewal funded proposals to raze and redevelop 363,637 acres of land – that’s roughly 568 square miles” and more than 300,000 people were relocated (University of Richmond 2021). As noted by the Lincoln Institute of Land Policy:

Vacant land in urban areas is not always the unintended result of financial drivers or city policies. The urban renewal policies of the 1950s, 60s and 70s aimed to improve the quality of the city environment. By condemning entire low-income, poorly maintained neighborhoods, and relocating the residents away from the urban core, often in isolated, poorly designed public housing, centrally located land was made available for redevelopment as high-end residential, commercial and retail property. This process of gentrification as a means of urban renewal was not always successful; some cities accomplished the razing of old structures but not the redevelopment, leaving large tracts of vacant land and displacing local residents to less desirable locations.

(Goldstein et al. 2001, 9)

By the end of 1965, Philadelphia had reserved $209 million in federal funding for urban renewal, second only to New York (Encyclopedia of Greater Philadelphia n.d.). Under the “Philadelphia Approach,” renewal emphasized “small scale, minimal displacement, citizen engagement, the preservation of neighborhood institutions, focus on urban design, and historic preservation” (Ryberg 2013, 194). Despite these efforts, the University of Richmond’s Digital Scholarship Lab estimates that urban renewal in Philadelphia displaced more than 13,000 families (University of Richmond 2021). Philadelphia conducted more than sixty Urban Renewal Projects, in areas such as Society Hill, Independence Mall, Nicetown, University City, Eastwick, and near Temple University (University of Richmond 2021).

Despite some efforts to do things differently in Philadelphia, approximately 40,000 vacant properties remain scattered throughout Philadelphia (City of Philadelphia 2020). Of these, 74 percent or approximately 30,000 properties are privately owned (City of Philadelphia 2020), with the balance taken into public ownership by the city through tax foreclosure, surplus city properties, and other mechanisms. In addition, 1.7 percent of properties in the city are “zombies” – properties where an owner abandons the home, but the lender has not undertaken foreclosure (Dickerson 2020). Regardless of occupancy status, private owners are required by city ordinance to maintain the property, including litter removal and securing the property (City of Philadelphia 2020, § PM-4). Vacant property in Philadelphia is not evenly spread across all city neighborhoods. Pearsall, Lucas, and Lenhardt (2013, 167) explain that:

The older industrial neighborhoods of north and south Philadelphia, as well as the once prosperous middle class streetcar suburbs of west Philadelphia, have disproportionately large quantities of both vacant lots and abandoned structures. Of all Philadelphia’s neighborhoods, Strawberry Mansion in North Philadelphia and Manuta in the west of the city are two of the most blighted in the city, characterized by large numbers of abandoned properties and vacant lots that have been left undeveloped and unimproved for many years.

Historically, seven Philadelphia city or quasi-public agencies have played a significant role in managing or selling the publicly owned or managed vacant properties. These include:

• The Philadelphia Housing Development Corporation (PHDC), a quasi-public entity funded by the city which manages the city’s land bank. The land bank was created by the City Council in 2013 under bill number 130156-A02 (City of Philadelphia 2013). The land bank conducts four key tasks: “Consolidate surplus City property … Acquire tax delinquent property at Sheriff’s sale … Dispose of surplus publicly-owned property ... Provide temporary access to property held by the Land Bank” (Philadelphia Land Bank 2019). The lots may be sold to individuals, developers, or nonprofit organizations (Philadelphia Housing Development Corporation 2022). Properties are sold at market rate, although discounts are available for properties that will be sold to nonprofits for public use or to neighbors for side yards (Philadelphia Land Bank 2020). These properties were acquired either from tax-delinquent sheriff’s sales or consolidated from existing properties already held by city agencies.

• Philadelphia Redevelopment Authority, now a part of PHDC.

• The city’s Department of Public Property, which manages and maintains properties where city staff work (City of Philadelphia Department of Public Property 2021). PHDC now serves as the operational arm for DPP vacant property sales.

• The city’s Vacant Property Review Committee (VPRC), a board comprised of fourteen people with a chairperson appointed by the city council president. In recent years, VPRC was accused of mismanagement of assets under its control, including “political meddling” in disposition of properties (Briggs 2019). In 2019, there was City Council legislation to fold the work of VPRC into the land bank (D’Onofrio 2019).

• The Philadelphia Industrial Development Corporation (PIDC), which sells and leases industrial and commercial properties (City of Philadelphia 2 2021).

• The Philadelphia County Sheriff, which hosts public auctions of properties taken due to foreclosure or tax delinquency (City of Philadelphia, Office of the Sheriff 2021).

• Philadelphia Housing Authority (PHA), which owns and manages affordable housing; with federal approval, it can sell homes and lots it owns (Philadelphia Housing Authority 2009).

The Department of Records,¹⁸ the Department of Licenses and Inspections,¹⁹ the Department of Planning and Development,²⁰ the Department of Revenue,²¹ and the Office of Property Assessment²² also have roles in addressing the issues created by vacant properties. Furthermore, the Philadelphia Fire Department, the Police Department, the Water Department, and the local electric utility PECO each need information about vacant properties to provide public services and undertake their respective responsibilities.

Social Problems Caused by Vacant Properties

There are three types of social harms that arise from the vacant property crisis in Philadelphia (and elsewhere). First, there are effects on neighborhoods and residents, including:

• Crime: There is a relationship between crime hotspots in the city and areas with a significant level of vacant property (Philadelphia Land Bank 2015, 20). As described by Goldstein, Jensen, and Reiskin (2001, 2), vacant properties “provide convenient venues for criminal activity, such as drug trafficking and gangs.” Productively reusing these vacant properties can help to reduce neighborhood crime. For example, scholars at the University of Pennsylvania studied the effects of restoring blighted and vacant lots and among other results they found reductions in crime, gun violence and burglary (Branas et al. 2018, 2946).

• Safety: Community members – especially children and homeless persons – are often attracted to vacant properties, many of which have unsafe structures or other hazards. “Abandoned buildings attract the attention of neighborhood children, who may decide to use them as play areas, even though they are poorly maintained and may be unsafe” (Goldstein, Jensen, and Reiskin 2001, 2). In addition, “The poor condition of most abandoned buildings makes them fire hazards. In older neighborhoods with minimal space between buildings, fires can easily spread from one building to another. A fire in an abandoned building may very likely result in the destruction of occupied buildings, displacing residents and increasing neighborhood blight” (Goldstein, Jensen, and Reiskin 2001, 3).

• Trash: Vacant properties often become dump sites for trash and other debris (Loesch 2018). These trash-strewn sites not only attract vermin and are unappealing for neighborhood residents, but they are also costly for the city to maintain. “During my time at the City, we estimated that the city was spending almost $10 million a year cleaning up illegal dumping, oftentimes on vacant lots” (Esposito 2020).

Second, and related to the neighborhood issues, are impacts on the delivery of city services, including trash removal, policing, firefighting, and addressing water leaks on-site. Public service providers generally face an added degree of uncertainty in characterizing risks and providing services when the conditions of the property are unknown, causing administrative complexities and adding cost. “In weak markets characterized by rising levels of vacancy and foreclosures, tax revenue and property values fall and the cost of providing essential services like policing, fire protection, and code enforcement rise” (Philadelphia Land Bank 2015, 20).

Finally, vacant properties have significant economic impacts. Not surprisingly, vacant properties have a negative effect on the value of surrounding homes as well as perceptions of the neighborhood. “The average household loses over $8,000 in property value due to vacant property in Philadelphia” (Philadelphia Land Bank 2015, 18). As noted by Susan M. Wachter and Kevin C. Gillen (2006, 4) of the University of Pennsylvania, “Our findings indicate that adjacency to a neglected vacant lot subtracts 20% of value from a home relative to comparable homes farther away from the site.” In addition, abandoned or vacant property may also result in lost tax revenue for the city, which may impact the delivery of public services. According to a 2010 report by Econsult and the University of Pennsylvania for Philadelphia’s Redevelopment Authority, vacant property cost the city:

1. 1. “$3.6 billion in lost household wealth. Vacant parcels have a blighting effect on nearby properties, reducing values by 6.5 percent citywide …

2. 2. Over $20 million in city maintenance costs each year. Though the City controls only a fraction of the vacant parcels within the city, it has to bear significant costs to maintain all of them – waste clean‐up, pest control, police and fire – totaling over $20 million per year.

3. 3. At least $2 million in uncollected property taxes each year. 17,000 vacant parcels are tax delinquent, most by over a decade, owing a total of $70 million to the City and School District in back property taxes.” (Econsult Solutions 2010, v)

Where Vacant Property Management Meets Smart Technology: Meso-Level Action Arena

Vacant property management has always faced data and knowledge problems. Simply keeping track of the quantity and qualities of vacant properties can be daunting. However, such knowledge is essential to effective management (including sales) of properties and provision of public services. There also are significant challenges rooted in the distribution of knowledge and responsibilities concerning vacant properties. Over the past decade, Philadelphia has tried to tackle some of these obstacles by improving its organizational processes and procuring, developing, using, and sharing with the public data and smart tech. In this section, we describe those efforts and the roles that smart tech plays in vacant property management.

Stakeholders

Numerous stakeholders face knowledge problems. We identify three main categories. Local community organizations and residents have a vested interest in the acquisition and productive reuse of vacant properties in their neighborhoods. These organizations may be concerned about which vacant properties are available for purchase and about how, when, to whom, and for what purpose the properties will be sold. Smart technologies that manage, track, estimate value, and communicate knowledge about the sales process can benefit these community organizations and residents.

These tools would also be useful to private developers and lenders, who need this data to make informed investment decisions. The goals of these private entities might conflict with the neighborhood groups, but the same technology could aid both.

Numerous city departments need information about where vacant properties are located and the condition/status of those sites. Understanding the number, locations, and types of vacant properties is central to PHDC’s redevelopment mission. During our interview, Professor Allison Lassiter provided a few additional examples of the city’s knowledge-sharing needs. Before running into the building, for example, firefighters need to know whether it is believed to be occupied and what types of hazards may be present. When leaks occur, the city’s water department must understand whether the line serves a vacant structure. Smart technologies such as jointly accessible tracking databases, public reporting systems, and sensors could serve as tools to aid in the provision of these and other city services. The following sections describe how Philadelphia has deployed smart technology in aid of key stakeholders.

Knowledge Problems and Smart Tech Solutions

Given the significant impact of vacant properties and the needs of varied stakeholders, there are several knowledge questions that cities must answer. The following are representative:

• Location: Where are vacant properties located?

  • ◦ Are the properties clustered in specific neighborhoods?

  • ◦ What has been the impact of these vacant sites on the surrounding community?

• Ownership: Who has title to the vacant properties?

  • ◦ Are these owners in arrears on property taxes?

  • ◦ Which properties are owned by the city and which by private entities?

  • ◦ When and where should the city begin the tax foreclosure process?

  • ◦ Where and when should the city condemn and take the vacant property for repeated code violations?

• Status of the vacant site: Are vacant property owners maintaining the site, as required by Philadelphia law?

  • ◦ Are there crimes or safety hazards at the site?

  • ◦ What is the status of utilities, including water and electrical, at the property?

• Disposition: Which properties are for sale by the city?

  • ◦ What is the city’s plan for property reuse (commercial, multi-family residential, homeownership, side yard, community park, urban agriculture, etc.)?

  • ◦ Who and what are involved in the property disposition process?

  • ◦ How will upcoming property sales be communicated to the public, nonprofit community organizations, and developers?

There are many opportunities to use data, information and communications technologies, and smart technology to address these and related questions. In accordance with the macro-level strategy (discussed previously), the city has focused mostly on using the internet to provide usable open data as shared infrastructure for all stakeholders as well as mapping and visualization tools that leverage open datasets.

Smart tech deployment and governance in this action arena follows a familiar logic. The city has made a significant effort over the last several years to adopt technology policies that allow for more transparent government and enable open pipelines of data for everyone to use. Broadly speaking, the city sends data collected through various programs to DataBridge. Aggregated data is then published to a data repository, like the Philadelphia metadata catalog or a website like OpenDataPhilly. Once the data is published, it is available publicly for access and manipulation by anyone with an interest. The City of Philadelphia maintains a tool called Atlas for people to explore some of the published datasets.

The Vacant Properties Indicators Model (VPIM) dataset, owned and maintained by OIT, is an illustrative example of how data is published and utilized in the city. The dataset is hosted on OpenDataPhilly. Anyone can download it. The dataset is updated regularly by the city to ensure that the data present is the newest and most useful available. The city maintains two visualization applications that utilize the VPIM dataset: the Vacancy Viewer application and the Atlas application. Both are accessible either by direct link or through the OpenDataPhilly page for the VPIM dataset. On one hand, the Vacancy Viewer application is specifically tailored to the VPIM dataset. It serves to provide an easily navigable map-based visualization system for identifying and ranking vacant property according to the model created in the dataset. The Atlas application, on the other hand, serves a more general purpose. It helps visualize over fifty datasets. The Atlas application allows users to access information about properties across the city and allows users to learn about: property assessments, deeds, licenses and inspections, zoning, voting, and nearby 311 calls, crime incidents, zoning appeals, and vacant property. Atlas is an attempt by the city to unify visualization of geographically relevant datasets. The Atlas application contains a generalized visualization of the VPIM dataset to provide an entry point into viewing Philadelphia-centric data.

One of the stated goals for the DataBridge tool was to provide a streamlined methodology and process for publishing and viewing data. The Atlas application is an example of that streamlined process. However, as the Vacancy Viewer application shows, more specialized tools and visualizations can be created. One clear benefit of open data is innovation and creativity in the manipulation and viewing of the dataset. The City of Philadelphia has done a lot of work to create a platform and tools that can be used to observe and interact with the data they have published.

There are, in fact, many smart technology tools used to assess and manage vacant properties in Philadelphia. A sample of these tools are described in Table 5.3, sorted by the knowledge question each technology primarily addresses:

Table 5.3. Smart tools for vacant property management

Name	Agency	Address	Description
Vacant property location & ownership
Vacant Properties Indicators Model (VPIM)	Office of Innovation and Technology	www.arcgis.com/apps/webappviewer/index.html?id=64ac160773d04952bc17ad895cc00680	Mapping system used by agencies and public to locate vacant properties. VPIM aggregates Philadelphia’s various geographic and administrative data sources to identify indicators of potential vacant property or building. Allows for all departments to be more proactive in assessing, billing, and inspecting vacant properties.
Atlas	Office of Innovation and Technology	http://atlas.phila.gov	Master aggregator of city mapping sites. Compiles information about all city properties into one location, including ownership, history of inspections, permits, and licenses, zoning, property value, and 311 service requests. Users can see street and aerial view.
Property Map	Office of Property Assessment	https://property.phila.gov	Info on property ownership, sales history, value, permits, licenses, violations, and appeals. The site also includes physical characteristics such as lot size, year built, building condition, zoning, political district, school catchment, and police district. Properties can be assessed within a 250-foot radius.
Status of the vacant site
311 System	City of Philadelphia	www.phila.gov/departments/philly311/	Residents use system to report vacant lot issues and request city clean-up. City refers request to owner to clean up lot. If does not occur, city will address issues and bill owner (City of Philadelphia 2020).
Litter Index	Office of Innovation and Technology	www.arcgis.com/apps/View/index.html?appid=4856a523514c4c02ba0e28e6a0e8c42c	“A map-based survey conducted by city staff of the litter conditions on city streets, vacant lots, parks and recreation sites, riverways, transit stations, and other public spaces. Surveyors identify the types of litter they see and give a 1–-4 litter score, with 1 being the cleanest and 4 being the most littered. The city then creates an indexed map of litter conditions across Philadelphia using the data collected through the surveys” (City of Philadelphia Litter Index 2019).
Disposition
Property Search Map	PHDC	https://phdcphila.org/land/buy-land/property-search-map/	Map indicates available properties for sale from land bank. Allows developers and purchasers to consider how to assemble multiple sites for development.
PHDC Land Management	PHDC	https://phl.maps.arcgis.com/apps/webappviewer/index.html?id=2eb44decb9464cb79f2132d1c5883674	Map indicates number and type of available properties. Provides information on zoning, market value, and ownership status.
PHDC website	PHDC	https://phdcphila.org/land/buy-land/	Website summarizes potential uses of vacant property including side or rear yards, affordable housing, community gardens and other public uses, and commercial activities. Includes information on requirements and application/RFP process, as well as PHDC strategic plan and policies.
PIDC Available Properties	PIDC	www.pidcphila.com/real-estate/available-properties	Provides information about available commercial and industrial properties for both city and privately owned properties. Includes size, zoning, and types of available public incentives/subsidies.
Sheriff’s Office Property Search	Sheriff’s Office	https://phillysheriff.com/property-listing/	Website indicates location, status, and description of properties to be sold at Sheriff’s auction

SmartCity PHL Roadmap and Knowledge-Smart Tech Gaps

The SmartCity PHL Roadmap includes vacant property management as an area of interest. In fact, the Departments of Licenses and Inspections, Planning and Development, the Waste and Litter Cabinet, the Philadelphia Water Department, the Philadelphia Fire Department, PECO, and the Department of Public Property – all of which have a role in addressing Philadelphia’s vacant properties – are members of the working group supporting development and implementation of the SmartCity plan (City of Philadelphia 2019, 2). Interestingly, none of the other key public agency vacant property owners, including the Philadelphia Housing Authority, the Sheriff’s Office, or the Philadelphia Housing Development Corporation, are listed in the SmartPHL Roadmap as members of this group (City of Philadelphia 2019, 2).

The roadmap identifies existing smart technologies, including several that are related to vacant properties. These include the city’s Vacant Property Model, DataBridge, Atlas/MapBoard, and its Litter Index (City of Philadelphia Litter Index 2019, 5). According to the roadmap, the Vacant Properties Indicators Model “identifies potentially vacant properties across Philadelphia by combining city datasets, analyzing and scoring them for every property record in the city. This solution has increased data accuracy and operational efficiency across stakeholders that deal with vacancy challenges” (City of Philadelphia 2019, 11).

As the SmartCity PHL Roadmap has been implemented, however, using smart tech to address the vacant property crisis has not been as successful as one might have expected. Managing/selling vacant properties has not been a major area of focus for OIT or the SmartCity working group. For example, the city’s SmartCity coordinator Emily Yates indicated that while there had been a discussion about including vacant properties among the early Pitch and Pilot initiatives, it did not proceed (Yates 2021).

Philadelphia has made progress in making data publicly available and providing various mapping and visualization tools (see previous section). These steps are important and help address some of the knowledge problems that may stifle stakeholder participation and progress in managing vacant property in the city. Yet, as became clear in our interviews, there is only so much that data and these types of smart tech tools can do. On one hand, many knowledge problems remain. The datasets are incomplete. Some datasets are managed separately and not always easily integrated. Conditions change, sometimes much faster than datasets can be updated. On the other hand, and perhaps much more important, some knowledge problems may not be amenable to data-driven, smart tech solutions – at least, the types being deployed. For example, questions concerning city planning and strategic disposition of vacant properties are not answered by data or mapping tools.

This observation raises a broader concern that surfaced in some interviews. Vacant property management is incredibly complicated, in part because it is not always reducible to a data or computational problem; it is often highly political and involves stakeholders with various competing interests. In addition, as noted during our interview with Angel Rodriguez, Executive Director of Philadelphia’s land bank, there are inherent legal and managerial complexities in acquiring and selling real estate. These complexities include ensuring that all buyers of vacant properties are qualified to undertake the long-term financial and maintenance obligations (Rodriguez 2021). Data and smart tech can be helpful, but are no panacea. In the next section, we briefly highlight some of the broader governance challenges that arose during our study.

Governance Challenges Affecting Smart City Implementation

Managing the disposition of vacant properties involves many organizational hurdles. We identify three governance challenges raised by interviewees and publications that may hinder implementation and coordination of smart city technologies to address the vacant property crisis in Philadelphia. These challenges include:

• Political structure;

• Organizational responsibilities; and

• Community group and public engagement.

Politics

Some of Philadelphia’s knowledge-sharing challenges regarding vacant properties are founded upon political processes. According to the city’s charter, Philadelphia cannot convey or acquire land, except by legislation, which requires city council approval. As noted in a report by the Pew Charitable Trusts “For instance, Chapter 8-205 of the City Charter forbids the Department of Public Property – which owns a majority of the city’s vacant land – from selling or exchanging ‘any real estate belonging to the City or grant any license, easement, right of way or other interest over or in such real estate without specific authority from the Council so to do’” (Pew 2015, 3). These requirements apply not only to sales from city agencies but also to sales from the land bank. In addition, one interviewee emphasized the importance of Philadelphia’s practice under its Home Rule that all sales of city-owned property be approved by the individual city councilor for that geographic district (Green 2021). This practice is known as “councilmanic prerogative” (Pew 2015). Councilmanic prerogative can lead to administrative delays and create challenges in implementing a comprehensive redevelopment plan (Green 2021). Councilman Green suggested that the only way to address this gridlock is to amend the city’s Home Rule/Charter. Another interviewee further highlighted the challenges with centralizing the vacant property process under the land bank: “I don’t think the city council ever wanted it to be successful … at the end of the day city council wanted to control what property got disposed of and who got it. And that isn’t the way I would think it should work, because it gives individual council members veto power over what gets developed or not.”

Organizational Responsibilities

The fact that different city agencies are involved in vacant property management and disposition in Philadelphia makes it difficult to organize an effective, coherent approach. In the past, many of these agencies operated as relatively self-contained silos, with little cross-agency data sharing or collaboration. Emily Yates, Philadelphia’s Smart Cities director and Ellen Hwang, the city’s former director and now with the Knight Foundation, indicated in their interviews that one of the first steps in implementing the SmartPHL Roadmap overall was to convince city agency staff that centralized systems and knowledge sharing were worth the effort. Some agencies, such as the Fire and the Water departments have embraced these initiatives and regularly use the Vacant Property Indicators database. Others are less engaged with the initiatives, appear to remain somewhat siloed, and may rely upon their own, internal land-tracking systems and planning processes.

The city has undertaken significant efforts over the past decade to reform its organizational approach to vacant property management. These efforts include consolidating much of the vacant property process under PHDC by establishing the land bank, rolling the Redevelopment Authority into PHDC, and ending the VPRC. To enhance the coordination between city agencies involved in the management of vacant property, Angel Rodriguez (2021), Executive Director of the Philadelphia Land Bank and Senior Vice President in charge of land management, design, and construction for PHDC, indicated in his interview that memorandums of understanding (MOUs) have been a vital aspect of the process. Rodriguez (2021) stated that the PHDC has spent years attempting to reform interagency coordination: “We’ve spent a lot of years ironing that out. [During the] first couple of years, it required me to get a memorandum of understanding with PRA, the Landbank with PRA, PHDC has an MOU with the revenue department, with the school district and an MOU with the commissioner public property.” In addition, Schilling and Hodgson note successes in establishing the office now known as the Office of Property Assessment, which evaluates and shares data on property values; developing a formal city land disposition policy; coordinating meetings across agencies; and improving data systems related to Sheriff’s sales (Schilling and Hodgson 2013, 21).

Community Inclusion

Community groups have voiced concerns about the uses of the properties sold by the city, whether from the land bank or other sources. For example, Beth McConnell, policy director with the Philadelphia Association of Community Development Corporation, “expressed concerns that the original vision for the Land Bank to be financially self-sufficient – to use the revenue generated from the sale of properties to fund its operations – creates a pressure to sell at market rate to developers and is at odds with the interests of current residents of these neighborhoods” (Haas 2019). As described earlier, there are several smart technologies that provide easily accessible data and maps on vacant properties to Philadelphia residents and community groups. However, data sharing is not equivalent to community engagement and citizen participation, which imply a two-way discussion on the opportunities for redeveloping vacant properties. A review of the existing SmartPHL technologies indicates that relatively few of these tools directly relate to public engagement. In fact, a few of our interviewees indicated that involving community groups and residents in the overall smart city planning process – including as it relates to vacant property – is an area that requires additional attention. These interviewees indicated that due to the complex organization of Philadelphia’s city agencies and the need for interdepartmental coordination, these public stakeholders needed to be convinced and brought on board (Yates 2021; Hwang 2021). Then, community organizations could be more fully incorporated. These interviewees further indicated that the Covid-19 crisis has slowed these outreach efforts. It is important to note, however, that PHDC staff do regularly meet with and conduct training sessions for community groups.

The Future of Smart Technology and Vacant Properties in Philadelphia

Given constraints and the incredible complexity of the vacant property challenge, it is not surprising that smart city technology has yet to make a significant improvement in the disposition of vacant properties in Philadelphia. “The City owns more than 5,000 parcels of surplus vacant property and has disposed of less than 700 of them in the last five years” (Philadelphia Coalition for Affordable Communities 2021, 2; see also Haas 2019: “Steven Jones said it took him 12 years to acquire the side lot he’d been cleaning and gardening for decades”). Yet, according to PHDC, the city’s efforts to reuse vacant property have improved in recent years: “Strategic property acquisitions increased from 21 in FY17 to 312 in FY19. In FY20, 157 properties were acquired; acquisitions in FY 20 were cut short due to the COVID-19 Pandemic. Dispositions have increased as well, from 241 properties in FY18 to 305 in FY19 and 321 in FY20. Dispositions through FY20 have brought in excess of $3 million in revenue” (Philadelphia Housing Development Corporation 2021, 10).

The types of smart city technologies already deployed by the city, as well as others not yet implemented, offer Philadelphia the opportunity to coordinate, communicate, and improve its approach to selling and reusing vacant properties. These technologies can and do assist city staff, commercial organizations, and community residents to locate, manage, and dispose of vacant property and buildings. The technologies assist public agency staff to answer key questions about where, when, and how to deliver city services related to these lots. In addition, the city’s smart technologies help private corporations to identify opportunities for redevelopment, investing much-needed resources into the city. Perhaps most importantly, these systems assist residents to apply for and implement reuse plans resulting in social benefits such as community gardens, affordable housing, or side lots for neighboring owners. Without Philadelphia’s existing smart technology, each of these outcomes would have been difficult – if not impossible – to achieve.

Nevertheless, there remain significant governance challenges to overcome if the promise of smart technology is to be realized in addressing Philadelphia’s tens of thousands of vacant properties. The technology can and does improve information accuracy, enhance communication efforts, and support interagency service provision. However, the promise of these technologies is not yet fully realized in Philadelphia. No smart technology can independently overcome the political and organizational issues and the complex economic trends outlined earlier. This case study serves as an example of the usefulness of smart technology and a stark reminder that it alone cannot solve significant public policy issues. Rather, the implementation of smart technologies must be founded upon effective local efforts to break down city service barriers caused by entrenched political and administrative structures. In addition, equitable, comprehensive, and successful vacant property disposition requires enhanced engagement with residents and community groups. Smart technology can support Philadelphia’s ongoing efforts to address these constraints and put vacant properties back into productive use for its citizens.

Conclusion

Smart tech deployment and governance in Philadelphia is complex and evolving. The GKC framework provided a useful scaffold for our study. At the macro-level, we observed conflict between tech boosterism and practical, public administration concerned with using data and technology to engage the community and solve identifiable community problems. The SmartCityPHL Roadmap, which reflects the more pragmatic approach to smart tech deployment and governance, sets the current tone, but it remains to be seen how effective it will be (as the pandemic stalled efforts to implement it). At the meso-level, we identified a series of knowledge problems in the vacant property context for which data, mapping, and other smart tech tools might offer solutions. Yet we also observed additional governance challenges for smart tech deployment as well as more fundamental limitations on what smart tech can do to resolve the vacant property crisis.

We conclude by noting how this study has shown us the importance of studying multiple action arenas over time and of longitudinal work more generally. It was particularly useful to assess Philadelphia’s approach to smart technologies at both the macro- and the meso-levels. The macro-level assessment offers insights into how the city’s strategy and related technologies have evolved over time; the meso-level applies these concepts to a significant and ongoing policy problem faced by the city. This multi-level combination offers insights not only to scholars evaluating the impacts of smart city approaches but also to local practitioners seeking to use technology and information sharing to address public problems. We plan to continue with this work and invite others to do so as well.

6 The Kind of Solution a Smart City Is Knowledge Commons and Postindustrial Pittsburgh

Michael J. Madison

Introduction

Practice and writing about so-called smart cities often suffer from significant problems. This chapter aims to steer in a different and more productive direction.

First, the smart city, it is said, offers policy and practice challenges to those who would create the smart city in the twenty-first century (Green 2019; Luque-Ayala and Marvin 2020). The right view, instead, is to abandon the interest in creation and to hold to evolution, with “smart” systems affecting the character of cities in locally relevant ways rather than in the same ways in all places. Second, the smart city, it is said, “dematerializes” social, economic, and political relationships in cities, by abstracting human interactions in physical space, coding information into data, and using that data to unleash new potential for democracy (Goldsmith and Crawford 2014) or exploitation by elites (Morozov and Bria 2018). The right view, instead, is to see how the harms and benefits of information governance in smart cities is linked to physical infrastructures, both preexisting (buildings, roads, and open spaces, for example) and novel (wireless communications networks, for example). The right view sees city form and community participation patterns as descended from their pre-“smart” configurations, particularly in long-standing intersections between centralized control of urban planning and development, on the one hand, and grassroots, neighborhood-based, emergent patterns, on the other (Florida 2014; Glaeser 2012; Jacobs 1961).

Together, those corrections point to offering a portrait of smart city governance in historical, material, and social context that – to take the most optimistic view – enriches rather than limits conversations about the future roles of technology in cities. Smart cities are ripe for studies of multi-layered governance on a case-by-case basis, taking historical as well as technical, social, economic, and political contexts into account. Sweeping claims that condemn smart cities or that celebrate them are premature. Empirics matter. This chapter illustrates with a deep review of a mid-sized American city, one that both has experienced significant recent investments in smart technologies and also bears considerable scarring and rejuvenation in its recent “ordinary,” non-“smart” development: Pittsburgh, Pennsylvania, USA. The chapter organizes its review via the Governing Knowledge Commons (GKC) research framework, because smart technologies in urban contexts prioritize questions about institutional governance of knowledge and information. Cities are both problem and solution. What kind of problem is the smart city? What kind of solution is it? In that spirit, the chapter’s title borrows from the title of the concluding chapter in Jane Jacobs’ The Death and Life of Great American Cities (Jacobs 1961; see also Bettencourt 2013; Hochfelder 2020). Pittsburgh’s smart city experience is inescapably entwined with Pittsburgh’s evolving industrial and postindustrial urban character.

The next section provides a brief introduction to Pittsburgh itself, drawing specific attention to features of the city’s experience that I characterize as social dilemmas. These are the governance problems that are the starting points for knowledge commons research. A section on methods and key insights follows. Evidence takes up the next section; Pittsburgh is subjected to a deep review of its history as it relates to smart city practices, including data gathering and public administration and recent uses of ICTs. That leads to a section reviewing recent and contemporary smart city initiatives in Pittsburgh, both describing actors and motivators and listing them in tabular form. The chapter then sketches key implications and questions for further research. A brief conclusion uses the Pittsburgh case to ask about the future of the smart city, the future of the city, and the role of knowledge commons in understanding both.

The Case: Pittsburgh

Today, Pittsburgh is a mid-sized American city, and the “mid-sized” characterization assumes that the population of the city proper (only about 300,000) is linked to the population of the surrounding region (roughly 2 million more, in total). For much of the twentieth century, Pittsburgh was a larger place in both respects, and the Pittsburgh region was a world-leading industrial center. Pittsburgh produced roughly one-quarter of the world’s structural steel. In the early 1980s, for reasons that lie mostly beyond the scope of this chapter, that industry ended. As community and economy, a hollowed-out Pittsburgh staggered on, eventually grounding its economy on an evolving, fragile blend of professional services – university-based education and clinical healthcare, termed “eds and meds.” In its more recent pivot to high technology and an “innovation economy” as a development and governance focus, Pittsburgh has emerged as an urban center that relies as heavily as any other on knowledge-sharing practices and principles. Sometimes that reliance is explicit; more often, it is implicit. This chapter documents both.

Pittsburgh is arguably one of the great twentieth-century urban success stories, but in the twenty-first century, Pittsburgh is unexceptional. That makes it a good case for examining governance of smart city technology, because Pittsburgh is neither behind some imaginary urban technology curve nor ahead of it. Like many cities, it doesn’t aspire to be celebrated as a “smart city”; instead, it merely hopes to do well, even to thrive. Pittsburgh has steadily accumulated and deployed a broad range of technology systems as part of its public administration practice, publicizing its advances as often and as much as it might. The case study documents what might be referred to as “ordinary” or “normal” governance of smart city technology and governance via smart city technology.

Research Methods

The chapter offers a broad historical take on ICTs and smart technologies in Pittsburgh. It also dives more deeply into some specific examples. Its research and presentation are pluralistic in tone, style, and method.

The research was informed by the fact that I have lived and worked professionally in Pittsburgh for close to twenty-five years. During most of that time I have participated actively in public dialogues about the region’s technology-based economy and public policies. In selecting documents to review and in arranging and conducting interviews, I contributed my own knowledge of key historical and contemporary events, figures, and practices. Every effort was made to achieve descriptive (i.e., historical and journalistic) completeness. (Historical data from prior to the twentieth century was obtained from key secondary sources documenting Pittsburgh’s history.) In part because much of the relevant source material was published or produced while research for this chapter was ongoing, inevitably those efforts fell short.

In addition to my own knowledge of Pittsburgh practice, sources and methods consisted of:

1. 1. Analysis of public-facing documents and other materials relating to development or uses of smart systems, civic technology, data-informed governance, and algorithms and/or data analytics in and around the City of Pittsburgh. That includes Allegheny County, of which Pittsburgh is a part. Those documents included reports, press releases, and summaries of public events and meetings and were published on public websites by public authorities, private actors working in concert or coordination with public authorities, and online news media. I selected, collected, and reviewed documents and materials for both critical developments and shared themes based on my preexisting knowledge of the practices of technology-focused economic development communities in Pittsburgh. In one instance of contemporary practice (Pittsburgh’s 2020 contract to host its municipal data with Google Cloud), I obtained documents both via a formal Right to Know request under Pennsylvania law and via the City of Pittsburgh’s public-facing procurement website, Beacon.

2. 2. Semi-structured interviews conducted with participants in smart cities strategies and deployments in the City of Pittsburgh and Allegheny County. Some work in the public sector, some in the private sector, some in higher education, some in nonprofit organizations, and some in philanthropy. I completed nineteen interviews in all. Like the public materials, I selected interviewees based on my prior knowledge of the systems and structures that characterize the technology and economic development communities in Pittsburgh. They were chosen in part for their diversity of perspective and in part for their commonality of interest. The interviewees all have or have had active roles in developing Pittsburgh as a smart city. My direct connections to the subject matter of this chapter are disclosed below.

Pittsburgh’s Twenty-First-Century Social Dilemmas

Much of the following narrative focuses on smart city practices in Pittsburgh in a specific time period – from 2014 to the end of 2021 – and in a specific environment, the City of Pittsburgh proper. That focus is based on the fact that much of Pittsburgh’s contemporary smart city identity is grounded in the vision and practice of Mayor of Pittsburgh Bill Peduto, who took office in early 2014 and who exited, after two terms, at the end of 2021. This section lays the foundation for analysis of smart city governance by highlighting the social dilemmas, both conceptual and pragmatic, that confronted the incoming mayor in early 2014. The GKC framework calls for inventorying social dilemmas but does not require that this step be the first. In this case, it seems wise to begin with social dilemmas. With this inventory in hand, later sections explore relevant resources, action arenas, and smart city strategies, including the origins of those dilemmas; smart city practices and solutions that came before Mayor Peduto’s tenure, and the contributions of other actors and organizations both before and during his service.

By “social dilemma,” I mean a collective action or coordination problem, a possible conflict between the ends of individual behavior (individual welfare) and the performance of a group of people, acting as a social system (social welfare). The smart city context offers two broad types of social dilemma. The first consists of dilemmas created by the social, cultural, and economic conditions facing the city as a whole. Some of those involve knowledge and information; some do not. These are dilemmas to which smart city practices are believed to be solutions, wholly or partly, so that information governance is a means to the broader ends of urbanism. The second consists of dilemmas created by smart city practices themselves, so that the benefits and burdens of knowledge and data sharing require further additional layers of information governance.

Both kinds of dilemmas are summarized here. This section includes both a broad, macro view of the challenges that confronted Pittsburgh during Mayor Peduto’s tenure and also mid-level (meso) and micro views of dilemmas specifically connected to the smart city. They are described in the present tense, because they continue to characterize the city.

Not all of these dilemmas directly implicated smart city practices, and not all of the smart city practices deployed in Pittsburgh were effective in dealing with these or other problems. But these were the background conditions that described Pittsburgh largely in advance of its significant investments in smart city technology.

Postindustrial Renewal and Economic Development

Pittsburgh’s first key dilemma consists of how to modernize an old, industrial city, with old material infrastructures; a declining population; an irregular geography; social and political infrastructures anchored in old institutions; many small neighborhoods disconnected from political power; formal fragmentation of government authority; and little reliance on modern data-focused systems. That dilemma includes day-to-day questions involving city living and working for residents and larger-scale questions involving how to grow and diversify the region’s economy, which is recovering from its former dependence on large-scale industrial manufacturing (Andes et al. 2017; Madison 2012). Pittsburgh was an industrial city and region almost without peer. Today, Pittsburgh is unambiguously a postindustrial city and region. But the meaning and practice of its postindustrial status is in the process of being built – politically, economically, socially, and technologically. Economic renewal efforts still dominate the region’s political and cultural conversations roughly forty years after Pittsburgh’s steel industry collapsed.

The durability of the need and the difficulty of finding solutions testify to the depths to which Pittsburgh’s older industrial core shaped the region in every respect. It also testifies to the difficulty of marrying the legacy of that core to twenty-first-century technologies and governance. As Mayor Bill Peduto has said, smart city developments in Pittsburgh are linked closely to Pittsburgh’s emerging postindustrial identity, and the success of the new strategies depends on building on that core, not distinguishing “new” Pittsburgh from “old” Pittsburgh (Peduto 2015).

Public Administration

A second key dilemma involves the role of governance itself. Pittsburgh has experienced a conversion, from ideas of good governance as a means to the end of shaping Pittsburgh to good governance as an end in itself. The former perspective is highlighted by the public–private partnership embodied in the original, mid-twentieth-century Allegheny Conference for Community Development, described in greater detail later. The latter is highlighted by the idea of data-driven public decision-making as a modern value, embodied in particular in the contemporary Allegheny County Data Warehouse.

Not only have the aims of good governance and data-based decision-making changed, but as with all purported ideological shifts, practice may not match rhetoric, exposing social dilemmas within social dilemmas. After 2014, the City of Pittsburgh’s Department of Permits, Licensing, and Inspections was provided with digital technology for the first time with respect to many of its operations, both internal and public-facing. Snowplow operators and road repair crews were provided with tablet computers. Upgrades in the quality of service did not automatically follow. In part, legacy practices were simply difficult to dislodge, because incumbent staff members were comfortable with existing practices and were challenged by technology-based changes. In part, the material cost of technology outstripped the vision. The City of Pittsburgh circulated a call for proposals for smart street lights in 2018 relative to the city’s 40,000 street fixtures. It was imagined that the lights could be used for a mesh network of public Wi-Fi, would integrate with smart traffic control technology, and would monitor local air quality. The project was abandoned when city administrators realized that the effort would require installing thousands of miles of new network cables. Some obstacles are bureaucratic or logistical. Pooling data of different types and from different sources in a fragmented system presents considerable bureaucratic, labor, and technical challenges as data are generated to meet the details of different technical specifications.

Historically Grounded Inequities

A third central dilemma concerns the lack of alignment between Pittsburgh’s smart city goals and strategies with both community interests and research objectives at Pittsburgh’s key partners in nearby universities. As to the community, the problems that the City of Pittsburgh has tried to solve with smart city technology are not necessarily the most significant community-based problems that need to be addressed. As to research alignment, the priorities of Metro21: Smart Cities Institute at Carnegie Mellon University (CMU), which coordinates much of the relationship between CMU researchers and the City of Pittsburgh, are heavily influenced by partnerships between the institute and private industry.

Like many American cities, Pittsburgh suffers from profound inequities across different city neighborhoods and between the City of Pittsburgh and communities nearby, in Allegheny County and beyond, in the delivery of and access to basic amenities of urban living: public transit, education, clinical health and public health, clean air, clean water, safety and security, and economic opportunities. Smart city strategies were undertaken in part to begin to address those problems, by expanding the populations of citizens who were engaged in governance and community-level decision-making. Again, social dilemmas emerged within social dilemmas; historically excluded communities were skeptical of government solutions anchored in contemporary ICTs. In accessing government services, for example, people preferred to interact with human beings rather than with machines.

Polycentricity

Pittsburgh’s experience seems to teach the opposite of an important line of political science research that promotes polycentric order as an optimal governance strategy, if it aligns governance resources closely with relevant communities (Black 2008; Ostrom 2010). In Pittsburgh, smart city strategies both respond to and are frustrated by the region’s host of fragmented and decentralized formal organizations and institutions. The region is rife with overlapping and intersecting jurisdictions, funding powers and responsibilities, and areas of cultural and persuasive authority.

This polycentric disorder is evident in Pittsburgh in at least two respects. Schematically, and recognizing that these two phenomena overlap considerably in practice, one is effectively horizontal and involves coordination among political, economic, and social or cultural leadership in different organizations. Two is effectively vertical and involves coordination between political, economic, and social or cultural leadership, on the one hand, and local communities and neighborhoods comprising the actual residents of the city, on the other. Governance mechanisms that address the former set of coordination challenges are comparatively numerous, well-structured, and well-documented. Governance mechanisms that address the latter set of coordination challenges are comparatively fewer in number and more difficult to detect and to study, particularly once one moves beyond formal systems of democratic participation, i.e., regular elections of public officials.

Political-Economic Hierarchy

Because Pittsburgh as a region is characterized by extreme formal fragmentation of political authority, overcoming obstacles and achieving coordination and cooperation among political organizations with respect to smart city practices is highly context-specific and often incomplete. Relevant mechanisms blend numerous formal and informal practices. In some smart city contexts, governance dilemmas focus on the privatization of public functions. That pattern is less pronounced in Pittsburgh. The relevant social dilemma focuses less on the role of private technology companies in dictating public policy and more on the ways in which public problems are solved by informal alliances of public, private, nonprofit, and philanthropic actors.

Some of the obstacles are budgetary. Until Mayor Peduto was inaugurated in 2014, the City of Pittsburgh Bureau of Police lacked any data analysts. Staffing has increased, modestly. Allegheny County, with greater financial resources and a significant track record in developing data analytics capabilities – funded initially by Pittsburgh philanthropy – provides voluntary data-related services and public-facing violent crime statistics dashboards for the City of Pittsburgh.

Some of the obstacles are jurisdictional and organizational. While Pittsburgh’s Western Pennsylvania Regional Data Center (WPRDC) is designated by both the City of Pittsburgh and Allegheny County as their official open data repository, the WPRDC has declined to accept and host certain datasets produced by the Allegheny County Data Warehouse, citing concerns that the Allegheny County data is not deidentified to the degree that the WPRDC and its other partners deem necessary. In 2021, the City of Pittsburgh launched a “Mobility as a Service” mobile application that integrates service data from the Port Authority of Allegheny County (an independent county-level entity that manages public transit services throughout the county, including the City of Pittsburgh) and private transit providers (technology companies offering ride-on-demand and carpooling services) with street-side access points and information hubs managed by the city.

Smart city strategies in these examples involve combinations of funding and relationship brokering that rely on third parties Neither the WPRDC nor the Allegheny County Data Warehouse would exist in their current forms today without substantial financial underwriting from Pittsburgh’s large philanthropic community. Pittsburgh’s Mobility as a Service initiative is funded by the Richard King Mellon Foundation. Many other smart city systems in Pittsburgh likewise rely on coordination among actors in the public sector and partners in Pittsburgh’s university community. That coordination is often multisided and therefore fragile.

Socioeconomic Hierarchy

Despite’s Pittsburgh governance fragmentation, historical wealth and technological expertise in Pittsburgh are highly concentrated in the region’s largest philanthropies and in its most significant research universities. Beyond those entities, Pittsburgh experiences extreme concentrations of informal cultural authority among political and business elites. Pittsburgh has long struggled as a community to access and distribute material resources effectively and equitably. It has also struggled to ensure appropriate and consistent levels of community participation in conversations about resource development and use. Smart city systems in Pittsburgh have been closely linked to the interests, expertise, and good will of a relatively narrow band of experts in addition to policy and institutional design.

Both the Allegheny County Data Warehouse and the region’s open data repository, the WPRDC, are strongly associated with specific individuals (Erin Dalton in the case of the Data Warehouse and Robert Gradeck in the case of the WPRDC) as well as with their commitments to good data practices in public administration. Like the design and operation of those organizations, collaborations between the City of Pittsburgh under Mayor Peduto and the Metro21 institute at CMU rely heavily on interpersonal relationships.

Those informal relationships mitigate the impacts of organizational polycentricity in part, because Pittsburgh’s interpersonal professional culture has long been noted for its collegiality. Professional and personal networks tend to be small and dense. CMU is not only a source of research for Pittsburgh’s smart city ventures. CMU’s degree programs are also the sources of graduates who have gone on to work on smart city practices in Pittsburgh, relying in part and building in part on a shared alumni identity. The University of Pittsburgh supplies not only a home for the WPRDC but also training and degrees and an informal alumni matrix for a number of Pittsburgh’s smart city actors.

Nevertheless, smart city practice in Pittsburgh is composed almost entirely of elite leadership with strong ties to local business, to national and international technology companies, and to smart city experts elsewhere. That pattern echoes (though it does not precisely replicate) Pittsburgh’s longstanding tradition of elite-led planning and strategy in both economic and cultural life. In a departure from that pattern, at times a reputation for smart city success in Pittsburgh has attracted expert talent from outside the region.

Informal relationships take on even greater importance as individual actors move from organization to organization and from role to role. They move both within Pittsburgh’s smart city ecology and also outside of it, establishing links with national smart cities organizations. Movement expands the pool of shared interpersonal expert relationships and helps to cement bridges among different smart cities organizations. Movement also potentially dilutes that pool, creating a new social dilemma. Even without movement, this informal network constructs bridges for expertise to transfer from organization to organization and sector to sector. That bridging also connects Pittsburgh’s smart city public sector and research communities to technology development practices in Pittsburgh’s private sector, including startup and spinout companies and Pittsburgh extensions of global technology firms.

Power Asymmetries: Democratic and/or Community Participation

The role of the Pittsburgh community as a whole in defining and shaping technology-informed governance has been relatively small. Pittsburgh’s smart city strategies have mostly been developed and deployed by the region’s political, business, and research-based elites, with little provision for community governance. The relative absence of broader community engagement is unsurprising in historical terms. Since the end of Pittsburgh’s steel industry, community distrust of newer technologies and their economic role has been a barrier to Pittsburgh’s overall renewal (Sabel 1993). CMU has a legendary research program in computer science and robotics, but that success has never translated into broad community-friendly sensibility. With respect to technology-related policy, community-based interventions in recent years have been sporadic. The City of Pittsburgh adopted a Dark Sky Lighting ordinance in 2021 largely as a product of community-based research and activism. The city’s Open Data Ordinance of 2014 likewise emerged in part from community interest. Both community efforts arose from engaged community volunteers rather than from broad, publicly supported outreach efforts.

Critical examination of the use of algorithms in public decision-making in Pittsburgh has come from the Pitt Cyber public policy program at the University of Pittsburgh (Pitt), likewise an initiative volunteered by expert community members rather than solicited by public authorities. That project is one of the few in Pittsburgh to recognize the significant misalignment between smart city program objectives and harmful community spillovers. In 2020, in response to an inquiry from Pitt Cyber, the City of Pittsburgh confirmed that it had discontinued a pilot predictive policing program, developed in partnership with CMU, called the “Crime Hot Spot Project.” Pittsburgh’s City Council followed that action with legislation banning police use of facial recognition technology without Council approval, although the Pittsburgh Bureau of Police later acknowledged using facial recognition technology (Clearview AI) during Black Lives Matters demonstrations in 2021.

The relatively small number of community-based interventions of that sort suggest that data collection and distribution practices may perpetuate rather than remedy inequitable living conditions in Pittsburgh with respect to health, wealth, and security both for individuals and for the community as a whole. Allegheny County’s Allegheny Family Screening Tool (AFST), a data-based system for allocating family support services, has been criticized on that basis, though more of the criticism has come from outside of the Pittsburgh region than from inside it (Eubanks 2019). Smart city practices in Pittsburgh tend to consolidate rather than democratize control of Pittsburgh’s governance in the hands of political and business elites.

Even within Pittsburgh’s elite tier, the evolving strength of different voices is often difficult to discern. Elite leadership has gathered regularly in Pittsburgh to discuss strategies for economic development, though not specific to tackle smart technology issues. Decision-making, however, appears to be informal, consensus-based, and reliant on personal trust.

Given gaps between Pittsburgh’s smart city leadership and community participation, smart city technologies might be deployed to enhance community governance capabilities. Pittsburgh’s Burgh’s Eye View data dashboard project and other, similar data dashboards are nods in that direction. It is not certain that smart city designers are yet providing mechanisms for genuine community participation about smart technology governance in fair ways.

Instead, concerns about smart city technologies have been raised in the context of broader economic development decision-making rather than in the form of broad, direct objections to potentially harmful smart city practices. Incumbent Pittsburghers in some neighborhoods affected by technology-based economic development have protested the disruption of long-settled living patterns. In one well-known instance, the City of Pittsburgh backed the development of a technology-themed facility on a site adjacent to the Monongahela River that once housed a major steel mill, now called Hazelwood Green. Among the site’s amenities is a closed track for testing autonomous vehicles. Residents of the adjacent neighborhood, which lies between the Hazelwood neighborhood and the campuses of Pitt and CMU, strongly objected to the construction of a transit link that would connect the riverside site and the universities, the so-called Hazelwood Connector. They cited both the disruption of their neighborhood and the fact that the transit link would benefit only the technology elites. The dispute continues, sharpened by the fact that in late 2021, the University of Pittsburgh and the Richard King Mellon Foundation announced that the foundation was committing $100 million to help the university develop a biotechnology manufacturing facility at the site, provisionally named “BioForge.”

Information Asymmetries

Information asymmetries of various sorts mean that both acquiring too little data about Pittsburgh residents and too much data create opportunities for exploitation, corruption, and worse. I detected no evidence of bad faith or self-interested behavior in Pittsburgh’s smart city practices but abundant evidence of how Pittsburgh’s investments in partnerships with private high-technology companies and reliance on university-based research has skewed smart technology deployment so far. Residents may be unaware of political or historical conditions enabling data collection in certain domains and not enabling data collection in other domains. They may be led to believe that data collection and use is beneficial when in fact its impact is either neutral or possibly negative. Potentially harmful smart technology deployments may be difficult to detect and evaluate because robust mechanisms for transparency and oversight are not in place. That lack of salience or visibility not only limits residents’ ability to engage meaningfully in community-based or democratic oversight. It also limits their awareness of the extent to which smart city systems affect fellow residents and community members.

Information asymmetries may also reflect and generate dilemmas as to producing and sustaining social trust. As residents of a city anchored in neighborhoods and small communities of long standing, Pittsburghers traditionally exhibit high degrees of social trust in one another. That tradition does not always extend to trust in leadership. For historical reasons, some community members may be insufficiently trusting of relevant public and private leaders to engage in community-based governance of technology systems. Other community members may be too trusting of leadership and therefore may be uninterested in participating in collaborative governance efforts. Trust-based dilemmas of these sorts relate not only to trust in Pittsburgh’s leadership but also to trust (or lack thereof) among many Pittsburghers in technology itself, based on the region’s mixed history in building an economy on foundations anchored in twentieth-century industrial technology.

Managing Community Identity

A final social dilemma concerns the construction of community identity, both related to smart city technology use and in general. Community identity refers to how Pittsburgh and Pittsburghers see and represent themselves with respect to their history and their ambitions. The challenge is that not everyone in Pittsburgh participates in those conversations, let alone in the same way or on the same terms. Shared history and shared ambition are distributed unequally, as they almost always are in a given city. Yet there are important points of commonality. Building on that commonality is part and parcel of Pittsburgh’s smart technology practice. The City of Pittsburgh has tried to shape conversations about Pittsburghers’ community identity in the innovation economy, by trying to communicate to the broader public the effective and equitable public administration that can accompany public technology use. Beyond computing, smart city practices are linked to Pittsburgh’s efforts to reconstitute its public identity as an equitable and forward-looking “green” community in contrast to its older smoky self. Key actors blend advocacy and practice directed internally, to the Pittsburgh community itself, and persuasion directed externally, to political and economic development audiences outside of Pittsburgh. It is part of Pittsburgh’s smart city practice that Pittsburgh should see itself in smart, technology-based terms. It is also part of Pittsburgh’s smart city practice that others see Pittsburgh in those terms.

Shared city identity recapitulates additional social dilemmas. Both for historical and contemporary reasons, not all Pittsburghers experience or want to experience a shared “Pittsburgh” identity, whether related to technology use or otherwise. Promoting a collective, shared understanding of community identity may put at risk valuable ideas and behaviors as to spontaneity, serendipity, and personal development in both the experiences of residents and the behaviors of city planners, administrators, and public employees of all sorts. In contrast to cities such as New York and San Francisco that have long been celebrated for not only accepting but actively encouraging novelty and distinctiveness in human experience, Pittsburgh’s reputation lies at the opposite end of that spectrum. Generalizing, Pittsburgh is a place that encourages and sometimes even celebrates conformity and social stability (Madison 2012). There are difficult but important balances to be struck between standardized, scripted, and even brittle behaviors in all elements of complex social systems, on the one hand, and improvised, innovative, and responsive behaviors on the other. Proponents of Pittsburgh’s prospective, novel postindustrial identity, including those who develop and deploy smart technologies, have to observe a poorly defined boundary between promoting shared community identity and pushing Pittsburgh residents in the direction of community rigidity and even inflexibility.

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The summary of social dilemmas leaves important questions for further exploration and research. In what respects do the social dilemmas listed incorporate or point to subsidiary or overlapping social dilemmas? How should these dilemmas be characterized in terms of the tools, techniques, and concepts that are best used in elaborating their nuances and coming up with remedies? Are these urban planning challenges? Technology design challenges? Public administration challenges? Challenges regarding ideology, values, and purposes? All of these? How should observers and practitioners blend responses to questions of individual presence, identity, and activity with questions of collective, communal well-being? Documenting social dilemmas is only a beginning.

The next stage of this GKC-based investigation is describing the resources that have been implicated in smart technology systems in Pittsburgh; the actors involved in deploying, using, and overseeing those systems; and the roles that those people and organizations have played.

Resources, Actors, Roles, and Rules in Pittsburgh’s Smart City Setting

The character of Pittsburgh’s smart city social dilemmas depends on the resource(s) at stake and the people involved. This section describes key knowledge, information, and data resources in Pittsburgh as a smart city, in context, adding to conventional or traditional inventories of urban resources in physical, social, economic, and political systems. These knowledge resources are examined in themselves and also as they are intertwined with other systems that characterize Pittsburgh. The section prioritizes description of who is involved in information governance, and what resources they draw on or manage. Of lesser interest are positives and negatives of technology and related phenomena as such (including “innovation” or “concentrations of power”), or abstract values as objectives (including “equity,” “justice,” and “democratic participation”).

Data

“Data about Pittsburgh” consists of the first salient shared knowledge resource. Data includes data about Pittsburgh residents (including data about their interests, needs, and behaviors) and data about Pittsburgh as a physical place and space (including data about attributes of material infrastructures such as roads, lights, buildings, and parks). Future research may dig deeper into sector-specific and practice-specific data resources within this broad data domain. In a general sense and at both large and small scales, data about Pittsburgh capture the fact that quality of living in a communal context is a shared resource in a broad, fundamental sense.

Data that documents individual experience materializes that shared, aggregated resource and subjects it to new sorts of governance. The following sections describe extensive efforts by the City of Pittsburgh, Allegheny County, and other, related actors to collect, store, share, and use data across a broad range of smart city systems. As a shared resource, urban data is new in part, because of the novel technologies used to collect and manage it. Pittsburgh’s long history of collecting information about itself is documented in detail in the next section.

The various types of shared data in Pittsburgh include data derived from monitoring and observing environmental conditions (air and water quality; glare from street lighting; road damage) and human behavior (school attendance, movement of cars and buses). Conditions of data storage and use vary. Some are data stored in publicly managed systems for use by government actors (in particular, the Allegheny County Data Warehouse) and data stored in privately managed systems for use by both public and private actors (in particular, the WPRDC). Uses of the data vary widely as well. A lot of smart city data feeds into decision-making by government actors. Smart city data is formatted so that it is accessible and usable both by government actors and by residents and third parties, in particular, via the City of Pittsburgh’s Burgh’s Eye View data dashboards.

Expertise

A second shared knowledge resource is smart city expertise and expert governance itself, defined both by the positions and roles of decision-makers in relevant public, private, nonprofit, and higher education sectors and also by the substantive training, knowledge, and relational capital that individuals bring to bear on smart city practices. Both governance roles and the human beings who occupy them are subject to historical and political contingencies of numerous sorts. Shared expertise in Pittsburgh’s smart city context resembles shared expertise in many government and governance contexts, with the proviso that Pittsburgh’s industrial history has left a legacy of heavy reliance on locally developed and locally trained expert talent. Expertise in some cities is regularly and deeply refreshed by talented individuals moving in and out of the community, strengthening the social capital that underlies many effective city-specific and regional policy collaborations (Menashi 1997; Squazzoni 2009). For historical reasons, that has been much less common in Pittsburgh.

Even in Pittsburgh’s comparatively static setting, unlike data and datasets (which in principle can be documented as shared resources via organizational and technical criteria), expertise is a shared knowledge resource that defies simple description. Experts and expertise may be recognized by virtue of role, by credentials, by formal peer recognition, and/or by social acceptance in some relevant community (Hartelius 2020). Expert networks are often fluid groups, and the expertise that they share is likewise dynamic. What counts as smart city expertise changes, as technology evolves, and as administrative and other governance strategies evolve (Eyal 2013). In Pittsburgh, smart city leaders and practitioners observe and learn from experiences in other places.

Taking those caveats into account, I observed a Pittsburgh-related “expertise community” for smart technology that includes substantial connections to CMU, both as a training ground for professionals in technology-based professions and as a key node in constructing research partnerships with industry related to smart city technology and practice; to Pitt, which has cultivated a node of similar type and function but which focuses less on industry partnerships and more on training professionals in public administration; to Pittsburgh’s philanthropic and nonprofit sectors, much of which are staffed by graduates of CMU and Pitt; and to the City of Pittsburgh and Allegheny County itself. People and their associated expertise circulate regularly within this network, moving from CMU to Pitt (Robert Gradeck, the director of the WPRDC, worked previously at CMU); from the nonprofit sector to CMU (Rick Stafford, the founding director of the Metro21: Smart Cities Institute at CMU, was previously the Executive Director of the nonprofit Allegheny Conference on Community Development); from Pitt to the City of Pittsburgh (Chris Belasco, Enterprise Project Manager at the city’s Department of Innovation and Performance, received his PhD from Pitt and serves as an adjunct professor there); and from the City of Pittsburgh to Allegheny County. Erin Dalton, Director of the Allegheny County Department of Human Services (DHS) and overseer of that department’s AFST system, holds a master’s degree from CMU.

These are tips of the proverbial iceberg. The number of personal and professional relationships evident in the construction of Pittsburgh’s smart city community is too numerous to document in full detail here.

Community Identity

A final, central shared knowledge resource in Pittsburgh’s smart city context consists of how individuals and small groups coalesce in time and over time to establish their collective identity as a city, producing both affective benefits and social trust that can underlie community development and improvement efforts (Sabel 1993). In short, Pittsburgh as an ideational construct is a critical shared resource, subject to social dilemmas as described earlier, that contributes to and follows from Pittsburgh’s smart city trajectory. A number of intersecting processes generate that construct. Political mechanisms exist for building and sustaining it, along with the dynamics of spatial relationships. Because the process isn’t coercive, some added ingredients are necessary. In significant respects cities are the durable products of processes of shared social cognition relative to everyday experience and relative to a place (Secor 2004). Individuals signal their affective experiences to others in both purposeful and casual ways; they tap into histories of urban identity and shape its direction going forward. Key actors and nodes in cultural networks reinforce the salience of certain behaviors and cultural signifiers. In Pittsburgh’s technology practices, the largest local philanthropies have often performed this role, steering investment in smart technologies in ways that align with inherited understandings of the best interests of the community.

Taking account of the fact that these processes themselves are mostly immaterial, variable, and highly imprecise, in many cities in the twentieth and twenty-first centuries, including Pittsburgh, social cohesion and trust built on urban identity has been purchased by corporate interests. Business and political elites in Pittsburgh have repeatedly tried to capitalize on local research and development activity in the robotics sector by publicly promoting the idea that Pittsburgh has become “Roboburgh” (Dieterich-Ward 2016).

Even more important, on a broad scale, have been corporate efforts associated with professional sports teams – American football, baseball, basketball, and ice hockey in the United States; ice hockey in Canada; football (soccer) in much of the rest of the world. In Pittsburgh, the shared community identity manufactured by workplace-based communities during the steel era (Slavishak 2008) has long since been transformed into community affection for its professional sports teams, particularly the Pittsburgh Steelers American football team. Fanaticism in support of the Steelers is arguably the only phenomenon that unites most Pittsburgh residents as “Pittsburghers” across the region. Fan identity is materialized typically via the “Terrible Towel,” a small yellow terrycloth towel printed with a black “Terrible Towel” logo, that Pittsburgh residents and supporters of Pittsburgh professional sports teams twirl overhead while attending games in person, to celebrate and encourage Pittsburgh teams and fellow supporters. The Terrible Towel is an emblem and signal of Pittsburgh’s shared identity. Black and gold are the official colors of the City of Pittsburgh and the dominant colors of each of the city’s professional sports teams. They were part of the coat of arms of William Pitt, first Earl of Chatham, English Prime Minister in the late 1700s, for whom the city is named. Today, they form an integral part of Pittsburgh’s symbolic identity, together with the region’s steel history.

Actors and Roles in Action Arenas

Having sketched relevant shared resources and related social dilemmas, the next step suggested by the GKC framework is identifying how resources, actors, and their roles are assembled into “action arenas” or social contexts in which governance activity related to smart city technology takes place, generating outcomes. Taking account of public sector, philanthropic, and higher education institutions as key actors, smart city action arenas in Pittsburgh can be visualized in a general way as depicted in Figure 6.1.

Figure 6.1. Smart city action arenas in Pittsburgh, Pennsylvania

Consistent with the discussion earlier in this section, the image represents Pittsburgh as a whole as an action arena. It shows both a series of subsidiary action arenas in the form of public sector entities, university entities, and philanthropic entities. It also identifies a distinct action arena that consists of actors anchored outside of Pittsburgh that engage in some respect with Pittsburgh smart city practices, including technology vendors, nonprofit organizations, and federal and state governments. The residents of Pittsburgh, both in themselves and in the form of community organizations and private sector companies, appear as constituent members of the macro Pittsburgh action arena. For-profit firms are not represented as an action arena in themselves, because I could not discern any evidence of collective or communal firm-based governance behavior in Pittsburgh, or with respect to Pittsburgh. Instead, both local private firms and national and international private firms interacted regularly with key actors in the primary government, university, and philanthropic sectors, selling technology and sometimes offering relevant expertise.

Two important considerations dictate relying only generally on the characterization represented in Figure 6.1, rather than too narrowly or precisely, in exploring smart city governance in Pittsburgh. First, each of the action arenas identified in Figure 6.1 signifies a number of smaller action arenas nested inside it. Each action arena, large and small, is subject to a greater or lesser degree to the resource descriptions and social dilemma characterizations supplied earlier. The overlapping circles speak to data itself as a resource and to governance expertise as a resource. For example, Pittsburgh governments include the City of Pittsburgh and, within the City of Pittsburgh, several distinct administrative departments. Pittsburgh universities include CMU and Pitt. CMU includes various research and other programs within CMU, such as Metro21, the CREATE Lab, and individual faculty members’ research programs. Likewise, Pitt includes various subsidiary units and researchers. Each of those should be considered an action arena with respect to smart city initiatives. Moving flexibly from larger to smaller scales in that regard is consistent with the intuition that smaller action arenas may be nested within larger ones.

Second, Figure 6.1 signifies that action arenas in the smart city setting are evidence of a polycentric social, cultural, and political system. Polycentricity highlights substantial overlaps in formal jurisdictional authority and in informal governance responsibilities. Yet that focus may detract from the fact that both formal and informal boundaries among action arenas often are less significant in Pittsburgh than interpersonal relationships among individual actors, including both social and political relationships. Smart city initiatives in Pittsburgh often require not only substantial collaboration among and across several polycentric centers but also among and across particular individuals, whose histories and forms of expertise accompany them as they migrate from organization to organization even within the Pittsburgh city action arena as a whole. In short, the important attention given to action arenas generally tends in Pittsburgh’s specific case to give insufficient weight to individual agency and to idiosyncrasies of personal history and attitude. As between governance system and structure, on the one hand, and personality on the other, a great deal of Pittsburgh’s smart city experience has been rooted in the latter.

Within these action arenas, judgments about how governance is produced are fluid. Smart city governance in Pittsburgh has not been heavily formalized by public actors. Formal, public law governing smart city activity in Pittsburgh is relatively modest in scope. A City of Pittsburgh ordinance passed in 2014 defines municipal obligations relative to publishing public-generated datasets in a publicly-accessible repository. Today, that repository is the privately supported and operated Western Pennsylvania Regional Data Center (WPRDC). Although the legal obligations and the creation of the WPRDC were part of a coordinated governance strategy for sharing data collected by the City of Pittsburgh and Allegheny County (with the operating costs of the WPRDC largely underwritten by leading local philanthropies), the repository was funded and launched only after the city subjected itself to a duty to share information, and as of late 2021 the city was not yet fully compliant with the law. Other City of Pittsburgh ordinances mandate certain private sector compliance and disclosure in connection with green construction and aspire to return “dark skies” to Pittsburgh via procurement and installation of improved streetlighting.

Informal rules, by contrast, govern most of this activity. The highest profile individual actors in Pittsburgh’s smart city ecology emphasize that in developing and deploying smart technology, they prioritize the interests of residents, both in term of how data is collected and used and in terms of acting consistently with principles of good government. There is no doubt that those views are genuine and motivated by good faith considerations. There is no doubt that views of what is possible and what is best are informed partly by deliberation about the future of Pittsburgh and about the future of good government generally, facilitated by conversations with colleagues in other places. There is also no doubt that these views are informed by knowledge about peer community practices and the uses of technology supplied by industry consultants and other third parties.

In practice, key Pittsburgh smart city actors invoke and rely on industry-standard practices regarding data security and data privacy. The City of Pittsburgh migrated its data storage architecture to Google Cloud starting in 2021, and the contract governing that commercial relationship emphasizes Google’s security practices. That contract does not specify undertakings by any party as to the privacy of residents or other data subjects. Interviews and document reviews for this study revealed no standard or typical practice by the City of Pittsburgh relative to sharing information with residents about possible privacy interests implicated by deploying smart city systems, other than consultations as needed with lawyers employed by the city and with third-party technical and policy experts. Nevertheless, the purpose of the move to Google Cloud is unambiguous: to use the Google Cloud infrastructure to build a “data lake” of pooled data for use in data analytics and data reporting. In homage to the specifics of Pittsburgh’s geography, and in contrast to Allegheny County’s Data Warehouse, the City of Pittsburgh pool is known as “Data Rivers.”

By contrast, public access to the WPRDC repository is governed, formally, by a click-through “Data Use Agreement.” That text is directed almost entirely to exonerating WPRDC and its sponsors and supporters from possible liability associated with using WPRDC-hosted data. As a practical matter, the WPRDC has no resources to follow up on or monitor compliance by community-based data users, and the disclaimer, like many click-through disclosures online, is both legally enforceable and, practically speaking, likely to be ignored. The presence of the disclosure does signify at least modest acknowledgment by WPRDC and its partners and sponsors that confidentiality, privacy, and security concerns are present when public data about resident activity is collected, curated, and shared. The WPRDC’s judgments about those values operate at a level that is tailored to its perception of its interests and those of city residents – as well as to the level of the University of Pittsburgh, which is WPRDC’s parent organization. Other actors express different judgments. Some datasets produced by the Allegheny County Department of Human Services have not been accepted for deposit with the WPRDC on account of differing understandings as to privacy protections afforded the subjects in the Allegheny County data.

The last notable feature of smart city governance in Pittsburgh, framed by the action arenas identified in Figure 6.1, is that smart city actors perceive that they are participants in a gift economy. That characterization applies both to their dealings with one another and also, at times, to their dealings with members of the broader Pittsburgh community. This is characterized partly in “pay it forward” terms, with the expectation that a kind of informal karmic justice associated with free and open sharing of civic data would eventually return benefits to the donor. It is characterized partly and more concretely in terms of overcoming obstacles to technology deployment by giving away time and expertise for free, particularly within large government organizations where time and technology expertise are not widely distributed in staff or budget terms. Representatives of technology firms that sell smart city technologies to cities distinguished their strategic consulting counsel as to smart technology uses from separate sales efforts. That perspective has both gift-oriented and profit-oriented motivations. The gift-oriented practices and attitudes confirm the existence of an informal network of favor exchange and loosely patterned cooperative behavior rather than a system of strong reciprocity or altruism (Jackson, Rodriguez-Barraquer, and Tan 2012). The content of governance practices in Pittsburgh’s smart city contexts, or what might be termed Pittsburgh’s smart city “rules-in-use,” appears to be less significant for what they require or permit and more significant in that they confirm the existence of a community of smart city practice and expertise.

Contingency and Context: Pittsburgh’s Smart City History

Smart cities emerge and evolve in ways that aren’t captured by descriptions of the political economy of cities (Frug 1999; Glaeser 2012), by the political economy of modern ICTs (Goodman and Powles 2019; Latham and Sassen 2005), or even, as per the previous section, by the logic of thinking through relationships among resources, dilemmas, actors, and rules. Pittsburgh’s smart city experience and smart city governance cannot be understood or interpreted effectively without giving significant attention to Pittsburgh’s history. The GKC framework enables researchers to include historical context in their exploration of commons governance.

For more than a century, Pittsburgh has been in the forefront of urban planners’ efforts to acquire data about urban conditions. That’s a description, not a celebration. Pittsburgh’s efforts to be systematic, productive, and not harmful in using data about itself have been inconsistent and intermittent. Sometimes, Pittsburgh has put that data to productive use. Sometimes, Pittsburgh leaders have ignored the data. This section shows how, and in the process it sets the stage for explaining many of the wider directions and smaller choices evident in Pittsburgh’s contemporary smart city governance. Many of its modern smart city moves are comprehensible only in the specific context of the detailed history of Pittsburgh as a distinct place, geographically, economically, politically, and sociologically (Lubove 1969; Madison 2012), and as the place that Pittsburgh and Pittsburghers imagine that Pittsburgh was, is, or may become (Neumann 2016).

The Origins of Pittsburgh’s Intelligence

When it comes to smart city governance and to knowledge-sharing practices in particular, Pittsburgh is significant as much for who and what is left out as for who and what is included. Those patterns of inclusion and exclusion have deep roots.

During the 2013 campaign that led to his election as the sixtieth Mayor of Pittsburgh, Bill Peduto published a list of 100 actions his administration would initiate during its first 100 days. Number one on the list was “A 21st Century Pittsburgh Survey.” A Pittsburgh native and long-time member of the Pittsburgh City Council, Peduto brought with him a deep knowledge of the city’s history and a wish to see it achieve a twenty-first-century version of its twentieth-century glory. As mayor, Peduto aimed to replicate one of the first and greatest works of urban sociology ever produced for an American city.

The original Pittsburgh Survey, funded by the Russell Sage Foundation in New York and Chicago (then the Russell Sage Foundation for the Improvement of Living Conditions) and published between 1908 and 1914, appeared initially in thirty-five magazine articles and eventually was collected in six volumes of research (Greenwald and Anderson 1996). In its time, it was a first-of-its-kind, uniquely comprehensive data-focused examination of social welfare in an American community, synthesizing research on living conditions, working conditions, and industrial production in a single place (Lubove 1969).

Taking account of both the city itself and what the Survey, following common practice at the time, called the Pittsburgh Steel District, Pittsburgh was an enormously and almost incomprehensibly productive industrial place. During the nineteenth century it was known as the “Iron City.” During the twentieth century, the nickname was updated to the “Steel City.” The metallurgical metaphors were paired with a third, the “Smoky City,” due to Pittsburgh’s dirty air. An 1860s Pittsburgh travel writer noted that Pittsburgh was so vibrant with the fires and smoke of industry that he called Pittsburgh “hell with the lid taken off,” and he meant that as a compliment (Madison 2012).

The “Steel District” geographic designation mattered to both researchers and local leaders more than a formal “City of Pittsburgh” identity, and related geography matters even today. Much of the steel production and associated industrial activity in Pittsburgh, including company towns, was located outside the City of Pittsburgh proper. Pittsburgh’s coal mines and steel mills were almost always located up Pittsburgh’s valleys, particularly up the Monongahela River and down the Ohio River, rather than in or near the urban center. The mills took advantage of the transportation economies that the rivers afforded relative to importing iron ore and exporting finished product.

Given the scale of the industry, workers associated with the steel industry – largely immigrants, in the late 1800s and early 1900s – were distributed around the Pittsburgh region. They were concentrated partly in company-supplied housing and partly in communities and neighborhoods adjacent to related industrial complexes, distributed across both the city and also in the less accessible, riverside locations that housed the largest mills. For most of its residents, the Pittsburgh Steel District was an awful place to live, with much of the population living in structures built to nonexistent housing codes and with virtually no modern water or sewer service.

Researchers for the Pittsburgh Survey aimed to document all of that, not to highlight anything specific to Pittsburgh but to use Pittsburgh as an exemplar of industrial conditions and social welfare across the United States. This was not, primarily, aimed at local reforms. The Survey was developed, researched, and written in response to an intervention by a small group of Pittsburgh business and community leaders who were aligned with the Progressive political movement nationwide. The vehicle for their interest was the Charities Publication Committee of New York; the host publication was Charities and the Commons: A Journal of Constructive Philanthropy. The point was fundamentally about Progressive politics: using data to support anti-corruption reform of public administration (out with patronage systems, in with the experts) and both voluntary and government intervention to improve residents’ social welfare.

(Pittsburgh wasn’t immune to ordinary efforts to improve urban living conditions. Around the same time that the Survey was researched and written, the City of Pittsburgh commissioned a report on its transportation infrastructure from a Chicago-based engineer. The report, released in 1910, was titled Report on the Pittsburgh Transportation Problem and criticized the lack of integration of the region’s many local streetcar companies.)

The Pittsburgh Survey generated massive amounts of data about industrial life, living conditions, and the environment. Locally, in practice, its impact was limited. (Pittsburgh had more success consolidating its streetcar operations.) To the extent that Pittsburgh absorbed the Survey’s lessons and welcomed political Progressivism, the movement took on a distinctly business-friendly character. The historian Roy Lubove chronicled in detail how the charitable impulses of the Pittsburgh business community married its market-dominating impulses during the 1920s, 1930s, and 1940s. Improvements were directed to physical infrastructure rather than to measurable changes to underlying questions of equity and social justice. Pittsburgh business leaders in partnership with Pittsburgh politicians endorsed and advanced housing reform legislation, investments in urban planning, and modest progress toward modern infrastructure, all in the interest of protecting and advancing Pittsburgh’s market positions in industrial production (Lubove 1969).

Throughout, the initiative to rely on the data and to begin the reforms depended on the essential political power of Pittsburgh’s business elite. That group consisted of a relatively small number of senior men serving as chief executives of large industrial firms that were, for all practical purposes, family-run enterprises. In the late 1800s and early 1900s, the group was led, politically, culturally, and economically, by Andrew Carnegie and Henry Clay Frick, industrialists, and Andrew Mellon, financier. Through the 1930s, their heirs and successors carried on the tradition of Pittsburgh leadership by Pittsburgh industry.

In 1943, informal collaborations between Pittsburgh’s business leaders and government leaders were consolidated and formalized in the Allegheny Conference on Community Development (ACCD), an early and durable public–private partnership in the form of a nonprofit corporation. The ACCD was energized largely by the leadership of the Mellon family banking and oil, gas, and coal concerns (embodied initially in Richard King Mellon), together with chief executives of other leading Pittsburgh companies (men named Mellon, Heinz, Kaufman, Hunt, and Hillman, and companies including Gulf Oil, Alcoa, U.S. Steel, Pittsburgh Plate Glass (now PPG Industries), and Heinz). This was noblesse oblige on the part of the individuals involved as much as corporate direction of state activity, in the guise of philanthropy. (The original by-laws of the ACCD required that member entities participate in the person of the company’s CEO or president, making elite governance formal and explicit.) The ACCD was made effective and durable by the active participation of Mayor David Lawrence (later Governor of Pennsylvania) and the local Democratic Party machine. The by-laws were later amended.

In the hands of the ACCD, in most respects, what needed to be done in Pittsburgh meant civic improvements to produce and reproduce the economic successes that defined the first half of Pittsburgh’s twentieth century. The ACCD took on the roles of coordinating regional planning across both business and local governments in the Pittsburgh region and of building community consensus around specific initiatives. In effect, the City of Pittsburgh and surrounding communities outsourced much of the visioning process to a public-spirited top tier of the private sector.

During the 1950s, the payoffs mostly consisted of productive investments in infrastructure: cleaning Pittsburgh’s smoky air by banning coal-fired home furnaces; cleaning the worst elements of Pittsburgh’s dirty rivers by regulating waste disposal; building modern highways and air transportation through Pittsburgh; organizing formal public health institutions; and redeveloping the most industrial sections of Pittsburgh’s Central Business District, replacing train sheds and related facilities with modern skyscrapers and parks. That initial round of improvements is often characterized by both historians and boosters as the “Pittsburgh Renaissance” (Madison 2012).

During the 1960s, the payoffs mostly meant urban renewal, clearing out so-called slums (predominantly Black neighborhoods) and replacing them with amenities for Pittsburgh’s (predominantly white) professional class. The steel-domed Civic Auditorium, opened as a concert venue in 1961 (and demolished fifty years later, having acquired an afterlife as a sports arena), was intended to showcase Pittsburgh’s metals industry for the benefit of prospective investors in the region. Its construction eradicated the much of the cultural center of Black life in Pittsburgh, known as the lower Hill neighborhood, home to a thriving arts community and to more than 8,000 people.

Pittsburgh’s Intelligences of the Late Twentieth and Twenty-First Century

That rhythm – a data-fueled baseline for good government and welfare improvements, followed by an elite-driven, intuition-based, largely privatized set of visions, strategies, and tactics – defined Pittsburgh for much of the twentieth century. The pattern can be documented and illustrated further with efforts by Pittsburgh public authorities – and iconoclasts.

Around the same time that the Pittsburgh Survey was being produced and published, Frederick Law Olmsted, famous as one of the designers of New York’s Central Park and other well-known public parks and recreation facilities in the United States, was retained by Pittsburgh’s business elite to produce plans for Pittsburgh. As planners and designers, Olmsted and his firm would rely on the bureaucracy of urban planning to implement their visions, but their charge was to tame Pittsburgh’s appalling physical and social conditions and, in cleaning and regularizing the conditions of urban life, to instill the working people of the city with “appropriate” moral order (Ingham 1991). This was Progressivism at work in a different register, top-down rather than, as with the Pittsburgh Survey, data-driven and bottom-up. As in the work of Ebenezer Howard (author of the utopian planning guide Garden Cities of To-morrow: A Peaceful Path to Real Reform in 1898), orderly and systematic urban planning – in a manner of speaking, the smart city of yesteryear – was a mode of social reform (Beevers 1988).

Olmsted’s vision, delivered in a report in 1910, was adopted only in part. As with the results of the Survey, pragmatic physical improvements were pursued while social justice implications were ignored. Today, many of Pittsburgh’s larger boulevards and bridges owe their origin to Olmstead (Bauman and Muller 2006). Pittsburgh’s regional parks and nearby vacation destinations were built in the same era, displacing local working class communities in the interest of the patronizing impulses of the business community (Dieterich-Ward 2016).

The top-down planning impulses of Pittsburgh’s power structure had additional manifestations, with a more entrepreneurial character. Pittsburgh’s most celebrated work of modern architecture, the Frank Lloyd Wright masterpiece Fallingwater (a vacation house located in the Allegheny Mountains just southeast of the city), was commissioned by Edgar Kaufmann, Sr., a local department store magnate. Kaufmann was so taken with Wright that he commissioned the architect in the 1940s to produce a series of futuristic plans for a civic center and related infrastructure to be built at the Point, the tip of the Downtown Central Business District. The civic center never came to pass; there is little evidence that the plans were ever seriously considered by the city. Kaufmann’s instincts were on the right path, however. The Point was leveled and remade as part of the Pittsburgh Renaissance during the 1950s. Among the new, related developments was a series of high-rise cruciform buildings clad in chrome-alloyed steel that evoke the 1920s Radiant City “Towers in the Park” vision of modernist, technocratic urban planning promoted by the architect Le Corbusier.

The planning impulse did not abate. In 1963, researchers at the University of Pittsburgh, together with the Pittsburgh Regional Planning Association (a subsidiary of the ACCD), produced a three-volume study addressing the economic prospects for the region, titled Economic Study of the Pittsburgh Region (Chinitz 1961; Lubove 1965). It concluded that Pittsburgh’s economy was stagnating as the era of structural steel production in the area was likely coming to an end. The study called for a transition to a more technology-driven economy. That recommendation was all but ignored. A complementary effort to develop a comprehensive computer simulation of Pittsburgh’s land-based resources to support data-driven planning efforts was terminated and abandoned before it could be completed (Brewer 1973).

At the other end of the spectrum of community institutions, federal antipoverty programs and model cities initiatives during the 1960s encouraged the development of neighborhood-specific organizing in Pittsburgh. Those organizing efforts included the preparation of a Pittsburgh Neighborhood Atlas during the early 1970s, which surveyed residents about neighborhood satisfaction and satisfaction with public services, and documented data from seventy-eight Pittsburgh neighborhoods about real estate prices, loans and tax delinquencies, and welfare assistance. Funded largely by the University of Pittsburgh through its School of Social Work and completed in 1977, the Atlas and the organizing behind it contributed significantly to defining Pittsburgh’s neighborhoods in their modern configuration (now ninety in all) and to cultivating the neighborhood – otherwise omitted from the vision advanced by the Allegheny Conference – as an effective locus for community participation in planning, reconstruction, and economic development (Cunningham et al. 1976; Lubove 1996).

The Atlas was conceived and produced specifically as a counterpoint project, contrasting common perspectives against elite perspectives, rather than as a complement to the efforts of regional leaders. Following the collapse of the steel industry in Pittsburgh in the early 1980s, Pittsburgh leaders again promoted efforts to anchor the region in integrated visions of technology-based industry. In 1985, a coalition of Pittsburgh leaders (the ACCD, the presidents of the University of Pittsburgh and Carnegie Mellon University (CMU), the Mayor of the City of Pittsburgh, and the political leaders of Allegheny County) published the Strategy 21 report, proposing an economic development plan for the region in the wake of the end of the steel era (Deitrick and Briem 2021). The report recommended pursuing an elaborate, data-focused effort to diversify the region’s economy away from its historical reliance on heavy manufacturing. Only one of the report’s significant recommendations was adopted. Pittsburgh built a major new international airport.

Out of the Furnace and Toward the Smart City

Pittsburgh’s historical tension between empiricism and elitism offers the key byway into understanding Pittsburgh’s smart city conditions today, even as the specific shape of that tension changed. It has been suggested that the rise of Pittsburgh’s two leading research universities and its largest philanthropies during the latter half of the twentieth century, and the decline of Pittsburgh’s old industrial and financial sector firms, brought with it a loss of interest in the cultural fabric of the city. The old industrialists’ possibly patronizing but nonetheless real focus on the lives of the people disappeared in favor of a focus on metrics (Lubove 1996). The criticism is overstated. In practice, governance technologies and tactics changed, and with new tactics came new goals. Good governance became measurable, at least in principle, rather than simply evident in residents’ and companies’ experience. The new players emerging in the later twentieth century and early twenty-first century brought forward a new and explicit focus on public administration and governance as goals in themselves, sharpening a distinction between this more modern, technocratic attitude and the noblesse oblige that inspired the original ACCD.

In other words, the era of a small number of supremely wealthy families in Pittsburgh actively driving the direction of the city, as heirs to the industrial and financial leaders of the late nineteenth century, ended. New key players emerged, taking their places alongside political leadership and the leaders of the region’s largest private companies, particularly the leaders of the foremost universities in Pittsburgh; the leaders of its largest employer; and the leaders of its major philanthropic organizations.

In 2013 and early 2014, Mayor Peduto’s list of 100 inaugural actions did not include turning Pittsburgh into a smart city or producing a smart city strategy. The list of 100 actions did include a number of items that fall within anyone’s definition of smart city administration. More important than the list itself, however, the Peduto administration helped to consolidate preexisting Pittsburgh assets and investments in data-driven government and private sector technology development, and to accelerate Pittsburgh’s reliance on smart city systems by weaving narratives that expressed smart city visions. This subsection summarizes the assets first, and then the visions.

Assets and Liabilities

Local politicians and promoters today tell a tale of Pittsburgh as a city that is capitalizing rapidly and thoroughly on the region’s historic, contemporary, and distinctive strengths in computer science and robotics (TEConomy Partners, LLC 2021). Among US cities, perhaps only Cambridge, Philadelphia, and Palo Alto share Pittsburgh’s justifiable claim to having birthed so much of both modern computer science and internetworking technology. Chief among Pittsburgh’s historical and contemporary assets in that regard is an elite private technical university founded by Andrew Carnegie (CMU, formerly known as the Carnegie Institute of Technology, or Carnegie Tech). CMU is famed as the home of much of the world’s earliest research on computing and today focuses a significant amount of its research on engineering, computing, and robotics. CMU anchors a small but growing technology economy directed largely to autonomous systems specifically and to ICTs generally. Pittsburgh aims to use those strengths both massively to improve the quality of Pittsburghers’ lives and also to attract new industries and employers to the area. The smart city in Pittsburgh is inseparable from broader enthusiasms about technology and economics. A corresponding new political economy is in formation, produced by and in response to the expectations of Pittsburgh’s newer, younger, more technologically oriented population (Winant 2021).

To Pittsburgh insiders, CMU’s influence on Pittsburgh’s “smart” trajectory has been important but not uniquely deep or durable. Certainly, CMU is one key institutional player locally. Its first notable smart city technology venture, the urban design research center at CMU’s School of Architecture known as the Remaking Cities Institute (RCI), opened in 2006 with funding from one of Pittsburgh’s leading foundations. The RCI led in 2009 to the formation of a traffic- and transportation-themed research center to bridge academic and industry interests, and in turn that organization, Traffic21, led to the formation in 2014 of Metro21: Smart Cities Institute, with a similar theme but with a smart cities focus. Metro21 coordinates or supports a variety of smart city research projects, including 3D visualizations; landslide warning systems; air quality and light pollution monitoring; paving and curb design; and programs for public art. Mayor Peduto later referred to Metro21 as the City of Pittsburgh’s research and development wing with respect to smart city technology (High 2017). In the pluralistic CMU environment, the separate Robotics Institute, now the focal point for the university’s long-standing research program in robotics, houses the CREATE Lab. CREATE stands for Community Robotics, Education and Technology Empowerment, and the lab differs from Metro21 in its focus on community engagement and transformation through community-generated technology innovation.

But like most research organizations of its type, CMU looks to achieve impact and status on a global stage rather than principally in its backyard. Its investments in Pittsburgh are typically part and parcel of using locally developed experience and data to expand its research impact much more broadly.

In the size and scale of its research enterprise, CMU is dwarfed by a second world-leading university, the University of Pittsburgh, or Pitt. Pitt’s impact on the regional economy has been more substantial than CMU’s, partly because Pitt is a publicly affiliated institution and in some respects prioritizes local and regional community impacts in its research and teaching programs, partly because Pitt enrolls far more students and employs far more faculty and staff, and partly because Pitt’s primary research interests lie in the health sciences, not ICTs. The clinical care organization spun off from Pitt’s medical education complex, formerly called the University of Pittsburgh Medical Center and today called UPMC Health Systems, is the largest employer in the Pittsburgh region and a close partner of the University of Pittsburgh. Only recently have Pitt researchers shown any real interest in smart city technology, but as described further later, Pitt’s history and identity give it a substantial, important, and necessary presence in Pittsburgh’s smart technology investments.

The rise of Pittsburgh’s two leading research universities is half the story of the shift in emphasis in Pittsburgh’s leadership during the latter part of the twentieth century. The other half of the story is the emergence of large-scale philanthropies as critical leaders and shapers of all aspects of regional development. Pittsburgh’s philanthropic sector is extraordinarily large in proportion to the size of the city, a phenomenon that is usually traced to the public generosity of the city’s industrial leaders extending back to Andrew Carnegie (Buechel 2021). Three of them are particularly notable both for their contributions to Pittsburgh life as a whole and to their participation in ICT-driven economic development and, now, smart city systems.

One is the Heinz Endowments, with assets of over $1 billion, which is the combined form of the Howard Heinz Endowment and the Vira I. Heinz Endowment. Both Heinzes were members of the family associated with H. J. Heinz Company, today Kraft Heinz, originally headquartered in Pittsburgh. The second is the Hillman Family Foundations, a collection of eighteen separate foundations administered centrally in Pittsburgh, with just under $500 million in assets. Henry Hillman was a mid-century industrialist and investor in Pittsburgh. Third is the Richard King (R. K.) Mellon Foundation, with assets of approximately $3 billion. R. K. “Dick” Mellon was a member of the Mellon banking family.

These three foundations, among many philanthropic organizations in Pittsburgh, exercise their leadership and influence partly through their grantmaking. Pittsburgh has relatively little of the risk capital that characterizes twenty-first-century technology markets in Silicon Valley, New York, and Boston. Early funding characteristically comes from Pittsburgh’s philanthropic sector for a broad range of activities: for public sector projects, technology infrastructures for private sector initiatives, for startup ventures in the nonprofit sector, for significant higher education initiatives, and for public–private collaborations. Influence is exercised in less direct and more informal ways, as foundation leaders work with project sponsors to shape initiatives and broker relationships among multiple possible participating entities. Foundation leadership in Pittsburgh has come to exercise much of the leadership responsibility, and receive much of the cultural deference, once associated with Pittsburgh’s industrial CEOs. The foundations and their leadership are often perceived by other Pittsburgh elites as honest brokers.

Meanwhile, Pittsburgh’s industrial heritage contributes to its smart city strategies and goals in several underappreciated ways, both for better and for worse.

Geography is the first. On the map, Pittsburgh sits on the western edge of a north–south mountain range that runs diagonally from New Hampshire in the north to Georgia and Alabama in the south, changing names as it goes. In Western Pennsylvania, these are the Allegheny Mountains, and they give Pittsburgh both its extremely hilly character and the two rivers that converge at the tip of the broad peninsula on which Pittsburgh’s Downtown neighborhood sits. (Pittsburgh’s Downtown is sometimes known as the Central Business District, or CBD.) That convergence, known as “the Point,” serves as the head of the Ohio River and the focal point for modern Pittsburgh’s business and government institutions. Pittsburgh’s geography is mostly a dilemma – not a social dilemma, but a physical obstacle. Pittsburgh’s hills and valleys are significant barriers to population and material mobility of various sorts and thus the material foundations for its fragmented governments, its transit and transportation challenges, its community equity (and occasional lack thereof), and its uneven progress toward pollutant-free air and water. Geography is also opportunity. If smart technologies can be proved to be effective in Pittsburgh’s difficult territory, then their success in less irregular urban settings is all but assured.

Imagined identity is the second. In the public imagination, particularly across the United States as a whole, twenty-first-century Pittsburgh may seem to be bigger and more substantial as a population and economic center than it actually is. Some of that public identity likely derives from the persistence of the public impression of twentieth-century Pittsburgh industry. Many Americans know Pittsburgh not as an actual producer of steel but as the place that once dominated the American steel industry. The mental image of industrial size and impact is carried forward via the city’s professional sports teams. The exceptionally successful Pittsburgh Steelers American football franchise has a noted global following to go with its passionate regional fan base. Imaginary Pittsburgh often gives regional leadership the ambition to think in big terms, particularly with respect to ICTs in both private and public sectors, often out of proportion to Pittsburgh’s likely economic trajectory. Pittsburgh’s public and private leaders regularly put forward the idea that Pittsburgh’s postindustrial destiny is inextricably linked to restoring Pittsburgh’s leading role on the stage of sophisticated world cities.

Actual size is a third. The impression that Pittsburgh’s historical scale continues to characterize Pittsburgh today is mistaken. Pittsburgh is modest by any standard. Today, Pittsburgh counts roughly 300,000 residents within the borders of the city itself. The metropolitan region of which Pittsburgh is a part, also often referred to (confusingly) as Pittsburgh, has roughly 2.3 million residents. The majority of those (roughly 1.2 million) live in Allegheny County, of which Pittsburgh is the largest city. The rest live in nine counties that surround it. These occupy Pennsylvania’s southwestern corner. Philadelphia, much larger and the largest city in Pennsylvania, sits in the state’s southeast corner, roughly 300 miles to the east. The small size of the City of Pittsburgh relative to the size of the county and the metropolitan area is due to historical patterns of development and economic dislocation. (The population of the City of Pittsburgh peaked between 1930 and 1955 at roughly 700,000; the metropolitan population of that era was roughly 3 million people.) Modern Pittsburgh’s size has contemporary benefits in the smart city context: the size of the professional class in Pittsburgh is quite small, both in its geographic dispersion and in its absolute size. Its expertise network has an intimacy that may be missing in larger cities.

Population dispersion, wealth, and mobility is a fourth. All cities have heterogeneous populations; Pittsburgh’s heterogeneity simply has its own, highly context-specific variations. Industrial and postindustrial patterns of economic activity impact Pittsburgh demographics more than the reverse, and the strengths and weaknesses of both public and private sector ICT systems on the ground are related in part to the industrial geography (and now postindustrial geography) of Pittsburgh’s neighborhoods and suburbs. On the ground, that means that the bulk of Pittsburgh’s population settled across the region in close proximity to its largest industrial plants. Because those were fixed in place, throughout the twentieth century population churn was low relative to patterns in similarly sized and larger cities elsewhere, in terms of both internal mobility among communities and population migration into and out of Pittsburgh.

That pattern of immobility has proved difficult to shift following the collapse of the steel industry in the early 1980s. A handful of City of Pittsburgh neighborhoods and nearby suburbs now experience more population dynamism and higher incomes, in that they are dominated today by families and others working in the professions, in newer ICT-related industries, in healthcare, and in higher education. Elsewhere, the end of the steel era largely consolidated existing demographics, with communities either depopulating or replicating themselves at smaller scales. The towns where the early steelworker populations were largest, particularly up and down Pittsburgh’s rivers, remain among the hardest hit economically by the end of the steel industry. Because Pittsburgh’s demand for labor was essentially fixed by the steel mills shortly after the turn of the twentieth century, the American Great Migration of Black Americans did not impact Pittsburgh to the degree that it affected other industrial cities, including Chicago, Detroit, and Cleveland. The city’s Black population, small and fragmented to begin with, has been migrating steadily out of the city since the turn of the twenty-first century, moving mostly toward Pittsburgh’s eastern suburbs. The lack of economic expansion in Pittsburgh during the second half of the twentieth century, and the corresponding lack of migration to the city, means that its Hispanic and Asian and Asian American communities are minute in comparison to their presence in Pittsburgh’s peer cities.

Transportation and transit are a fifth. Today, transit links between and among neighborhoods and towns around the region are notoriously weak, compounding mobility and access problems created by Pittsburgh’s geography and reinforced by twentieth-century population dispersion. Regional roadways and urban railways were built in the early twentieth century to accommodate industrial needs and residential patterns that suited the mills. But the topography of the region and its focus on infrastructure developed by and for industry left the region without a road system or transit system coordinated and ready for development at a larger scale. The Pittsburgh Railway Company consolidated streetcar lines across the region shortly after the turn of the twentieth century, but, like streetcar operators across the United States, beginning in the late 1950s it yielded to political, economic, and social imperatives to invest in highways. Yet modern interstates penetrated Pittsburgh only in part; as steelworkers started to move out of mill towns and into emerging post-World War II suburbs, the architecture of the early interstate highway system in Pittsburgh largely aligned with the development of those newer communities rather than with broader regional interests. Transit and transportation systems largely reinforced the region’s geographical fragmentation.

Adding these industrial carryovers and contemporary interests together yields Pittsburgh’s ongoing intense attachment to the small-scale hilltop and river valley communities and neighborhoods that developed in the shadow of the steel mills more than a century ago. The American political system is famously fragmented, but even against that baseline Allegheny County shines for its extraordinary acceptance of micro governments. It is home to 130 self-governing municipalities, including the City of Pittsburgh. That’s the largest number of autonomous governments of any Pennsylvania county and both the cause and the effect of the region’s fragmented political governance. Moreover, the City of Pittsburgh itself formally recognizes ninety distinct neighborhoods, many of which are home to semi-autonomous economic development organizations. Allegheny County has forty-three separate school districts, each of which possesses independent taxing authority under Pennsylvania law and, like the county and its municipalities, its own procurement system. For historical and now cultural reasons, these communities are customarily focused intensely on inward-facing community participation and governance rather than outward-facing questions of broader regional collaboration and cooperation (Madison 2012).

Smart City Visions

The cultural and political effects of older industrial Pittsburgh, while present in today’s experience, are increasingly attenuated. Both its political and business elites and its community-based governance are gradually accepting and in many respects even trying to promote the transition to a postindustrial world. Pittsburgh is gradually becoming less of the place that it was, dominated by the ethos of industrial production, meaning large workforces making things, big companies, and benevolent corporate leaders, and more of a place that prioritizes best modern government and governance practices. A new political economic settlement has yet fully to emerge, but Pittsburgh’s smart city investments are developing both as part of the transition and in its shadow.

Pittsburgh’s emergence into its current smart city era is thus characterized by governance conditions both at the top of its political-economic hierarchy (elite power and wealth) and at the community level (unusually strong micro governance) that coevolved with its twentieth-century model of highly integrated, concentrated industrial capitalism. In important respects, leadership styles and strategies have carried on as they did earlier in the twentieth century, planning from the top down for a new industrial future and now for a postindustrial future. Regional integration and collaboration along political, economic, or technological dimensions are almost entirely products of high-level public–private partnerships of the sort represented by the Allegheny Conference. The ACCD itself, with its affiliate and partnership organizations, remains a central participant in postindustrial coordination activities, along with other, more recently introduced organizations that focus explicitly on technology-themed sectors.

That synthesis means that Pittsburgh has no shortage of ambitious, even visionary plans for the city and region, plans that are now anchored in “innovation,” “technology,” and elements of the smart city. Often speculative and only partly realized in practice, they reflect a long-standing impulse to think from the top down in grand, urban, modernist terms, to sculpt the city to suit leaders’ tastes and ambitions. These modern efforts signify less in terms of tangible results as to knowledge or data sharing and more in terms of Pittsburgh’s continuing efforts to build and rebuild a certain mode of elite-led governance that is hierarchically conceived and technocratically implemented.

In 2014, Pittsburgh was a finalist in the national Smart City Challenge, a competition organized by the US Department of Transportation that awarded a $50 million grant to a public–private partnership focused on ambitious smart city pilot projects. That effort, called SmartPGH, was a collaboration among the City of Pittsburgh, Allegheny County, the Port Authority of Allegheny County, regional utilities, and leading philanthropies that focused on using smart technologies to reduce emissions from public and private transportation systems. Although the proposal was not successful in the Smart City Challenge itself, it catalyzed the formation of Metro21 at CMU and staked Pittsburgh’s national reputation in smart city efforts.

The so-called p4 initiative was launched in 2015, “Pittsburgh for People, Planet, Place and Performance,” rallying investors and philanthropies to projects highlighting the role of data in public administration, particularly in environmental, employment, and housing contexts. It aimed at making Pittsburgh a “city of the future” via urban growth and development coordinated through the Urban Redevelopment Authority, a public entity acting in coordination with the City of Pittsburgh. p4 later lost its alliterative title and became a City of Pittsburgh “City of the Future” initiative directed to environmental sustainability. Some of the development work undertaken in connection with p4 was rolled over into a “ForgingPGH” comprehensive visioning process that was intended to elicit community input via scenario planning. A parallel program, Pittsburgh’s “Roadmap for Inclusive Innovation,” included strategies to address Pittsburgh’s digital divide, government data transparency, and technology-related entrepreneurship.

In 2017, the Brookings Institution think tank, on a commission from the City of Pittsburgh, leading Pittsburgh philanthropies, and leaders in Pittsburgh’s high technology sector, delivered a report recommending that Pittsburgh commit to an integrated, leadership-driven economic development strategy to accelerate the region’s transition to a technology-and-innovation-based economy (Andes et al. 2017). Pittsburgh’s slow rebound from the end of the steel era had already attracted global attention; President Barack Obama called attention to it by arranging to host the 2009 Group of 20 meeting in Pittsburgh.

The Brookings Report prompted both the formation of a formal philanthropy-funded coordinating entity (InnovatePGH) and the launch of a regular series of leadership meetings, as to tech-centered development, among the mayor of the City of Pittsburgh, the presidents of the region’s two leading universities (the University of Pittsburgh and CMU), leaders of Pittsburgh’s largest philanthropic organizations, the County Executive (the elected leader of Allegheny County), and the head of UPMC Health Systems.

A similar coalition of public and private leaders, facilitated by the modern version of the ACCD, assembled Pittsburgh’s proposal in 2018 to secure an Amazon headquarters facility, the so-called Amazon HQ2, as part of Amazon’s national intercity competition for that prize. (By that time, the ACCD had expanded its mission and taken on an explicit ambition to serve as an ambassador for Pittsburgh business (Nunn and Rosentraub 1997).) Pittsburgh’s bid was released publicly only long after Amazon chose another contender. The bid relied heavily on the collaborative culture that Pittsburgh’s business and government elite built among themselves during the region’s steel heyday.

More recently, in 2021 the City of Pittsburgh promoted the “OnePGH” plan, which aimed to link the city, the nonprofit community, and local philanthropies in efforts to promote affordable housing, green infrastructure, and workforce development, and a “2070 Mobility Vision Plan” that speculated about a hyperloop system, high-speed trains, aerial trams, vertical takeoff and landing vehicles, and an updated network of bridges. (Transportation is an important contemporary theme; 2021 also saw the release of a “Downtown Mobility Plan” by the Pittsburgh Downtown Partnership, an ACCD affiliate; a regional long-range plan produced by the Southwestern Pennsylvania Commission, and a NEXTransit plan spanning twenty-five years from the Port Authority of Allegheny County.) The Pittsburgh Robotics Network, an alliance of private industry and economic development organizations that took shape after the publication of the Brookings Institute Report in 2017, published a proposal in 2021 for $150 million in public funding of industrial research and development to accelerate the growth of Pittsburgh’s robotics and autonomous technology sector. Last but by no means least, in 2021 the Richard King Mellon Foundation announced a commitment to donate $150 million, the largest grant in the foundation’s history, to Carnegie Mellon University to support technology research initiatives directed to the community, and $100 million to underwrite a new “BioForge” biotechnology manufacturing facility in Pittsburgh. The CMU funds are designated for supporting research and programming at the intersection of technology design and community engagement in Pittsburgh; the BioForge fund is aimed at catalyzing new commercialization efforts building on health sciences research at the University of Pittsburgh.

The Blossoming of Pittsburgh as a Smart City

In addition to these relatively grand plans, Pittsburgh’s contemporary smart city investments have a variety of recent specific antecedents in both public and private sector technology deployments. Pittsburgh has never tried meaningfully to follow a plan regarding information technology, either as mode of government practice or as focus of economic development (Deitrick and Briem 2021). Its efforts have advanced on the ground at lower levels. Some present practices are traceable to initiatives from twenty years ago and before. The Pittsburgh Neighborhood Atlas, from 1977, was a significant early modern effort to build an information system for the city. Other key early smart city ventures are highlighted here.

Three of these focused on civic data and public administration in the City of Pittsburgh. The first, 3 Rivers Connect (3RC) (named for Pittsburgh’s location at the confluence of three rivers), was a private nonprofit initiative launched in 1999, founded and operated by researchers connected to CMU, leveraging privately developed, venture capital-backed database, search, and visualization technology distributed in a pair of sister companies, MAYA Design and MAYA Viz. It was funded by Pittsburgh-based philanthropy. Characterizing itself as a venture in “civic computing,” 3RC initially hosted a web-based resource titled the Information Commons, which consisted of an early online directory of community-based organizations and resources. The Information Commons evolved into an effort to develop search tools and data analytics that crossed traditional and fragmented data silos, linking information from and for public sector organizations, economic development interests, and community groups.

(Notably, this early investment in the immaterial, technocratic city emerged around the same time that the early internet materialized in a physical location. In 2002, the ground floor of the former Downtown headquarters of Alcoa was converted by a public–private regional government entity (the Pittsburgh Regional Alliance (PRA)) into a “technology information hub” called the Xplorion. The Xplorion featured banks of plasma screens displaying information for visitors about Pittsburgh-specific business development, education and training opportunities, and cultural attractions. Before the smart city was conceived as an immanent part of everyday life, a version of the smart city in Pittsburgh was a showroom that one could visit on foot, and that the PRA hoped would create a “wow” factor that would appeal to businesses considering whether to locate in Pittsburgh.)

As a use case for MAYA’s technologies, 3RC itself grew in scope over fifteen years of operation, and it eventually developed and offered separate websites and software tools for both community and public sector application. 3RC not only inventoried resources across multiple sectors but also supplied tools for querying and analyzing data pools. Among its public sector partners was the Allegheny County Department of Human Services. The county’s humanservices.net domain served as a gateway to an Information Commons repository of information about daycare centers, drug and alcohol assistance, and food banks, combined with mobility and access information for citizens. As commercial search technologies and accessible databases got larger and more powerful, the case for 3RC weakened, and it wound down in 2012. Its privately owned data analytics technology for civic infrastructure had already been spun forward into a separate commercial entity.

The second was implemented within the administration of the City of Pittsburgh during the tenure of Mayor Tom Murphy in the early 2000s. The system was CitiStat, a statistics tracking and data analytics system pioneered in the City of Baltimore, Maryland. The purpose of CitiStat was to centralize data collection as to forms of citizen/community interaction (citizen phone calls about city services, pothole filling, garbage collection, and so on) and then to allocate service-based resources accordingly. The system would help rationalize the distribution of those resources and create a data-based system for employee and managerial accountability. Pittsburgh’s CitiStat system required a dedicated physical space where team members would meet to share and analyze data. The space was built, but the system did not survive the end of Mayor Murphy’s administration in 2006.

The third, serving most directly as a precursor to contemporary smart city practice, was the Pittsburgh Neighborhood and Community Information System (PNCIS), which operated from 2005 to 2014 as an initiative of the Center for Economic Development at CMU and the University Center for Social and Urban Research (UCSUR) at Pitt. Beginning in 2008, PNCIS was as an affiliate of the National Neighborhood Indicators Project (NNIP), a national network of data intermediaries organized by the Urban Institute. PNCIS was an open data initiative, collecting and cleaning datasets addressing public and community activities in Pittsburgh and making them available for public access and use, either online or via hard computer media. It was funded partly by Pitt, partly by CMU, and partly by the City of Pittsburgh, with fundraising and management support from a Pittsburgh-based community financial organization, the Pittsburgh Partnership for Neighborhood Development (PPND) and local philanthropies. But the PNCIS was not funded sufficiently for its services to meet the full range of community need, and it was not charged with supporting public sector activities as well as community organizations.

The technical and structural limitations of PNCIS were recognized and addressed in the development of a successor open data enterprise, the Western Pennsylvania Regional Data Center (WPRDC), which is supervised by the same person who led the PNCIS, Robert Gradeck. The WPRDC is the official open data repository of the City of Pittsburgh and accepts open datasets from all manner of regional governments and community organizations. It was created in 2014 via a collaboration among the City of Pittsburgh, Allegheny County, and local philanthropies. As noted earlier, a complementary open data ordinance was adopted by the City of Pittsburgh at the same time.

The impulse to collect and publish data as “indicators” of community well-being both preceded the WPRDC (and the PNCIS) and survives it. The Pittsburgh TODAY Regional Indicators project, housed separately at UCSUR, traces its origins to the mid-1990s and a regional benchmarking project initiated by the Pittsburgh Post-Gazette, the region’s principal daily newspaper. The project originated in the newspaper’s instinct to document the region’s post-steel recovery in quantitative terms. The project has been sustained through organizational and funding changes, including management by 3RC, and continues today under the leadership of one of the journalists who helped launch the project in the first place. Public sector indicators projects have been less durable. A Pittsburgh Equity Indicators report was published by the City of Pittsburgh in 2018 and updated in 2019, describing economic conditions in Pittsburgh relative to gender, race, and income.

Two additional enduring early smart city investments turn up at Allegheny County, home of the Department of Human Services mentioned earlier, and in the private real estate development community.

Allegheny County created its Data Warehouse in 1999, consolidating its own internal data relating to behavioral health, child welfare, and homeless services in order to support decision-making, improve case management, and conduct policy analysis. The Data Warehouse is, in sum, an internal management tool. (The 3RC service was in part an early public-facing interface for certain data collected in the Data Warehouse.) Later, data from other county agencies were included, and the county crossed jurisdictional lines to partner with the Pittsburgh Public Schools, an unrelated public authority responsible for all public primary and secondary education in the City of Pittsburgh; with the Allegheny County court system and the Allegheny County Jail; and the housing authorities of both Allegheny County and the City of Pittsburgh. Cooperative agreements with other government organizations enable the county to conduct trend-based data analysis that links county-level data to human services data acquired both from the state of Pennsylvania and from the federal government.

The Data Warehouse was launched as part of a larger, comprehensive reorganization of the county’s service departments, whose fragmented character was deemed to have contributed to the death of a child formerly in the charge of the county’s child protection service. Funding for the project came from Pittsburgh-based philanthropies. In expanded and modified form, it is still in use today. In 2013, with data shared by the Pittsburgh Public Schools and other school districts in Allegheny County, and in coordination with the United Way of Southwestern Pennsylvania, Allegheny County launched a “Be There” campaign addressed to public school students, premised on data-derived correlations between school attendance and the need for public services supplied by the county. (The United Way holds a large trove of data relating to demand for services provided by community organizations, as the provider of the “211” information hotline.) Since 2016, the Data Warehouse has supported DHS’s use of its Allegheny Family Screening Tool (AFST), a predictive risk modeling tool for addressing allegations of child maltreatment. The AFST uses the content of the Data Warehouse to generate a “Family Screening Score” for each call to the county’s child welfare hotline, predicting the long-term likelihood of a family’s future involvement with child welfare systems. Call center staff use the score in determining which calls to refer to investigators.

Last among these early precursors to contemporary smart city practices in Pittsburgh is real estate development. A leading Pittsburgh philanthropy funded the formation of the Green Building Alliance (GBA) in 1997 as a nonprofit organization focused exclusively on environmentally friendly building practices in the region’s commercial building sector. The GBA was the first such organization of its kind in the United States. Among the GBA’s early successes was the new David L. Lawrence Convention Center, opened in 2003, which was awarded Gold LEED certification by the US Green Building Council. That project accelerated Pittsburgh’s progress on the green building front, progress that is now linked directly to investments in smart building technology that renders the building’s energy performance more data-driven and efficient. The GBA now operates a data collection and sharing program as Pittsburgh’s “2030 District” (part of a network of “2030 Districts” around the world, a spinoff of the private Architecture 2030 advocacy organization). That program enables GBA members to collect and share data on building performance with one another and with the City of Pittsburgh.

In 2016 and again in 2019, the City of Pittsburgh added formal endorsements to these private sector efforts. The Pittsburgh Building Benchmarking Ordinance, adopted in 2016, requires owners of large nonresidential buildings to report their annual energy and water consumption to Pittsburgh. In 2019, the City of Pittsburgh adopted an ordinance that requires that all new or renovated Pittsburgh government buildings be net-zero (NZE) ready. The GBA works closely with the real estate development efforts of Pittsburgh’s Urban Redevelopment Authority (URA) and with energy planning initiatives in Pittsburgh’s commercial neighborhoods, and it partners with the CREATE Lab at CMU to develop “democratizing data” programs. Those efforts are aligned with the City of Pittsburgh’s Climate Action Plan, the first version of which was adopted in 2008. (Version 3.0 was released in 2018 following an extensive process of community engagement.) Arguably, even Pittsburgh’s legacy industrial producers are starting to get environmentally “smart” and to follow the trend toward cleaner air. In early 2021, US Steel announced that it canceled a planned $1 billion investment in emission control and production upgrades at its remaining operations in the Monongahela Valley, upriver from Downtown Pittsburgh. Instead, three batteries at the Clairton Coke Works, long the source of much of Pittsburgh’s worst particulate pollution, will be shut down. The company’s decision drew immediate and loud public recriminations from a coalition of labor unions.

Pittsburgh’s Smart City Solutions

With the inauguration of Mayor Peduto in early 2014, the pace and breadth of new and extended smart technology systems in Pittsburgh and related technology-oriented developments increased. Likewise, their salience increased both within public administration processes and in public-facing conversations about the roles of technology in Pittsburgh society. This section catalogs continuing smart city projects in Pittsburgh. The catalog illustrates both data-sharing practices as knowledge commons, in which data is collected and pooled as a shared resource, and governance-sharing practices as a distinct form of knowledge commons, in which governance techniques and strategies are combined across formal organizations. The catalog is offered here primarily for its potential utility for further research.

Key observations ease the way into presenting the catalog itself.

Smart City Accelerants and Catalysts

Critical players and contributors to the post-2014 transition came from a variety of sources. The mayor himself stands out, though the power of his administration to move forward with smart city strategies depended in part on the fact that its interest in doing so coincided with broader national and international interest in technology- and data-based public administration, the availability of relevant technology, and political and cultural transitions in Pittsburgh.

The most important of these transitions was the new administration’s decision to create a new Department of Innovation and Performance in 2014 and a new Department of Mobility and Infrastructure in 2017. “Innovation and Performance” fulfilled a campaign pledge to modernize city administration with new technologies and practices. It is both a service center for other City of Pittsburgh departments and a coordinator of relationships with technology vendors and academic partners. Its inaugural director, Debra Lam, served in Pittsburgh until 2017, when she left to become Managing Director, Smart Cities and Inclusive Innovation at the Georgia Institute of Technology (Georgia Tech). “Mobility and Infrastructure” (DOMI) grew out of the priority assigned to modernizing Pittsburgh’s transit and transportation systems in connection with the city’s economic development goals.

Mayor Tom Murphy, who served the City of Pittsburgh between 1994 and 2006, was similarly inclined toward the uses of data and technology. But his constituency was not prepared to support a technocratic vision of Pittsburgh government, and the relevant technology was in its infancy, comparatively speaking. Murphy’s successor and Peduto’s predecessor, Luke Ravenstahl, exhibited little enthusiasm for a technology-first approach. Municipal finances compounded political and ideological barriers. In 2003 the City of Pittsburgh designated itself “distressed” under Act 47, the rough equivalent of municipal insolvency under Pennsylvania law. Tax reform and restructuring Pittsburgh’s pension system were high priorities. Pittsburgh exited Act 47 status in 2018.

Political leadership played only one role in the shift toward a more aggressive embrace of smart technologies. Pittsburgh’s smart city deployments emerged and continue to operate as complex combinations of contributions from the public sector, the philanthropic sector, local universities, private technology companies, and occasional key interventions by specific individuals. Pittsburgh’s institutional and organizational resources were summarized earlier. Additional resources partly constitute a loose network of cultural capital and partly enhance Pittsburgh’s pool of smart city expertise directly.

At the micro level, individual actors have at times played important parts in building and sustaining Pittsburgh’s contemporary technology practices. Their contributions can be traced partly to their institutional identities or affiliations and partly to their personal and professional mobility from role to role and sometimes from sector to sector, as catalysts, relationship builders, and endorsers. For example, the Allegheny County Data Warehouse was launched as part of a large reorganization of service provision by the county that included the creation of the Department of Human Services itself. The reorganization was recommended by a blue ribbon commission led by John Murray, president of Duquesne University, former dean of the law schools at both Duquesne and the University of Pittsburgh, and a widely respected community presence. The early success and longer durability of the Data Warehouse is credited both to the director of that department, Marc Cherna, and to the talent of the person later hired to expand and extend it, Erin Dalton. The success of the Western Pennsylvania Regional Data Center is partly attributable to the efforts of its director, Robert Gradeck, who helped to found and operate its predecessor organization, PNCIS, as a staff member at CMU’s Center for Economic Development. The smart cities partnership between the City of Pittsburgh and Carnegie Mellon University leaned on the experience of Richard Stafford, who directed the launch of Traffic21 in 2009 and Metro21 in 2014 and who served as the Chief Executive Officer of the ACCD from 1990 to 2003. Key individuals at Pittsburgh’s three leading philanthropic organizations have played important roles from time to time in brokering new institutional designs in Pittsburgh’s uses of public technology.

At the macro level, the City of Pittsburgh taps relationships with Results for America, a national nonprofit supporting data-based public administration and funded by Bloomberg Philanthropies; the Operational Excellence initiative and the Government Performance Lab at Harvard University, part of the Ash Center for Democratic Governance and Innovation at Harvard’s Kennedy School; and the Center for Government Excellence (GovEx) at Johns Hopkins University. Pittsburgh public administrators have been active in the Civic Analytics Network, a cohort of public data officers hosted by Harvard’s Ash Center. Metro21 at CMU spawned the MetroLab Network, a network of city–university partnerships, in 2015, as part of the White House Smart Cities Initiative.

A Smart City Catalog

Six tables of smart city initiatives in Pittsburgh follow, representing a portrait of contemporary Pittsburgh as a smart city disassembled into many of its constituent parts.

Any catalog inevitably raises classification and clustering challenges; here, those challenges are compounded by the fact that this chapter takes smart city practice to include a broad range of systems and practices. Lots of things count as smart city-related initiatives in Pittsburgh for my purposes, in the sense that lots of things are worth examining in greater detail as cases of knowledge commons governance. But they count in different respects. The classifications used below are provisional. The knowledge commons governance in evidence may be sorted differently by other researchers.

Table 6.1 lists resources and systems that constitute all or parts of smart city infrastructure. These are mostly technical systems for network connectivity and data storage, which offer the means to collect data, to combine or pool data, to access data, or some combination of the three.

Table 6.1.

Infrastructure

Item	Sector	Technology or system	Initiators, providers, funders	Date launched	Notes (purposes, legal frameworks, outcomes)
1	Connectivity – broadband	Connectivity Improvement Plan for the Western Pennsylvania region	Southwestern Pennsylvania Commission; Metro21 and Traffic 21 at Carnegie Mellon University; and Allies for Children (a Pittsburgh nonprofit funded by the United Way, among other grantors)	Announced in 2021	Map, gap analysis, and strategic plan intended to guide improvement of regional broadband connectivity in relation to demographics, socioeconomic conditions, educational, health care, and business needs.
2	Connectivity – networking	NetPGH	City of Pittsburgh Department of Innovation and Performance and a proposed commercial vendor	Announced in 2020	Initiative intended to support single-provider fiber connectivity network among city facilities.
3	Storage	Google Cloud	City of Pittsburgh Department of Innovation and Performance and Google Cloud	Contract awarded in 2020	Project that migrates to Google Cloud existing applications and datasets (including the city’s website, its GIS data, its permitting system, and its security camera system) from on-premises VMWare storage.
4	Devices	Computer hardware and related systems	City of Pittsburgh Department of Innovation and Performance; Dell Technologies	2019	The City of Pittsburgh selected a single vendor to supply and upgrade desktop, laptop, and mobile devices with the expectation that they would be used by City employees in implementing smart city programs, such as the Snow Plow Tracker (Table 6.2, item 1) and the Rec2Tech program (Table 6.5, item 1).
5	Analytics	City Performance Tool (CyPT)	City of Pittsburgh Office of Sustainability; Siemens; the Green Building Alliance, the Hillman Family Foundations, Carnegie Mellon University, the University of Pittsburgh, regional utility suppliers, and the National Energy Technology Laboratory (NETL, with a site located in Pittsburgh)	Partnership announced in 2017; report produced in 2019	The tool supports decision-making as to physical infrastructure in the public sector, focused on carbon dioxide emissions associated with energy generation, building design, transportation, and economic development.
6	Management – organization and service delivery	Information Technology Infrastructure Library (ITIL) training and certification in best practices in information technology (IT) services	City of Pittsburgh Department of Innovation and Performance; Axelos (a commercial provider of training and certification standards for best practices methods in IT services); New Horizons (a commercial provider for ITIL training)	2018	ITIL training was introduced to improve and systematize and integrate IT operations and service delivery across City of Pittsburgh departments and to city residents.
7	Platforms – open data	Western Pennsylvania Regional Data Center (WPRDC), hosting datasets including data generated via the City of Pittsburgh and Allegheny County	Heinz Endowments (funder); Allegheny County (grantee); City of Pittsburgh (grantee); University of Pittsburgh (grantee, host, and funder)	2015	With respect to the City of Pittsburgh, the WPRDC fulfills the city’s obligation by ordinance adopted in March 2014 to provide public access to municipal datasets. With respect to other public bodies, particularly Allegheny County, the WPRDC makes available certain datasets that in the judgment of the WPRDC adequately protect privacy interests of data subjects. The WPRDC also engages with local and national community organizations in developing and distributing open datasets and providing data literacy education, notably the National Neighborhood Indicators Partnership (NNIP) and the Black Equity Coalition.
8	Datasets – data pools	Allegheny County Data Warehouse	Allegheny County Department of Human Services (DHS) (host); the Human Services Integration Fund (a coalition of Pittsburgh foundations) (funders); the Allegheny County Office of Data Analysis, Research, and Evaluation (manager)	2000	The Data Warehouse and the DHS itself were elements of a large-scale restructuring of Allegheny County government and services recommended by a volunteer-based blue-ribbon commission, the Independent Committee to Review Allegheny Children and Youth Services, aka the Murray Commission.
9	Decision-making tools – data dashboards (public-facing) and complementary dashboards (internal to the City of Pittsburgh)	Burgh’s Eye View dashboards and visualizations; Dashburgh	City of Pittsburgh Department of Innovation and Performance	Burgh’s Eye View: 2016 Dashburgh: 2021	Burgh’s Eye View map-based dashboards are created from data generated by 311 requests for city services, public safety information, building information, city resource inventory, tax delinquent properties, and traffic signal information. Dashburgh, a dashboard for accessing dashboards, was launched in December 2021.
10	Decision-making tools – digital twins	Virtual twin dataset	City of Pittsburgh; Allvision (a technology startup based in Pittsburgh)	2020	Allvision participated in the PGH Lab program (item 15 below) and piloted a virtual twin program to create an inventory of City of Pittsburgh streetlights (used both for lighting and telecom infrastructure), using LIDAR and GPS technology.

Item	Sector	Technology or system	Initiators, providers, funders	Date launched	Notes (purposes, legal frameworks, outcomes)
11	Decision-making tools – mobility and accessibility	AgileMapper	Various municipalities in Western Pennsylvania	2016	AgileMapper is supplied by RoadBotics, a Carnegie Mellon University spinout company that offers technology for producing mapped visual asset data of a community’s physical assets, primarily road conditions (degraded streets, including potholes), by distributing data collection in a smartphone app.
12	Decision-making tools – land banking	Land Bank	City of Pittsburgh Urban Redevelopment Authority (URA)	2014	The Pittsburgh Land Bank was created as an independent municipal agency in 2014 to inventory roughly 11,000 parcels of vacant, abandoned, and distressed real estate and return it to productive use. The program has largely failed to meet its goals, in part because many parcels are burdened with tax liens owned by other government entities, and in 2021 it was moved into the URA, a long-standing municipal agency charged with coordinating economic development activity based on publicly owned real estate. Pittsburgh efforts to compile data regarding vacant and abandoned property date to 2000 and include community efforts coordinated through the University of Pittsburgh Community Outreach Center (COPC) and the Pittsburgh Community Reinvestment Group’s Vacant Property Working Group. Those efforts later merged into the formation of the Pittsburgh Neighborhood and Community Information System (PNCIS), founded by CMU and the University Center for Social and Urban Research (UCSUR) at the University of Pittsburgh. Public and community efforts to manage Pittsburgh’s vacant land also include the Vacant Lot Toolkit (2015) and the related Adopt-A-Lot Ordinance, adopted by the City of Pittsburgh; and investments of time and volunteer expertise by community organizations that include Tree Pittsburgh, Grow Pittsburgh, the Pittsburgh Greenspace Alliance and the Western Pennsylvania Conservancy, a public/private partnership.
13	Decision-making tools – waste management	Smart trash cans	City of Pittsburgh Department of Public Works	2019	The City of Pittsburgh deployed 1000 smart trash cans equipped with sensors to indicate their quality of functionality (damaged, afire) and level of fullness.
14	Decision-making tools – wastewater and stormwater management	Sewer line and tunnel inspection via the RedZone Solo robot and Multi-Sensor Inspection (MSI) systems	City of Pittsburgh and Pittsburgh Water & Sewer Authority; ALCOSAN (Allegheny County Sanitary Authority); RedZone Robotics (a technology startup based in Pittsburgh)	2014	RedZone Robotics is a Carnegie Mellon University spinoff company.
15	Technology development	PGH Lab	City of Pittsburgh Department of Innovation and Performance	2016	The City of Pittsburgh operates this incubator for Pittsburgh-based smart technology companies to develop technology for piloting in the City of Pittsburgh and other local authorities. Priority for admission to the incubator is given to firms owned by members of underrepresented communities.

Table 6.2 lists resources for providing citizen access to public decision-making processes, via one or more technological means. These include mobile applications for requesting public services or public information; technology platforms that provide levels of transparency with respect to public administration processes; and technology-reliant systems for soliciting community input into public decisions.

Table 6.2. Citizen access to public processes

Item	Sector	Technology or system	Initiators, providers, funders	Date launched	Notes (purposes, legal frameworks, outcomes)
1	City-provided public services	Citizen apps	City of Pittsburgh	Various	Citizen-facing app-based information about public services includes: Snow Plow Tracker; PGH.st (trash schedule); Snow Angels (crowdsourced community-based snow removal); One Stop PGH (integrating information about planning applications and building permits, code enforcement, and business licensing); and CivicCentral (formerly BuildingEye) (database access for the City of Pittsburgh Department of Permits, Licenses, and Inspections). Citizen-facing app-based payments systems include mechanisms regarding: parking tickets and parking leases (in municipal garages and lots), and OneTaxPGH (business and real estate taxes). Citizen-facing app-based registration systems include mechanisms for: fire/burglar alarms and public facility use. Citizen-facing app-based data input mechanisms include: PGH Watchdog (for submitting claims about waste and theft of city property and services, supplementing the 311 system for submitting citizen requests for service); and Engage PGH (dashboard of city-sponsored planning projects soliciting public input).
2	Government procurement	Beacon	City of Pittsburgh Office of Management and Budget (host); Code for America (technology development); the R. K. Mellon Foundation (funder)	2016	Beacon and the Beacon website consist of a public-facing database of public contracts and Calls for Bids (CFBs).
3	Municipal finance	Open Book Pittsburgh	City of Pittsburgh Office of the City Controller	2009	Open Book Pittsburgh consists of a database and dashboard providing information regarding municipal contracting, campaign finance contributions and expenditures, lobbyist identities, and financial disclosures by public officials.
4	Municipal finance	Fiscal Focus Pittsburgh	City of Pittsburgh Office of the City Controller	2015	Database and dashboard providing information regarding municipal budgeting and payments.
5	Citizen input into government decision-making	Potholes and Pierogies	City of Pittsburgh Mayor’s Office of Community Affairs	2018	The City of Pittsburgh organized deliberative forums for residents on the city’s capital budget, hosting the events in neighborhoods and at times intended to maximize access. The name “Potholes and Pierogies” is both a reference to the dinner menu and a nod to the many Pittsburghers descended from immigrants.
6	GIS data; physical infrastructure	Who Owns My Infrastructure?	Allegheny County Geographic Information Systems (GIS) Team	2018	The website consists of a data visualization that uses Allegheny County GIS data and data from the WPRDC (Table 6.1, item 7), and the Pennsylvania state Department of Transportation and Department of Environmental Protection.
7	Public health	Opioid Overdose Dashboards	City of Pittsburgh Department of Public Safety; Allegheny County Health Department (separate dashboards)	2021	The City of Pittsburgh dashboard compiles data from EMS service calls for opioid overdoses on a monthly basis and maps that data to demographic and neighborhood-level information. The Allegheny County dashboard relies on overdose death data from the Allegheny County Office of the Medical Examiner (ACOME), Emergency Departments, and EMS agencies.

Table 6.3 lists technology-based systems for collecting data about citizen behaviors and community resource conditions, many of which recirculate that data into decision-making processes within public administration systems.

Table 6.3. Public ICTs for citizen utility

Item	Sector	Technology or system	Initiators, providers, funders	Date launched	Notes (purposes, legal frameworks, outcomes)
1	Mobility and accessibility	Surtrac	City of Pittsburgh Department of Mobility and Infrastructure; Carnegie Mellon University (initial technology partner); Rapid Flow Technologies (a technology startup based in Pittsburgh)	2012	Surtrac technology for traffic control via smart traffic signals was developed at Carnegie Mellon University, piloted in the City of Pittsburgh, and later spun out into a private company, Rapid Flow Technologies. Rapid Flow Technology has expanded its partnership by deploying the technology elsewhere in the City of Pittsburgh as part of a city-led “Smart Spines” project for traffic flow along several priority corridors. The City of Pittsburgh also receives aggregated traffic flow data from the private mobility company Waze and from the I-95 Corridor Coalition Traffic Flow Data Program.
2	Mobility and accessibility	Sidewalk accessibility	City of Pittsburgh Department of Mobility and Infrastructure; Port Authority of Allegheny County (a county authority); Pittsburgh Parking Authority (a municipal authority); University of Pittsburgh (initial technology partner); pathVu (technology partner)	2017	pathVu is a commercial company spun out of the University of Pittsburgh that collects data about sidewalk conditions via both crowdsourced and automated inputs. The company was a member of the PGH Lab program (Table 6.1, item 15).
3	Mobility and accessibility	Parking	City of Pittsburgh; Pittsburgh Parking Authority; Parkmobile (a national technology company, vendor to City of Pittsburgh); Meter Feeder (a technology startup based in Pittsburgh, vendor to the City of Pittsburgh and other municipalities in the region)	2014	Coin-operated parking meters throughout the City of Pittsburgh were replaced by digital kiosks, accessible by smartphone; payments are managed through Parkmobile, a commercial vendor, and Meter Feeder, a Pittsburgh-based rival. The Pittsburgh Parking Authority uses license plate recognition equipment on roving vehicles to monitor parking in the City of Pittsburgh. Meter Feeder also provides parking payment services to other Pittsburgh-area municipalities.
4	Mobility and accessibility	Pitt Smart Living Project	University of Pittsburgh	2019	University of Pittsburgh researchers used funding from the National Science Foundation and a partnership with Walnut Capital (a private real estate developer) to develop facilities that supply data to public transit users, combining data from the Port Authority of Allegheny County, public weather data, and information about crowding in stores and other places obtained from Google Place). The purpose of the project is to encourage prosociality and to reduce public transit congestion by combining and sharing information about transit use with information about business resources (inventory, time-sensitive pricing).
5	Mobility and accessibility	Move PGH	City of Pittsburgh Department of Mobility and Infrastructure; Port Authority of Allegheny County; private micromobility providers (technology partners); R. K. Mellon Foundation (funder)	2021	Move PGH is the product of a community convening begun in 2019 titled the Pittsburgh Micromobility Collective (“Mobiliti”). The initiative centers on a “Mobility as a Service” (“MaaS”) pilot project and includes the “Transit” app and Ready2Ride, systems that permit City of Pittsburgh residents to pay bus fares, rent micromobility vehicles such as electric bikes and scooters, find carpool partners, and rent vehicles for short-term use. Private micromobility partners are given exclusive operating rights in the city for two years and will maintain fifty “mobility hubs” near existing transit stops to support electric bikes and scooters, including real-time light rail and bus information on digital screens. State law was amended to permit e-scooters to operate under the motor vehicle code. The Port Authority distributes real-time route and schedule data via TrueTime and Bus Tracker applications.

Table 6.4 lists systems for “smart” decision-making by public authorities, consisting mostly of algorithmic processes that rely on data from a variety of sources. The line between “data governance” and “algorithmic decision-making” is fine and, in practice, possibly nonexistent.

Table 6.4. Public ICTs for data-based decision-making

Item	Sector	Technology or system	Initiators, providers, funders	Date launched	Notes (purposes, legal frameworks, outcomes)
1	Public safety and policing	Automated License Plate Readers	Allegheny County District Attorney; OpenALPR (technology provider)	2017	Community concern about the ALPR systems in Pittsburgh and the unsupervised use of the systems by the Allegheny County District Attorney was raised in 2019 in Pittsburgh media, by national civil liberties organizations, and in the state legislature.
2	Public safety and policing	Surveillance cameras	Allegheny County District Attorney and the Allegheny County Chiefs of Police Association	2017	County officials and police departments outside the City of Pittsburgh installed a network of security cameras in fifty locations, including in some City of Pittsburgh neighborhoods, to capture footage potentially relevant to street crime.
3	Public safety and policing	Pre-trial Risk Assessment Tool	Allegheny County Municipal Court	2016	A unit of the court makes recommendations regarding pre-trial release conditions for criminal defendants. The recommendation relies on a risk score, which is determined by a risk assessment tool and based on personal interviews and other information.
4	Public safety and policing	ShotSpotter	City of Pittsburgh Bureau of Police; ShotSpotter (technology provider)	2018	ShotSpotter technology uses acoustic sensors to identify and characterize gunfire and automatically notify emergency responders via the 911 service.
5	Public safety	Pedestrian Safety Action Plan	City of Pittsburgh Department of Mobility and Infrastructure	Plan released 2021	The plan proposes to conduct data-based Road Safety Audits to analyze and treat areas of historical and predicted pedestrian crashes.
6	Public health – family welfare	Allegheny Family Screening Tool (AFST)	Allegheny County Department of Human Services; R. K. Mellon Foundation (funder)	2016	The AFST is a predictive modeling tool designed to improve child welfare screening decisions. The AFST relies on the data collected in the Allegheny County Data Warehouse (Table 6.1, item 8).
7	Public health – child welfare	Hello Baby	Allegheny County Department of Human Services; various nonprofit organizations (partners); the Heinz Endowments (funder)	2020	Hello Baby is a data-based tiered prevention model for allocating public health and child support resources on a voluntary basis to families with children under age three. Hello Baby relies on data collected in the Allegheny County Data Warehouse (Table 6.1, item 8).
8	Education	Be There	Allegheny County Department of Human Services; University of Pittsburgh; United Way of Southwestern Pennsylvania; Pittsburgh Public Schools; Congress of Neighboring Communities (twenty other public school districts in Allegheny County); Allegheny County Intermediate Unit; various philanthropies and nonprofits, including Allies for Children	2013	Public school districts in Pennsylvania are separate from municipal and county authorities. Be There was a public campaign to encourage school attendance developed as a result of a voluntary data-sharing partnership established initially in 2011 between Allegheny County and the Pittsburgh Public Schools, with encouragement from the United Way of Southwestern Pennsylvania. Data from the Pittsburgh Public Schools and other school districts regarding attendance records and academic outcome data were combined with data on service provision to children, in the Allegheny County Data Warehouse (Table 6.1, item 8). Related voluntary data sharing among public school districts in Southwestern Pennsylvania is coordinated by the Remake Learning network, a nonprofit organization.
9	Environment	Air Quality Forecast and Dispersion outlook report	Allegheny County Health Department	2018	This dashboard was a relaunch of an existing resource, now anchored in Allegheny County Mon Valley Air Pollution Episode regulations. Air quality in Allegheny County has been a source of long-standing public and community concern, going back well over 100 years. Contemporary community activism dates to the formation of GASP (Group Against Smog and Pollution) in 1969 and now includes the Breathe Collaborative of nonprofit and research organizations and philanthropies.
10	Environment	Street Tree Inventory	Western Pennsylvania Conservancy (a public/private partnership); Tree Pittsburgh; City of Pittsburgh Department of Innovation and Performance; the Pittsburgh Shade Tree Commission; UrbanKind Institute; Carnegie Mellon University	2014	This inventory is part of the TreeVitalize Pittsburgh project and includes a Street Tree Management Plan, an Equitable Street Tree Investment Strategy, and an iTree Eco Analysis.
11	Environment	Trees N’At	City of Pittsburgh	2018	A web-based mapping application built by the Department of Innovation and Performance, using satellite imagery to document the locations of all of Pittsburgh’s street and park trees. The mapping application is linked to tree inventory data maintained by the Forestry Division of the Department of Public Works, stored in a Cartegraph database along with inventories of other city assets: city facilities, bridges, pools, playgrounds, rinks and fields, signs, crosswalks, and other geographic data. The datasets are shared via the WPRDC.
12	Food security	Optimizing food delivery via community organizations	Carnegie Mellon University; United Way of Southwestern Pennsylvania; Allegheny County Department of Human Services; Penn Hills School District; Municipality of Penn Hills; Greater Pittsburgh Food Bank	2020	This pilot project optimized bus routes for delivery of free breakfast and lunch to students in Penn Hills, a Pittsburgh suburb, by using anonymized data from the Allegheny County Data Warehouse about students and families receiving food services. The project built on an earlier effort to use student location data to optimize daily transportation services for children attending schools in Allegheny County.

Table 6.5 lists areas where technology development and deployment are parts of Pittsburgh’s public sector engagement with smart city strategies in unusual or unorthodox respects: recreation and education, on the one hand, and economic development in the private sector, on the other.

Table 6.5. Public support of ICTs in education and business

Item	Sector	Technology or system	Initiators, providers, funders	Date launched	Notes (purposes, legal frameworks, outcomes)
1	Culture, recreation, and sociality	Rec2Tech	City of Pittsburgh; Comcast; Remake Learning (a Pittsburgh nonprofit); national and local philanthropies (funders)	2016	Public recreation facilities in the City of Pittsburgh host technology (STEM) learning events for young people. The program continued in 2020 with a grant from National Science Foundation to support Rec2Tech centers in Pittsburgh and Baltimore.
2	Economic development	Autonomous vehicle development	City of Pittsburgh Office of the Mayor; Uber, Argo, Aurora, Motional, Waymo (companies developing autonomous vehicle technology)	2016	Mayor Bill Peduto welcomed autonomous vehicle development and testing in the City of Pittsburgh by Uber and other firms in 2016 as part of an economic development strategy to attract robotics firms to the city. Pennsylvania law put no regulatory restrictions on self-driving cars on public streets. Following accidents involving Uber vehicles in other locations, Uber’s failure to demonstrate public benefits associated with use of its autonomous vehicles or expansion of its business, and Uber’s eventual exit from the autonomous sector, the mayor and the City of Pittsburgh suspended their embrace of autonomous vehicles on public streets and shifted to supporting real estate development at the site of a former steel mill, where autonomous vehicles could be tested on a private track. Labeled “Hazelwood Green,” the project attracted public criticism because it required public subsidies for transit links between the site and the campuses of Carnegie Mellon University and the University of Pittsburgh. Building those links would disrupt an existing low- and middle-income neighborhood.

Table 6.6 lists instances of smart city practice in Pittsburgh that emanate in the first place from community engagement with community needs, in identifying problems and developing data- and technology-development strategies as governance solutions.

Table 6.6. Community data production

Item	Sector	Technology or system	Initiators, providers, funders	Date launched	Notes (purposes, legal frameworks, outcomes)
1	Housing	Eviction Rapid Response	Carnegie Mellon University; RentHelpPGH (partner); Heinz Endowments (funder)	2020	The project was developed in the CREATE Lab at Carnegie Mellon University (Community Robotics, Education and Technology Empowerment Lab), part of the Robotics Institute at CMU. Volunteers scrape local court websites to gather information about eviction filings and hearings, using the data to advise tenant and link them to community resources via the RentHelpPGH project and platform.
2	Environment	Smell PGH	Carnegie Mellon University; various regional and state nonprofits (partners); Heinz Endowments (funder)	2016	The project was developed in the CREATE Lab at Carnegie Mellon University. The app enables residents of Allegheny County to submit reports related to pollution odors.
3	Environment	Light Pollution Map	Pittsburgh section of the Pennsylvania chapter of the International Dark-Sky Association (IDA) and Carnegie Mellon University. Street light upgrades are being advanced by the City of Pittsburgh Department of Mobility and Infrastructure	2017	Pollution mapping was undertaken by aerial surveillance. In 2018, the City of Pittsburgh solicited bids for upgrading its inventory of streetlights with “smart” LED lights but abandoned the project because the city lacked the ICT infrastructure to support light fixtures as networked devices. In May 2021, Pittsburgh issued a call for proposals to upgrade all of its streetlights to non-networked LED fixtures. The City of Pittsburgh enacted a Dark Sky Lighting ordinance in August 2021. Pittsburgh’s review of the effects of streetlights includes observations in 2010 by CMU’s Remaking Cities Institute of glare emitted by early LEDs.
4	Civic technology	Community groups and projects that have focused on technology development for the civic sphere	Volunteers supported in part by the City of Pittsburgh, Urban Redevelopment Authority, Google, local philanthropies, and Civic Champs, a volunteer management software platform	2013	Volunteer-based organizations come and go, sometimes coalescing into formal nonprofit organizations and sometimes fading with the exit of key volunteers. A partial inventory of Pittsburgh civic technology groups includes Code for Pittsburgh (Pittsburgh’s cohort in Code for America), Steel City Codefest, Remake Learning, and Google Civic Innovation.
5	Social justice	Data 4 Black Lives	Volunteers led by graduate students at CMU	2020	Pittsburgh-specific hub of a national nonprofit organization, Data 4 Black Lives (D4BL), that aims to identify and eventually abolish uses of Big Data systems that disproportionately affect Black residents and other people of color.

Evaluation and Implications

The GKC framework calls for evaluation of knowledge commons governance cases but doesn’t specify particular standards or metrics. The following discussion draws out certain salient themes, focused in part on smart city governance themes and in part on knowledge commons themes. Inevitably, the discussion emphasizes questions for further research at least as much as it describes Pittsburgh’s smart city failures, successes, challenges, and opportunities.

Does It Work?

The first and immediate question posed by any knowledge commons system and thus by a smart city governance system is whether it works. Does the system do what it is intended to do? What is it designed to do? What are its expected and unexpected costs and benefits, over different time scales? Does the system solve the problem that it is intended to solve, and does it solve a problem that needs to be solved? Does it create further problems either within its context or sector or by triggering spillover impacts elsewhere? These are not problems of knowledge commons governance or smart city technology as such. They are questions to be asked with respect to any institutional governance arrangement, and often to be asked in comparative context. How does the system work compared to one or any other actual or possible system?

Here, judgments are necessarily incomplete. Smart city practice may be motivated and influenced by ideals of effective and efficient governance, by conscious and subconscious idealization of technocratic control of urban spaces, and/or by the quest for better lives for city residents. On the ground, the question concerns the pragmatics of balancing individual and community interests, demands, and goals with available time, expertise, and material resources.

Pittsburgh’s smart city governance is flawed at least in part in the sense that some data-driven systems have been pursued or deployed without adequate consideration being given to the need to invest in complementary technologies or labor to sustain them, particularly in a highly decentralized technical configuration. Labor and expertise demands have been revealed both with respect to data analytics, statistics, and network engineering and also with respect to field-based technicians. Asking garbage collectors to carry mobile tablets to record images of potholes means reconfiguring how garbage collectors are trained and how garbage trucks are crewed. Smart street lights can’t necessarily be maintained by the same technicians who maintained older street lights.

Most of Pittsburgh’s smart city systems are too new to have been subjected to much independent review of their efficacy or effects. The Allegheny County Department of Human Services has allocated resources to producing products that assess its uses of data analytics, which are thoughtful but which are not designed to undertake comprehensive comparative institutional analysis.

Emerging descriptive research has been directed to sector-specific uses of data and algorithms in Pittsburgh governance, focusing on land use (Ghosh, Byahut, and Masilela 2019) and the origins of Metro21 at CMU (Preis 2019). Some interviewees acknowledged that Pittsburgh’s use of citizen-facing technologies such as dashboards has been more complete and effective than its use of data for internal decision-making. The WPRDC is widely known in Pittsburgh and elsewhere as a model of an open data institution, but it has engaged in relatively little community outreach in Allegheny County. As noted earlier, critical approaches mostly focus on the Allegheny County AFST (Eubanks 2019) and on the uses of algorithms in public decision-making in Allegheny County.

Looking at smart city governance as an element of Pittsburgh’s broader turn toward technology-driven economic development, the evidence of impact is mixed, both for better and for worse, and mostly incomplete. As with many cities, Pittsburgh often focuses on metrics that are at best imprecise, such as total dollars invested in private sector technology companies and the aggregate number of associated jobs, and at worse misleading. It is plausible to hypothesize that recent developments in Pittsburgh’s reliance on technology-based firms, and Pittsburgh’s interest in an “innovation economy,” have grown despite rather than because of coordinated or planned efforts to advance such a technocentric vision.

Experts and Expertise

Commons governance of all sorts, but especially knowledge commons, leans heavily on questions of boundaries and boundary making. Because both knowledge resources and governance resources are largely immaterial, the character of resource boundaries – including organizational and community boundaries – involves historical accident as well as institutional design, public policy choice, and logical or conceptual clarity. What Sassen refers to as borderlands are often the most interesting and important governance topic to explore (Sassen 2001). Few borderlands questions are as fraught, conceptually or empirically, as the question of experts and expertise in collective, community governance. The history of research science and scholarly communications, perhaps the canonical examples of knowledge commons governance through time, illustrates precisely how the role of experts and expertise has to be explored carefully in the context of broader social and community goals (Boyle 2006; Kuhn 1996).

The key conceptual point, to be developed through further research, is that people working with data are almost of necessity members of functional expert communities, practicing an emergent form of knowledge commons. Community boundaries are necessarily porous; community membership is necessarily fluid. Expertise in the smart city, including Pittsburgh’s smart city, is a process of becoming, not a state of being.

The Pittsburgh smart city experience makes clear the roles of both technical expertise as to data and information technology and public policy expertise as to the uses of data in public administration and community engagement. It makes clear that those roles did not always predate the development and deployment of a range of smart city systems and strategies. Roles and their responsibilities grew and evolved over time, and the people themselves moved about the system for a variety of reasons.

Community-based expertise of this sort appears to be the hinge that distinguishes exploration of smart city practice as knowledge commons from the premise that knowledge commons governance proceeds from nuanced understanding of the role of openness in a resource management system. An emphasis on expert knowledge and expert networks, long a creature of Progressive politics (and thus dating to Pittsburgh’s earliest efforts to acquire data about itself), is in tension with that premise. As criticism of the Progressive Era makes clear, prioritizing expertise in governance of public institutions raises questions concerning democratic legitimacy that need to be parsed carefully (Hofstadter 1955). Even expert networks can be more or less open; the Pittsburgh smart city experience teaches that participating in smart city governance may require little more than volunteering some time, as in the community-based odor detection application called Smell Pittsburgh.

Pittsburgh’s expertise network is fluid enough that it is far from limited only to graduates of CMU and Pitt. But mid-level staff professionals advancing smart city initiatives in the City of Pittsburgh during the Peduto administration possess, at the least, master’s degrees.

In sum, if one of the goals of knowledge commons governance and related research is to understand how to advance overlapping goals with respect to improving the quality of knowledge resources and knowledge governance, then researchers need to carefully unpack questions of hierarchy and influence, communications patterns, legitimacy, authority, reliability and trust, accountability, and transparency. Those are all values associated with relevant expertise as such and in collective settings (Abbott 2001). And researchers need to pursue those questions while carefully separating them from questions of elite status or political, economic, or cultural power (Latour 1988). In what respects are knowledge-sharing strategies imposed on the broad Pittsburgh community? In what respects is the broader community even aware of the existence of those strategies, let alone given an opportunity to voice their participation in governance strategies, by voting or otherwise contesting them? In Pittsburgh, the questions of power and elite status, and presumptive exclusion of the broad community from decisions about community welfare, were more clearly in evidence earlier in Pittsburgh’s twentieth-century experience. In the twenty-first century, the cultural authority of entitled elites has receded somewhat, but it finds echoes in the persistent influence of Pittsburgh’s largest philanthropic organizations and in the thick partnerships between Pittsburgh’s public sector and its research universities.

Hidden Intelligences

What’s missing in this account? Even a broad focus on the smart city risks missing important attributes of knowledge governance in the urban experience. In Pittsburgh, that means medicine. Undoubtedly the largest and most socially impactful contemporary data-sharing practice in Pittsburgh is not part of Pittsburgh’s smart city inventory. It is a data-sharing agreement begun in 2016 between UPMC Health Systems, the region’s largest clinical health care provider; the University of Pittsburgh, which houses a health sciences research program across six separate professional schools that is funded with close to $1 billion annually in US federal research sponsorship; and CMU, one of the world’s leading research universities with respect to computer science. This Pittsburgh Health Data Alliance, which now also partners with Amazon Web Services (AWS), feeds clinical care data from UPMC to the Alliance’s combination of medical, biomedical informatics, and computer science research communities. State-of-the-art machine-learning power is directed to developing precision medicine therapies based on nearly thirty years’ worth of clinical data. The relatively low population movement historically associated with Western Pennsylvania means that UPMC stores richer longitudinal data based on patient care than most of its peers in other US regions.

Within the medical research community, this is a highly unusual program, with extraordinary practical potential payoffs and also extraordinary ethical complexity. Outside of the medical research community, however, it is, to an even greater degree than the AFST, out of view of the broader Pittsburgh community. The only community health experience in Pittsburgh of comparably broad impact was the development and testing of the polio vaccine during the early 1950s. Thousands of Pittsburgh children accepted shots in their arms, a collaborative, public undertaking of a distinctly material and immaterial sort that Pittsburgh is proud to share and celebrate as a community triumph (Greidanus 2010). The Pittsburgh Health Data Alliance operates almost entirely and solely as a function of the community of medical experts.

Conclusion: The Future of the Smart Postindustrial City and the Uses of Knowledge Commons

The smart city presents different stories about whether cities and their residents should care about being “smart.” This chapter has addressed one specific US city, Pittsburgh, Pennsylvania, as a case study of how those different stories are represented on the ground. The chapter takes the Governing Knowledge Commons research framework as its essential organizing device. The GKC framework draws out the shareable and shared character of the immaterial resources – the multiplicity of knowledge, information, and data resources that lie at the heart of what it might mean for a city to be “smart” – and connects them to the contingent immaterial and material resources that are often more commonly associated with the city – geography, culture, and history.

The Pittsburgh case study teaches that smart city data is only one immaterial feature governed as a complex, shared resource. Governance techniques and expertise themselves also constitute important immaterial shared knowledge features of the smart city. Pittsburgh further teaches that the smart city isn’t necessarily the new, bright, futuristic phenomenon described by some promoters. The smart city may be inextricably linked to attitudes and cultural patterns of long standing. In governance terms, Pittsburgh as a twenty-first-century smart city in formation bears a strong resemblance to Pittsburgh as a twentieth-century steel-making powerhouse. Whether Pittsburgh was “smart” 100 years ago is no more significant, however, than whether Pittsburgh is “smart” today. The GKC framework exposes both historical and contemporary context for urban governance.

The idea of the city has been linked for centuries with three key overarching metaphors. Two of these – the city-as-machine and the city-as-living-organism – are often used in different ways as baselines for evaluating smart cities. Both of these have long and respected histories. The history of machine-based, techno-utopian dreams of administrative and social efficiency runs from the present day (Goldsmith and Crawford 2014), through the Progressive Era (Caro 1974), and to antiquity (Scott 2017). A counter-narrative, featuring cities as naturalistic organisms or ecologies, runs essentially as long (Frug 1999; Mattern 2021; O’Mara 2007). There is also a notable history of efforts to meld the two metaphors in analysis and practice, via what one historian called Buckminster Fuller’s “cybernetic pastoral” (Massey 2006).

Often overlooked in that debate is a third grand metaphor with ancient roots: the city as spiritual – and therefore immaterial – ideal (Mumford 1961; Rykwert 1976). This perspective draws out subtle but critical contrasts with respect to the duel between the first two metaphors. Both of those are essentially materialist metaphors; in different ways they are advanced by both the rationalist planners and also by their evolution and ecology-minded critics (Jacobs 1961; Sjoberg 1965).

The immaterial metaphor is relevant and important to smart city research in that researchers should be attentive to the uses of immaterial ideals as goals or pathways for the modern city itself. Should the smart city be framed as an immaterial “knowledge commons,” which is, in a way, a kind of spiritual ideal? This chapter has assumed the relevance of that question. Further research should explore that topic in greater detail.

That means that the smart city may not be simply another step on the evolutionary pathways of the city as such. The smart city may be a qualitatively different phenomenon altogether, a dematerialized “space” that residents choose – or exit – for reasons having to do with their roles in knowledge, information, and data governance rather than simply another site in centuries-old debates about cities and political economy.

Dematerialization of community engagement and identity in the smart city may mark the end of what has historically made the city a critical site of economic activity. People will still live in agglomerated settings, but economic activity related to those agglomerations may cease to be a meaningful driver of the agglomeration. People won’t need to live where they work, or vice versa. They might live where they choose to live, including in cities. Today, we connect as much via representations in data and on screens as we do via embodied interactions. It’s entirely possible to live in a place yet participate little in traditional local communal or economic life and participate a lot (or not) in knowledge governance.

If the smart city means that what cities are for and how cities are constructed is changing fundamentally, should investigations of urbanism change fundamentally too?

That question is salient because of the Covid-19 pandemic that began in 2020, but it’s not new. Rae, writing in 2005, described the end of urbanism, as market dynamics and exit by city residents started to change the basic character of a city as a place where people collaborate to solve their problems (Rae 2005). Is Pittsburgh headed in that direction, becoming less of a place in itself that relies on a century’s worth of inherited industrial success, and more a mode of place-centered affinity that people choose based on how they experience life on the screen and in the database? The GKC framework should be useful as a device not only for understanding how knowledge commons in the smart city begin and carry on but also for understanding how they end.

Disclosure

From 2017 to 2019, I was the Academic Director of the University of Pittsburgh Institute for Cyber Law, Policy, and Security, known as Pitt Cyber. Pitt Cyber receives funding from various corporate and philanthropic supports in Pittsburgh, including the Heinz Endowments. I have no connection with research or public policy interventions supported by Pitt Cyber that are directed to City of Pittsburgh or Allegheny County operations, or to any programs mentioned in this chapter.

I was previously Faculty Director of the Innovation Practice Institute at the University of Pittsburgh School of Law, which was funded in part by the Heinz Endowments.

I am a member of the board of directors of the Partnership to Advance Responsible Technology (PART), a nonprofit organization based in Pittsburgh that receives funding from the Richard King Mellon Foundation.