Part III - Legal Tech and Access to Justice

9 The Supply and Demand of Legal Help on the Internet

Margaret Hagan

Millions of Americans have civil justice problems every month, and most of these go unmet. A recent survey of low-income Americans found that over 70 percent of households had at least one civil legal problem in a year, including around health care, housing, disability benefits, veterans’ issues, and domestic violence.¹ But of these needs, 86 percent of the problems received inadequate or no legal help.² Without legal assistance, a person may lose their home to an eviction or foreclosure, suffer physical abuse without protection, go into debt or bankruptcy, lose custody of their children, or be denied medical care.³

Why is there such a large justice gap between the high volume of justice problems and the small percentage that receive legal assistance? This may be due to the increasing costs of providing legal services, with lawyers having to follow burdensome procedures and licensing requirements that make it difficult to sustain a business model serving low- or moderate-income households.⁴ Or another commonly cited reason is the undersupply of public interest lawyers to assist people with civil justice problems. The underfunding results from decades of congressional restrictions on legal aid funding, which both limits the supply of free lawyers and restricts whom these free lawyers can serve.⁵ Without widely available free or affordable legal services, millions of people are turned away when they seek assistance.⁶

But what about those people that never seek legal aid assistance in the first place? This is the problem of awareness and capability. As Sandefur’s research has highlighted, many Americans do not conceive of justice problems as ones that are “legal” or that legal assistance could help with.⁷ Instead, they often attribute them to happenstance, bad luck, or other reasons – all of which make it more likely that they do not seek out legal or social services to have their rights protected and experts assist them. Here the problem is not a limited supply of affordable or free legal services. Instead, the problem is people’s lack of consciousness of their legal rights and how legal professionals can help them,⁸ and a lack of confidence, capability, or trust that they want to engage with legal assistance to deal with their problems.⁹

Recent decades have seen a variety of interventions aimed at closing the justice gap by increasing legal awareness among those with civil justice problems and their capability to use available assistance. In the early 1970s, consumer-facing legal clinics arose in storefronts with transparently priced menus of legal services, making legal help more approachable, demystifying the process of engaging a lawyer, and advertising how and why people should make use of legal services.¹⁰ At the end of the 1970s, bans on attorney advertising were invalidated, and legal groups began to release audio, video, and print outreach to the public to drive up people’s awareness about when and how they could use a lawyer to help them.¹¹ By the 1990s, however, the use of lawyer advertising had shifted to focus primarily on personal injury needs rather than routine legal services (like divorces, debt, and estate planning). By the mid-1990s, the storefront legal clinic movement was extinct.¹²

More recently, awareness and capability efforts have centered on use of technology. Websites like LegalZoom and Rocket Lawyer emerged to serve the needs that storefront legal clinics had decades earlier, and these sites began to spend heavily in traditional and online advertising to build people’s legal awareness.¹³ More public interest organizations also began to build websites and apps, to make it easier for people to find and use legal help.¹⁴ These sites have features intended to improve people’s capability to engage with legal services, like referral engines to make it easier to engage a lawyer, self-help guides to understand the law, chat functions to get basic questions answered, and dispute resolution tools to generate agreements with the other party.¹⁵ In recent years, new awareness-focused applications have begun to use artificial intelligence to automatically spot justice problems in their online posts, to diagnose what legal issue they might have.¹⁶

While justice problem-solving on the Internet remains a work in progress, all signs are that improving internet-based tools will be a central component of any successful effort to close the justice gap. This chapter presents a new approach to evaluating legal help websites as one of these internet-based tools. It posits that the mere existence of court and legal aid websites is not enough to close the justice gap. Rather, there must be accountability and research as to whether people are able to find and use these sites to build legal capability. This chapter presents one method to assess the impact of legal help websites: measuring the supply of sites, the demand for them, and the factors that may be impeding better matching of people with online resources.

9.1 The Need for Research on Legal Help on the Internet

As more service providers attempt to use the Internet to close the justice gap by increasing legal awareness and capability of people, more people are going onto the Internet to find help for all kinds of problems (legal or not) that happen to them.¹⁷ Many of these “life problems” that people search about (for example, getting calls from a debt collector, wondering if a past criminal record could be masked, dealing with a landlord threatening eviction, worrying about medical bills, or trying to get school services for a child with learning difficulties) are “justice problems.”¹⁸ In the past, people might have turned first to family, neighbors, librarians, or professionals to seek assistance for such life problems. People still might reach out through social connections, but increasingly the Internet figures prominently in this search for help.¹⁹

Yet little is known about the role of the Internet in people’s problem-solving around legal life events. Do online sites and tools increase people’s awareness and capabilities around their legal rights? Do they empower people to take action to resolve their justice problems? A handful of studies have surveyed people about whether and how they see legal assistance online.²⁰ This preliminary research, most of it done as small surveys and lab experiments, has established some useful insights and metrics as to how various internet intermediaries and resources may better serve individuals seeking out help on their problems. Among the insights are what kinds of search results, websites, and apps best improve people’s understanding of the law, and which may best encourage people to take action on resolving their problem. Even so, we still lack knowledge about how many people are seeking help for justice problems on the Internet and how they behave when they do seek help online.

The limits of existing studies on justice problem-solving on the Internet stand in stark contrast with the medical field. Public health researchers and medical practitioners have developed data-driven techniques to understand people’s health assistance–seeking behavior online, and what this means for how to better deliver services, predict needs, and communicate with the public.²¹ Researchers gather data on what people are searching for, what kinds of websites they are visiting, what stories they are sharing about their health, and what actions they take in response to what they find online. This research helps public health officials improve outreach and education, predict new outbreaks of disease, and develop better services to engage people.

The justice sector can leverage what the health sector has already developed: research protocols, data exchanges, and artificial intelligence aimed at improving people’s access to the legal system via the Internet. The public health work on digital epidemiology and infoveillance can guide those working on access to justice to new knowledge on the volume and type of legal needs, people’s preferences and needs for services, and opportunities for innovative technology that can improve people’s knowledge that they can use the justice system to resolve their life problems, and that can improve their capabilities to participate meaningfully in it.

To develop this research and practice around the Internet for legal help, there is a need for dedicated, ongoing work on an ordinary person’s online legal help landscape. This overarching work can spotlight where new directions for justice system outreach, services, and reform could be targeted.

1. 1. What is the demand and supply for justice problem-solving on the Internet?²²

2. 2. Who are the key intermediaries that are receiving people’s help requests and matching them with resources?

3. 3. And what are the datasets and research protocols that we can use to make sense of internet activity, for use in access to justice services and policy making?

The remainder of this chapter tackles one part of this needed research – namely, the first question, on the supply and demand of legal help in the US on the Internet as of 2021. It does so, first, by canvassing past research on how people use the Internet to deal with legal problems. Then it lays out three understudied research questions about the supply-and-demand theme: What is the quantity of the supply and the demand, what is the quality of the supply, and what harms do people experience because of low quantity or low quality? Finally, it offers preliminary answers to these questions by surveying hundreds of commercial and public interest websites that aim to serve people with civil justice problems, calculating initial estimates of how many people are visiting them, and then comparing these visit estimates with the estimates of people’s justice problems, based on legal needs surveys.

By way of preview, this analysis shows that that millions of people each month are coming to websites to seek out help for their problems, with many more visitors going to commercial sites than public interest ones. The ecosystem of public interest online resources is scattered among the states, rather than concentrated on national hubs. Some states’ public interest legal help portals are attracting a much higher relative number of visitors than others, indicating that there are substantial opportunities to improve how they offer help to the millions of people coming online for legal help each month.

This, of course, is only a start. Ideally, more researchers and practitioners will tackle the larger research agenda laid out above to build our store of knowledge about how courts, government agencies, legal aid groups, and justice technologists can engage with the public to improve their access and capabilities. In particular, there are many more data sources from internet intermediaries like search engines and social media that can provide insights about where people are going to seek help, whom they trust to help them, and what kinds of behavior they engage in to deal with their problems. Legal policy makers, service providers, and researchers can benefit from greater knowledge of what people are doing on the Internet, and how to increase people’s access to the justice system online.

9.2 Prior Research on Legal Help on the Internet

Many legal practitioners and scholars in the 2000s highlighted the potential for new websites and internet-based tools to increase access to justice.²³ These proposals detailed how websites could increase the number of people who could find assistance, lower the burdens of time and cost to access help, and improve people’s legal capabilities.²⁴ That “techno-optimism” about whether internet-based technology can increase most people’s access to the civil justice system has been challenged in recent years, as website and application development have hit hurdles in accomplishing their goals around user engagement and outcomes.²⁵

A small number of researchers have begun investigating if and how the Internet is improving access to justice. This research, primarily by Sandefur, Denvir, and Hagan, examines how people seek out legal assistance on the Internet and what kinds of tools are available for them to use.

9.2.1 A Growing Supply of Online Help, but Not Always User-Centered

Sandefur recently surveyed what digital legal help tools exist, and what forms of assistance they offer to users trying to use technology for self-help.²⁶ Her survey found 322 digital legal tools specifically for nonlawyer users. This included legal help websites with guides and forms, legal dictionaries to clarify jargon, lawyer referral service platforms, and then tools that provide almost end-to-end support for a specific problem (including diagnosis of an issue, evidence gathering, process guides, form assembly, filing, and follow-up). Sandefur observed a mismatch between what the tools offer and the apparent justice needs desired by the public, as well as the issue areas served.²⁷ Many of the digital legal tools were focused on providing information rather than facilitating user action. They also did not necessarily match the most common user needs reported by people: household finances, health and insurance, consumer problems, family problems, housing, and immigration. This study points to the need for more evaluation of the supply of online legal help, and the development of measures that can encourage more supply that matches the demands and preferences of people in need.

9.2.2 People Finding Inappropriate Resources on the Internet

Catrina Denvir has researched how different demographic groups, including young adults and senior citizens in the UK, attempt to use online search to deal with life and legal problems. Her research includes both simulation labs to analyze how people search for help and website assessments to measure the quality of the help people receive.²⁸ Denvir’s work found some common patterns in people’s behavior online. Many start with a search engine, type in short questions, and try to find pages that could help them. She observed that young people tended to find and use information with little regard to the importance of jurisdiction. Even as digital natives, they often were unable to use the Internet to get correct information on their problem. In some cases, the young people got distracted by irrelevant information, trying to apply it to their situation, even if it was not legally correct to do so. These lab studies confirm that more people are trying to use the Internet to find help but raise concerns about people (including digital natives) finding “help” that in fact has incorrect, out-of-jurisdiction, or anecdotal information that may lead them astray.

9.2.3 Preferences for Clear, Authoritative, Open Access, Comprehensive Resources

My own earlier research performed lab simulations, in which US adults were asked how they might respond to a legal problem using the Internet.²⁹ This study found that respondents, as in Denvir’s studies, preferred to start with a search engine like Google to find help for their civil justice problem. And as with Denvir’s respondents, they often ignored the importance of jurisdiction, and they sought out peer-to-peer anecdotes on forums. The study also had respondents evaluate different commercial and public interest legal help websites and express their reasons and preferences for the ideal online assistance. Most all respondents wanted a tool that met the following criteria:³⁰

• • Authoritative, if not directly from the government, then closely affiliated with it;

• • Open Access, without paywalls, advertisements, or upselling – ideally being offered by a public interest actor rather than a commercial one;

• • Modern Design and Technical Capabilities, that offer mobile-friendly, intuitive, and interactive resources, and that are accessible to people with disabilities;

• • Comprehensive, with resources not just for initial understanding of a problem area, but also for taking action to respond to a problem.

These preferences echo Sandefur’s concerns that current digital tools are not comprehensive enough (providing only information rather than tools to take action). The user preferences also suggest categories for a standard evaluation metric, which researchers could use to measure if sites are sufficiently meeting people’s needs for usability, accessibility, and trustworthiness.

9.2.4 Open Questions for Further Research

Research studies so far on the Internet’s role in access to justice have been relatively small, with surveys, simulation tasks, and user interviews of small groups of people. What is missing is a broader examination of how people use the Internet to seek help for justice problems. The early research has laid the groundwork: More people are going online to seek help, and there are more sites, tools, and apps being built to serve them. But what do we actually know about the supply and demand of legal help online?

Public health data-driven research can provide legal researchers with models for evaluating the Internet’s use for access to a public good. The rise of digital epidemiology, infoveillance, and infodemiology³¹ in the public health field offers lessons for legal researchers exploring how people are seeking and finding help for justice problems, on a population level. Digital epidemiology and infoveillance involve drawing upon digital sources of data where people share information about themselves, like on search engines, social media sites, and other platforms. This data can then be analyzed through techniques like natural language processing to identify patterns, intents, and possible problems. Digital epidemiology has been used to analyze internet datasets to identify possible influenza outbreaks based on patterns of user searches, mental health risks based on online forum posts, and risk of being infected with HIV based on tweets.³² These techniques have identified patterns of people’s medical needs, their preferences for assistance, and the coming outbreak of a crisis – though they may be problematic if relied upon as the sole evidence for where to deploy resources or make policy.³³

Legal researchers might employ techniques akin to digital epidemiology in order to establish broader, population-level understandings of access to justice on the Internet. Returning to the core research questions introduced previously, but with a richer sense of the state of the field, new research might ask:

1. 1. What is the quantity of demand and supply for legal help on the Internet? What is the volume of assistance being sought out? Does the supply match the demand? Are there “online legal help deserts,” with minimal resources for certain issue areas? These can help make better agendas of where resources should be spent in creating more online help.

2. 2. What is the quality of the supply of legal help, and the matching of people to this help? Are the websites and tools online providing resources that people want to use, are able to use, and that get them to good outcomes? And are intermediary platforms directing people to higher-quality help, or to lower-quality help? Research around quality of supply and quality of intermediary’s matching can help set better policy about what kinds of online tools should be funded, and what internet platforms like search engines and social media ought to prioritize in their algorithms.

3. 3. Are there harms occurring when people seek help on the Internet? Are people finding malicious or unintentional misinformation about their legal options, processes, and outcomes online? This may be because of their own misunderstanding of jurisdiction, their reliance on anecdotal advice, frauds and scams, or intentional misinformation campaigns. As with public health concerns over misinformation and over harms of medical advice being given over the Internet, legal practitioners and policy makers could benefit from more research on whether and how people are finding misinformation about their justice problems online, and what harms these may cause. This could lead to more intentional strategies by service providers, policy makers, and internet platforms to address misinformation and support quality sources of assistance.

This chapter, as already noted, tackles the first of these questions, about the quantity of supply and demand for legal help online. It provides initial data sources, techniques, and findings that can offer some insight into how the Internet is functioning in people’s access to justice.

9.3 What Is the Quantity of Supply and Demand for Legal Help Online?

How many people are coming to the Internet to find help for their justice problems? And how many resources are there to assist them with these problems? There is no perfect source of data on the demand or the supply for legal help on the Internet. But there are surveys and proxy data sources that can help us to estimate what is happening online. This section presents the data sources and methods to quantify the supply and demand of legal help online: the sites that are supplying help (either as intermediaries or as providers of legal help) and the numbers of people that are seeking help.

The Internet has billions of websites.³⁴ How many of these count as “supplying” legal help for people seeking help for justice problems? First, we must distinguish between two types of help websites: intermediaries and providers. Intermediary sites let people express their problem or story, and then discover links, people, or answers to their problem. Some of the primary legal help intermediary platforms in the US are search engines, social media platforms, and forums. Providers’ sites, on the other hand, provide content for a person to deal with their justice problem (rather than just referrals to other sites).

9.3.1 Intermediary Platforms Used for Justice Problem-Solving

The main intermediaries for justice problems are likely to be the same as general problem-solving intermediaries: search engines, voice assistants, and social media platforms.

Search engines are platforms in which people present words, phrases, or sentences for the intermediary to then interpret and respond with sites (or direct answers). Google Search is by far the most widely used search engine. For search engines from US desktop computers in 2021, Google received 86.64 percent of search queries, Microsoft’s Bing search engine had 6.79 percent, and Yahoo, 2.75.³⁵ For mobile searches, the companies are in a similar order – but with Google with an even higher share. Of mobile searches in the US in 2021, Google has 93.4 percent market share, Yahoo has 2.02, Bing has 1.87, and DuckDuckGo has 2.3.³⁶

Voice assistants, in the form of mobile phone–smart device assistant or voice-enabled speakers, are another rising type of intermediary. Voice assistants are increasingly used, in particular on one’s smartphone, car, tablet, television, or computer. Over 63 percent of Americans used a voice assistant as of 2020, and 51 percent use a voice assistant on their smartphone.³⁷ In 2020, an estimated 128 million US residents used a voice assistant at least once a month.³⁸ Searching the Internet is the most frequent use cases for voice assistants.³⁹ For voice assistants specifically in home speakers, Amazon’s Alexa brand (as of 2021, relying primarily on the Bing search engine) is the leading voice-enabled speaker with 69.7 percent of US market share in 2020, with Google’s Home devices (using Google Search) at 31.7 percent, and others at 18.4 percent.⁴⁰

Social media platforms are another key intermediary. The most popular platforms among US adults as of 2021 were YouTube (81 percent use it), Facebook (69 percent), Instagram (40 percent), Pinterest (31 percent), LinkedIn (28 percent), Snapchat (25 percent), Twitter (23 percent), WhatsApp (23 percent), TikTok (21 percent), Reddit (18 percent), and Nextdoor (13 percent).⁴¹

We can assume that the general popularity of these search engines, voice assistants, and social media sites carries over to justice problem help-seeking. These intermediaries provide opportunities for research on internet problem solving. Just like in public health research, we can use them to observe what people are searching for, how they frame their problems, what they click on, and how they behave. That said, research using these intermediaries is difficult, because they do not make their data about users’ searches, clicks, and other behavior open to researchers.

9.3.2 Provider Websites That Offer Legal Help

Apart from these intermediaries of online legal help, there are the provider websites, which offer assistance to people seeking help on a justice problem. Within the provider group, there is another division, between commercial providers and public interest providers. Commercial providers have a for-profit business model and are giving help, information, and tools in order to either upsell the user to other services or to get advertisement or referral fees from them. Public interest providers have a nonprofit business model and are trying to get assistance to the user in order to improve their outcomes. Some may aim to generate revenue through paid services, but most public interest sites are funded through grants or government funds.

9.3.3 Commercial Legal Help Supply

I surveyed the Internet for commercial websites that offered legal assistance for civil justice problems and identified over seventy sites that have over approximately 5,000 visitors per month. Some of the most prominent general commercial legal help websites are Nolo.com, Avvo.com, Findlaw.com, Legalmatch.com, AllLaw.com, and LawShelf.com. These sites offer resources for a wide variety of legal issue areas.

There is another layer down of commercial legal help suppliers: those that focus on particular areas of legal needs. Some focus on creating legal documents for estate planning, businesses, and contracts.⁴² Other providers aim exclusively at business formation legal needs.⁴³ Another cluster of commercial providers focuses on family law needs, like divorce and child custody.⁴⁴ There is another cluster around bankruptcy, debt, and credit repair problems,⁴⁵ another around disability benefits claims and navigating resources for people with special needs,⁴⁶ and another around personal injuries and torts.⁴⁷

In addition to sites whose mission is exclusively around providing legal help, there are also commercial sites in other, nonlegal domains that try to attract users with justice problems. In this parallel commercial group, there are sites that offer financial literacy and other professional services, such as Nerdwallet.com, Credit.com, Creditcards.com, Consumerhelpcentral.com, Studentloanhero.com, or Angieslist.com. These sites’ resources often overlap with legal help resources, especially for life problems that have both legal and financial dimensions, like debt collection, homeownership, and landlord-tenant scenarios. The other parallel commercial group are news outlets. Sites like Usnews.com, Wusa9.com, WashingtonPost.com, and Cnbc.org offer articles that provide basic overviews of legal situations, with short articles aimed at giving general discussions of various life, legal, and financial problems.

I compiled a list of the most popular commercial legal websites, using search engine optimization (SEO) tools Ahrefs and Similarweb, which list the most popular websites for common keywords. By searching for sites that appear frequently for keywords around law, legal help, legal aid, legal answers, and related issues, I identified approximately seventy commercial legal help sites. This research focused on civil justice problems (so excluding criminal and immigration law keywords). Also excluded were commercial provider websites that appear to have fewer than 5,000 visits per month.

9.3.4 Public Interest Legal Help Websites

Apart from the commercial providers, there is a robust ecosystem of public interest legal help websites. They provide similar kinds of content as the commercial ones do articles, step-by-step guides, frequently asked questions, and form-filling tools. They also tend to have contact information for legal aid attorneys, free chat with law librarians, and other on-ramps to free services.

Unlike the commercial provider sites, public interest legal help websites are almost all at the state or local region level. It is notable that there is not a single national legal aid or public interest legal help portal that gives national guidance on civil justice problems. Rather, it has been state or local actors that have created legal help portals for their region, giving guides and contacts for people looking to address their justice problems.⁴⁸

There are some national public interest websites around specific issue areas or demographic groups. For example, there are national public interest sites for sexual assault and domestic violence,⁴⁹ women’s law issues,⁵⁰ landlord-tenant issues,⁵¹ immigration issues,⁵² and bankruptcy and debt issues.⁵³ There are also some national legal help websites that provide specific tools or resources, like a legal dictionaries and reference materials.⁵⁴

I identified approximately 340 civil help websites that provided free information and tools to people in the fifty states, as well as DC and Puerto Rico. I did not include local bar associations, law library, or county court websites, because the majority of them do not have substantial self-help material (though this may change in the future, and these sites might be added into future research).

Most public interest legal websites operate at the state or regional level. Within each state, frequently there is a local ecosystem of four kinds of public interest legal help websites:

1. 1. A statewide legal help portal, which provides an overview of civil justice guides, contacts, FAQs, and tools.

2. 2. A legal aid organizational website (or sites), which provides contact information, hotline numbers, clinic details, and a limited number of articles or guides on legal issues. (Some states have many regional legal aid groups, each with its own website, while others have a single main legal aid group serving the entire state.)

3. 3. A court self-help website, which offers court-focused guides, tools, forms, and service hours to self-represented litigants who have an issue in civil, family, or traffic court. (Some local county courts may have their own self-help, but typically this is run by the statewide judicial council or administrative office of the courts.)

4. 4. A free online brief advice clinic for low-income people, run through the ABA Free Legal Answers project. Not every state has a Free Legal Answers clinic, but more than thirty do.⁵⁵

Some states, like California, Florida, and New Jersey, have many legal aid organizations and so have a large number of public interest websites. Other states, like Wyoming, North Dakota, Georgia, Wisconsin, or New Hampshire, do not have statewide legal help portals and may only have one or two public interest legal help sites.

9.4 What Is the Demand for Legal Help Online?

There is no public data source that represents exactly how many people are searching for justice problems. Google and other search engines do not release their data on exact numbers of search volumes for different queries. But there are other proxies that make possible some estimates of how many people are seeking legal help online.

9.4.1 Estimates of Demand from Legal Needs Surveys

One way to estimate how many people might be coming online to find help is to look at estimations of how many people experience justice problems in the US. Legal needs surveys ask adults about how often they have experienced justice problems, like situations of wage theft, eviction, debt collection, bankruptcy, domestic violence, foreclosure, access to medical treatment, and the care and custody of children and dependent adults.⁵⁶ Sandefur’s study of a representative sample of US adults in 2013 found that two-thirds of them experienced at least one civil justice problem in the past eighteen months, with the average number of justice problems being 2.1 problems in eighteen months. Of the two-thirds of adults who reported having a problem, they averaged 3.3 needs in eighteen months.⁵⁷

These rates of justice problems allow us to estimate how much demand there might be for legal help. By using this estimated rate of each adult experiencing 2.1 problems in eighteen months, we can use states’ adult populations to estimate how many people are experiencing justice problems in a month. This estimation is likely to overestimate the number of people coming to the Internet to seek help for a justice problem. Surveys have found that 16 percent of US adults take no action (including reaching out for assistance or searching for help) when they experience a justice problem.⁵⁸ Accordingly, we can assume that a significant proportion of adults with a justice problem, akin to this 16 percent figure, may not come online to find help. There are not yet surveys that document the rate at which people experiencing a justice problem go onto the Internet to seek help.

I calculated each state’s expected number of justice problems per month, and the expected number of problems for which people seek help.⁵⁹ For example, we might assume that each month in California there are around 3,572,000 justice problems, and that people might take action on approximately 3 million of them. Or in Alabama, there may be around 445,000 problems per month, and people will seek help for around 374,000 problems. In total, we can assume that the whole US population has around 25 million acted-upon justice problems per month (with acted-upon meaning that the adult takes action to try to address it). These estimates provide a rough expectation of how many adults might be seeking help online.

Using these estimates of acted-upon justice problems per state, we can approximate if supply is matching demand. Are people in a state visiting legal aid, court, and public interest websites at the rate we may expect them to? Are there 3 million visits to California legal help websites each month – or is the number substantially higher or lower? How well is the supply of public interest websites matching the demand for legal help?

9.4.2 Tracking Demand through Analytics and SEO Traffic Estimators

Aside from estimates based on surveys, another strategy to measure demand is to count the visitors to legal help websites. There is a clear gap in this strategy: Not all people searching for help with a justice problem online will in fact find their way to a legal help website. Website visit counts will not capture demand from people who might have framed their online queries in terms that may have led them to other sites – or who looked at search results and decided not to click anything. Still, the visitor counts can help us see if the expected demand matches the actual demand, and if that matches the number of people using public interest sites.

Site analytics. Sites that have an analytics tool installed can track the numbers of people who come to visit, what search terms or other sites have referred them to this site, and what pages on the site they visit. These analytics numbers are useful because they are closest to being exact counts of visitors. They are not completely accurate. Often they will undercount visitors, because of the use of ad blockers, cookie blockers, and JavaScript disablers by visitors. When a person has these blockers in place on their browser, they can prevent Google Analytics from tracking their behavior – and thus stop the site from registering their visit. Researchers can use Analytics, from websites’ administrators that have given them access or reports to their sites. These numbers will likely underestimate actual visits.

SEO platforms have developed tools to estimate the traffic to websites, even without access to websites’ administrative backends. These SEO research platforms do not offer exact numbers of how many visitors come to a specific website in a month. But they provide useful estimations of how many visitors are coming from search engines to a site.⁶⁰

SEO traffic estimator by search keywords. One type of SEO traffic estimation tool, like that from provider Ahrefs, makes these estimates by tracking billions of keywords that people tend to search for, and then seeing how many people are searching for them each month, which sites appear for them, and which sites people click on.⁶¹ This permits estimates of the average monthly visitors coming from search engines to a given site. The SEO traffic estimation tools will most often underestimate actual visitors to a website because of several inbuilt constraints. First, some SEO tools (like Ahrefs) track only visitors who are coming from search engines, and not from other pathways (like those directly typing in the website URL or coming from another non-search website). Second, they do not track every single keyword (or search query) that a person might type into a search engine. Though a tool like Ahrefs Traffic Estimator follows over 6.1 billion keywords, visitors might use “long-tail” searches (like, “show me a legal aid group that can help me with an eviction notice please Google”) that it does not track.

SEO traffic estimator by behavior tracking. Another SEO estimation tool, Similarweb, takes a different approach. It gathers data about users’ online activities from internet service providers, a panel of monitored devices, and shared web analytics accounts.⁶² They use their behavioral tracking data, analytics access, and other public data sources to estimate how many people are visiting a given website. Other SEO tools have found Similarweb to provide the most accurate estimates of total visitors to a site, though they tend to overestimate visitors.⁶³

To assess which estimation tool might be useful, I used a website that I maintain with my team at Stanford Legal Design Lab. In May 2020, our team launched a national non-profit website for housing law information, Legal Help FAQ. We have Google Analytics tracking visitors to the website and keeping counts of users and visits. According to Google Analytics, in the month of January 2021, the site had 13,520 users and 30,623 page views. Similarweb estimated that the site had 18,126 users and 31,877 visits. They overestimated visitors by 34 percent (4,606 users), and visits by 4 percent (1,254 visits). Ahref estimated total traffic from Google Search to LegalHelpFAQ to be 42 visitors in January 2021. Google Analytics indicated that we had 4,385 visitors from Google Search in January 2021. This was a substantial underestimation of search traffic to our site, with a difference of 4,343 visitors. I then proceeded to measure Similarweb’s estimates against other sites, whose administrators shared their Google Analytics reports with me (see Table 9.1).

Table 9.1 Comparison of different estimations of visitors to legal help websites

Site	Google Analytics reported visitors per month (likely to underestimate)	Similarweb estimation of visits per month (likely to overestimate)	Difference between site Analytics and Similarweb’s estimate
Legalhelpfaq.org	13,520	18,126	34 percent over, by 4,606
Wisconsin State Law Library	30,100	36,461	21 percent over, by 6,361
Michigan Legal Help	180,049	166,689	7 percent under, by 13,360
Texas Law Help	318,232	378,050	18 percent over by 59,818

Google Analytics tends to underestimate the number of visitors, though it is not clear by how much. Similarweb seems to overestimate the number of users visiting the site, differing from the Analytics by as much as 34 percent. Similarweb’s numbers are substantially closer to the Analytics’ numbers than the Ahrefs tool.

With those caveats on the tools’ limitations to produce exact numbers, Similarweb does provide us with rough estimates of most legal help websites’ traffic. Its ballpark estimates should not be relied upon for exact measures, but they can be approximate counts to help service providers and policy makers compare how different kinds of sites are performing and how they change over time.

9.4.3 Legal Help Site Visits as Proxy for Demand

By looking at rough estimates of visits to various types of legal help websites, we can see what kinds of justice problem-solving behavior is happening online. These numbers are estimates from Similarweb, so they may overestimate actual visitors. They are also for a single month, January 2021, which occurred during the COVID-19 pandemic, and so may be different than a typical month (without a public health emergency) (see Table 9.2).

Table 9.2 Estimated visitors to commercial legal help websites in a month

Type of commercial legal help website	Estimated monthly number of visits to this site in Jan. 2021, from Similarweb
All types of commercial legal help sites	50,909,394
General legal help websites	31,539,004
Legal forms sites	7,702,137
Immigration	3,312,554
Public benefits sites	2,050,050
Family law websites	1,857,023
Small business sites	1,765,107
Debt, credit, and bankruptcy sites	1,439,497
Personal injury sites	1,244,022

These monthly estimates of visits to commercial legal help websites indicate that tens of millions of people come online to seek assistance and information about the law each month. Compared to our earlier estimate from legal need surveys that the US adult population has approximately 25 million justice problems per month, the visits to commercial websites almost double this estimate. This high number of visits may include “multiple visit” scenarios, in which a person with a single justice problem visits more than one website in order to find assistance. These website visits may also include visits from people outside the US, who found the resource online. Some visits may also come from legal professionals or researchers, using these websites in their own work. We cannot take each visit to a website as indication of a unique justice problem; these numbers of website visits are not direct proxies for legal need counts.

These caveats aside, this estimated traffic of over 50 million visits to US commercial legal help sites in one month strongly suggests that there is a substantial demand for legal information and assistance online. This survey also shows that there are active ecosystems of websites supplying assistance for certain legal issue areas, including immigration, public benefits and disabilities, family law, small business, bankruptcy, and personal injury.

9.4.4 Visits to Public Interest Legal Help Websites

As mentioned earlier, most public interest sites are local rather than national. There are approximately twenty public interest national sites, most of which focus on particular legal issues or provide national coverage with legal dictionaries or sets of forms.⁶⁴ The total estimated number of visitors in January 2021 to only the national public interest websites was around 6,290,000 visitors.

This 6.2 million visitor count must be adjusted downward, though 4.49 million of those visitors were to Cornell’s Legal Information Institute (LII), which provides a legal dictionary and open access to legislation and other laws. Many users of LII are legal professionals and students using its legal reference resources. It’s impossible to discern how many of LII’s 4.49 million visitors are legal professionals versus people seeking help on their justice problem. The monthly number of laypersons seeking help on the national public interest legal sites likely lies between 1.79 and 6.29 million (see Table 9.3).

Table 9.3 Estimated visitors to national public interest legal help websites in a month

Type of national public interest legal help website	Estimated monthly number of visits to this site in Jan. 2021, from Similarweb
All types of national public interest legal help sites	6,291,274 (or 1,798,274 without LII)
General legal help websites	4,800,403 (of which, 4,493,000 to LII)
Debt and bankruptcy	569,366
Domestic violence	444,591
Women’s law	388,478
Immigration	56,559
Housing	31,877

The estimated traffic to national public interest sites is substantially lower than that to national commercial help sites, by at least 44 million visits per month. The coverage of issues is also quite different. National public interest websites focus more on debt, domestic violence, and women’s law issues, and less so on family law, small business, immigration, public benefits, or housing. In some cases, such as family, benefits, and housing, the shortfall is likely because regional public interest sites are expected to serve this need. But the lack of a national public interest hub for these issues is noticeable, particularly given apparent high demand for these issues.

How do local public interest legal help websites (for instance, those of a local legal aid group or court self-help center) fare, in terms of estimated monthly traffic? Unfortunately, it is difficult to measure most courts’ self-help sites, because of the nature of their websites. Most court help pages are located as a subpage of the main court website (like https://www.azcourts.gov/selfservicecenter or https://mdcourts.gov/legalhelp). This prevents estimation of their traffic, because the Similarweb estimation tool works on only the main domain and not the subpages. I was also unable to estimate many legal aid sites’ visitors, because they apparently have fewer than 5,000 visits per month, and the Similarweb estimation tool could not reliably predict their visit count.

These limits result in a restricted measure of local public interest site visits. I ran visitor estimations for each state’s statewide legal help portal. Not every state has a dedicated “Law Help” portal. In some cases, such as Delaware or Wisconsin, it is a legal aid group’s site that functions as a de facto statewide resource. But most of the states do have something akin to Alaska Law Help, Law Help Hawaii, or Massachusetts Legal Help. The estimated visitor counts to these statewide law-help portals is a first attempt to measure people’s visits to local public interest sites.

The total estimated visitors to the statewide legal help portals were approximately 3,454,000 per month. Nine of the portals had over 100,000 estimated visitors per month, mostly from high-population states like Texas, Massachusetts, and Illinois. But the numbers of visitors did not necessarily correspond to population numbers or projected levels of justice problems (see Table 9.4).

Table 9.4 Estimated visitors to statewide legal help portals, including most highly visited sites

Statewide legal help portal	Estimated monthly number of visits to this site in Jan. 2021, from Similarweb
All statewide legal help portals	3,453,921
Texas Law Help	578,563
Massachusetts Legal Help	424,324
Illinois Legal Aid Online	369,715
Connecticut Law Help	312,095
Michigan Legal Help	248,960
Washington Law Help	218,663
LSNJLaw	174,994
The People’s Law Library of Maryland	152,816
Pennsylvania Law Help	100,665
Law Help New York	80,832
Legal Aid Oklahoma	77,806
Arizona Law Help	71,560

9.5 Discussion of Online Legal Help Trends

When we compare the expected number of justice problems in each state to the visits to the statewide legal help portal, some sites have visitor numbers that are a much higher proportion of the estimated demand than others. For example, Connecticut’s portal visitor estimates reach almost 95 percent of the estimated justice problems occurring in its adult population. For Massachusetts, this percentage is around 65 percent, Illinois is around 32 percent, and Washington at 31 percent. At the other end of the spectrum, the statewide legal help portals of California, Florida, and North Carolina seem to be getting visits for only around 2 percent of estimated problems in the state (see Table 9.5).⁶⁵

Table 9.5 Proportion of estimated acted-upon justice problems to statewide portal visits

Jurisdiction	Expected number of acted-upon justice problems per month	Estimated visits on state legal help portal for this jurisdiction per month	Difference between estimated problems + web visits	Proportion of expected problems showing up as portal visits
Connecticut	331,082	312,095	−18,987	0.9426516694
Massachusetts	646,299	424,324	−221,975	0.6565444167
Illinois	1,149,627	369,715	−779,912	0.3215956132
Washington	694,380	218,663	−475,717	0.3149039431
Maryland	549,616	152,816	−396,800	0.2780413962
Michigan	915,008	248,960	−666,048	0.2720850528

The high proportion of visits to portals in Connecticut and Massachusetts may not mean that nearly every person in these states who experiences a justice problem is coming online and finding their statewide public interest resource. These portal websites may have content and technical strategies that attract visitors from outside their jurisdiction. Their relatively high number of visits does indicate that these states are effective at making public legal help accessible and discoverable online.

9.5.1 State Portals as an Underdeveloped Resource

For those states whose portals get relatively few visits, this may be because there is another public interest site in their jurisdiction that has a high-traffic site. For example, in California the statewide legal help portal gets far fewer visitors than the court’s statewide Self-Help center website. In this state (unlike most others), the state court is the leader in online legal help.

Still, the estimates of monthly visitors to public interest legal help websites show that there is a broad section of the public that is not finding these free, non-profit resources when they are searching for their justice problems online. The estimated visitors to commercial websites indicate that there are tens of millions of people seeking information on legal topics on the Internet each month. A handful of public interest websites have been able to attract relatively high proportions of their potential audience. But most state portals seem to be getting visits from fewer than 20 percent of people in their state experiencing justice problems.

These findings indicate a gap that policy makers and service providers must prioritize. The supply of public interest legal help sites might be improved with more content, improved technical and design updates, and outreach strategies. The sites may be able to reach more of the people seeking legal help online if they improve their performance so that more people can find them, and more internet intermediaries are likely to place them high on search results.

How does a site improve its offerings and placement by intermediaries? One answer is investment in better content that matches what people are searching for and websites that engage visitors so that they do not click away quickly. It also involves improving the technical and design performance of the sites, so that search engines favor them. More work needs to be done with public interest sites to master these SEO techniques and content development work that many of the commercial sites have done, in order to engage the millions of people coming onto the Internet in search of help.

9.5.2 Technology Companies’ Role in Directing People to Commercial or Public Interest Sites

Another area of policy concern is the dominance of commercial legal help websites in visitor patterns over public interest websites. To be sure, commercial legal help websites are not inherently bad. For-profit entities have high-powered incentives to offer user-friendly designs, responsive technology, and content and services that match the needs of the public. Their business models, however, tend to steer people away from free legal assistance and give only basic beginning information about a legal issue rather than a full protocol of steps and process.

A standard approach is to offer short descriptive articles about a problem like eviction or debt collection, rather than a full step-by-step guide like those that might be found at public interest websites.⁶⁶ One type of commercial model relies on attracting people to click on the site, in order to show them advertisements. These sites present short, generic articles framed around FAQs like “How Do I Stop an Eviction?” which give people descriptions about the law and options of what they can do while showing multiple advertisements for nonlegal content. These generic articles do not provide information about jurisdiction, defenses, laws, or free services a person can use.⁶⁷ Another for-profit model provides short summaries of substantial, local legal information for free, but then with a paywall around actionable help. For example, on Nolo’s website about non-payment of rent and eviction, the site provides a summary of local legal requirements and defenses. If a visitor wants to understand how to make use of these laws, the site advertises that they should buy the website’s books, forms, and templates, or that they should hire a lawyer affiliated with the site.⁶⁸ By contrast, public interest sites tend to give visitors a menu of free assistance, including do-it-yourself guides, form-filling tools, free legal navigators, legal aid representation, and holistic social services assistance.

Commercial websites may be getting so much traffic vis-à-vis public interest ones because they have deployed more search engine optimization strategies: producing more content that matches people’s search keywords, creating sites that people stay on for longer amounts of times, having technically capable websites, and taking other actions that make it more likely for Google and other search engines to place them higher on search results pages. Public interest organizations may, as mentioned before, improve the content and technical performance of their sites to be more competitive.

Still another factor that shapes comparative use rates is the search engine companies’ policies themselves. As with other sectors, the search engine companies could alter their ranking algorithm to prioritize court, legal aid, and other public interest legal help providers above commercial providers. Google, for example, has altered how it responds to its users’ searches around health problems or voting and elections to provide information that is sourced from vetted public interest actors rather than commercial websites. In 2015, Google partnered with the Mayo Clinic and medical doctors hired by their company to curate medical knowledge panels to show in response to people’s health searches.⁶⁹ In 2016, Google worked with a university and foundation-supported Voting Information Project to present knowledge panels on where to vote, requirements to vote, and who is on the ballot in local elections.⁷⁰ Could such an initiative be possible for users’ queries around evictions, foreclosures, wage theft, divorce, custody, debt collections, and domestic violence protection? Technology companies play a substantial intermediary role, directing people to resources that can answer their questions and conferring authority to those that place high in their search results. Public interest organizations may partner with these search engine intermediaries to create knowledge panels and search rank algorithms that convey key local legal help information to people searching online that would appear before the normal search results from a mix of commercial and public interest providers.

More thinking remains to be done on how best to harness the capacities, resources, and profit-seeking motivation of the commercial sector alongside the public-interest orientation and ethical approach of non-profit and legal aid groups, whether public or private. The empirical analysis presented above aims to spur some of that thinking.

9.6 Conclusion

This chapter raises many questions for future research about the role of the Internet in access to justice. Is it an effective on-ramp into the justice system for people who come online to find help? Or is it confusing, misleading, or harmful – possibly directing people to incorrect or unhelpful resources, or overwhelming them so that they disengage, or offering them too-limited resources that don’t empower them to take action to resolve a problem?

Future research can build off the initial data collection, methods, and analysis in this chapter. The documentation of the legal supply – the intermediaries, commercial providers, and non-profit providers – can be built upon, with greater evaluation of their traffic, their quality, and people’s outcomes when using different kinds of online sites. The initial estimates of demand for online legal help might be refined in future work, with better information about the rates at which people go online for justice problems and the rate of different kinds of legal issues.

This chapter was not able to tackle many other important questions about the Internet’s role in access to justice. In particular, what is the quality of the supply of legal help online? Are people able to discover the highest quality help, or are they being directed toward lower-quality or incorrect help by intermediaries? This type of quality evaluation can be done through a standardized scorecard of legal help sites, building off of earlier research on user preferences and effectiveness of legal technology. Building off of Sandefur, Hagan, and Denvir’s earlier assessments of legal help tools’ quality, some key measurements of quality are: (1) content quality (accuracy, relevancy, and actionability); (2) human-centered design (accessibility, amount of administrative burden, and engagement of user); (3) technical performance (speed, lack of bugs, responsiveness); and (4) discoverability (search engine placement, social media referrals, backlinks to trustworthy sources).

In addition, legal researchers can build from public health researchers’ digital epidemiology and infoveillance techniques to track legal needs through search engines and social media data sources. Researchers could pool legal aid groups’ Google Analytics, or use SEO traffic estimators, along with Google Trends and other intermediaries’ APIs in order to track people’s online expressions of justice problems and legal needs longitudinally. This research on legal needs can provide useful population-level knowledge about what kinds of justice problems people are experiencing, what seasonal patterns exist, and what outbreaks of needs may necessitate new emergency services or outreach.

The final priority area going forward should be documenting and measuring harms people may be experiencing when seeking assistance online. Are there situations akin to antivaccine misinformation in law? How often are search engines directing people to legal help resources from the wrong jurisdiction, leading people to rely on incorrect law, file incorrect forms, or use a defense they don’t actually have?

Finally, in addition to more research-focused work, policy makers and justice stakeholders should focus on online strategies to address the justice gap. There are two main avenues. First are efforts to increase the prominence of public interest legal help online. This work could aim to reform existing state help portals, legal aid websites, and free tools, to have content that better matches people’s searches, design that is more user-friendly, and technology that is more responsive and fast-loading. All of these factors can increase public interest websites’ prominence in search results and numbers of visitors. The second reform avenue is for court and legal aid leaders to engage technology companies to change how search algorithms treat people’s searches for justice problems. There is the potential for a public-private partnership, to develop more reliable, quality content for Google, Siri, and other search engines to feature when someone goes online to search “help I’m being evicted” or “how do I get a restraining order?” The Internet holds great promise in developing people’s awareness of their rights and their capability to take action on justice problems, but there is still substantial work to be done to deliver on this potential.

10 Digital Inequalities and Access to Justice Dialing into Zoom Court Unrepresented

Victor D. Quintanilla , Kurt Hugenberg , Margaret Hagan , Amy Gonzales , Ryan Hutchings , and Nedim Yel

The gravest public health challenge in a century has disrupted and transformed our civil justice system. In the span of weeks, courts across the country were forced to make countless, rapid, and difficult decisions. Many courts suspended in-person hearings and moved proceedings to online platforms, such as Zoom. While a shift to virtual courts has been lauded by technological enthusiasts and reformers for decades, little research has examined how this technological change may affect vulnerable unrepresented persons and low-income people in the United States on the “have-not” side of the digital divide.

In this chapter, we seek to cast light on how virtual proceedings unfold for these low-income unrepresented persons in the everyday. It is important to do so. To date, much of the conversation has lauded Zoom court proceedings as the future of civil justice, centering this praise on idealized forms of online proceedings and their conveniences, without interrogating the impact of the precarity that low-income people contend with or persistent digital divides.

In marked departure, we examine how these new technologies affect the experiences of low-income unrepresented persons who encounter, and contend with, adversities within virtual court proceedings. We examine how these new technologies reconfigure the features, affordances, and barriers present within the civil justice system, and the impact of these new technologies on the psychology of judges, lawyers, and unrepresented persons, as well as the impact of these new technologies on the meaning of the judicial role and on a person’s unrepresented status. As political theorist of science and technology Langdon Winner observes, “[i]f the experience of modern society shows us anything … it is that technologies are not merely aids to human activity, but also powerful forces acting to reshape that activity and its meaning.”¹ In fact, we must “pay attention not only to the making of physical instruments and processes … but also, to the production of psychological, social, and political conditions as part of any significant technological change.”²

Here we adopt Winner’s perspective by focusing not on an idealized future for virtual courts under techno-optimistic conditions, but on the actual practice and experience of low-income unrepresented persons in virtual courtrooms today. We do so to allow a forthright consideration of policies and reforms needed to improve access to justice. Unlike debating the costs and benefits of in-person versus virtual proceedings under idealized conditions, looking to the bottom casts light on the actual needs, experiences, and outcomes of real people in virtual proceedings. Moreover, we believe that examining how virtual proceedings unfold in the everyday will contribute to the development and refinement of accurate and useful theories about our dynamic civil justice system and best practices for enhancing access to justice in virtual proceedings. Finally, we center our analysis not just on the experiences of those on the “have” side of the digital divide or those who are the most powerful in these settings – judges and lawyers – but also on those on the “have-not” side of the digital divide: low-income people who contend with adversities and confront challenges when seeking justice in virtual courtrooms.

Past research on videoconference hearings is mixed on whether the use of videoconferencing negatively impacts assessments and outcomes.³ Research does suggest that defendants appearing in videoconferences may be disadvantaged.⁴ Indeed, one widely cited study revealed that video bail hearings resulted in bail amounts that were 51 percent higher for those who appeared virtually as opposed to those who had their hearings in person.⁵ Yet these studies are dated, and the technologies employed in virtual courts during the global pandemic have vastly improved. Moreover, little attention has been paid, to date, to the implications of video conferencing for unrepresented persons, let alone cases involving asymmetries of representation involving low-income persons. In short, there is pressing need for a new and thorough look at the access-to-justice implications of virtual hearings.

In this chapter, we report the first phase of a multiphase research program made possible with funding from the Pew Charitable Trusts. In this preliminary phase, our research team engaged in observations of over 500 live-streamed Zoom/Webex proceedings in small claims courts in Indiana, most of which were eviction and debt collection cases. Our research revealed that the vast majority of low-income persons in these cases are unrepresented (98.6 percent), and a majority are dialing into virtual court (e.g., Zoom/Webex hearings) on their cell phones (64.4 percent) without access to the virtual capabilities of these remote proceedings, including cameras. In the main, these cases involve representational asymmetries, in which repeat-player plaintiff lawyers litigate against low-income persons who are unrepresented. Troublingly, these cases entail an additional layer of technological asymmetry, in which repeat-player lawyers regularly employ the full range of virtual interaction and videoconferencing capabilities of Zoom/Webex, while the low-income unrepresented persons whom they sue, because they dial into these proceedings, are limited to the audio-only capabilities of their cell phones.

The chapter proceeds as follows. Section 10.1 introduces the theory of “doing” unrepresented status, with an emphasis on the social production of unrepresented persons and the social construction of pro se status, orienting the reader toward the social-cognitive processes of judges, lawyers, and unrepresented persons. Section 10.2 describes persistent digital divides in the US. Section 10.3 reports results from empirical observations in virtual civil courts, including the surprising (to us) finding that low-income unrepresented persons are overwhelmingly using cell phones to dial into Zoom/Webex-based virtual hearings, limited to audio-only capabilities. Section 10.4 discusses our observations, considering the asymmetries in affordances, barriers, and constraints created by technological asymmetries and the impact of these asymmetries on the social cognition of judges, lawyers, and unrepresented persons.

10.1 Doing Unrepresented Status: The Social Production of Unrepresented Persons and the Social Construction of Pro Se Status

Over 15 million cases filed each year in our state civil justice systems involve one or more unrepresented persons,⁶ and the percentage of unrepresented people has risen rapidly in case categories where basic human needs are at stake, including evictions, family law, and debt collection cases.⁷ Many unrepresented persons are members of racially and socially disadvantaged groups.⁸ They encounter our civil justice system without legal representation to defend their basic civil legal rights.

The theory of doing unrepresented status⁹ posits the social production of unrepresented persons. That is, the very presence, and the vast percentage, of unrepresented persons within our civil justice system is not a fixed, natural, or inherent quality of that system.¹⁰ Rather, society produces unrepresented persons and the manner in which they appear, participate, and engage with our civil justice system through societal decisions and public policy choices – including public policy choices about the technologies that we employ to organize the civil justice system. These policy choices shape how unrepresented persons access and appear in the civil justice system, how they are perceived and socially constructed by court officials and other actors, and in turn, how they interact with others as a result.¹¹ These social dynamics create feedback loops, recursive processes, or self-fulfilling prophecies, in which expectations and social roles affect everyday interactions between persons within the civil justice system.

Second, the theory of doing unrepresented status posits the social construction of pro se persons.¹² That is, an unrepresented person’s pro se status is an active process, involving social cognitive processes (how we think and feel about others), social identity processes (how we think and feel about social identities), and behavioral processes (how we speak and act toward others) that people do and ascribe onto unrepresented persons. Legal officials impute and apply mental schemas, expectations, stereotypes, and beliefs about the characteristics of pro se parties onto people navigating the civil justice system without lawyers.¹³ This aspect of doing unrepresented status centers on the cognition, affect, and behavior of judges and lawyers toward these persons, and the intergroup interactions that unfold as a result within the civil justice system.¹⁴ Everyone with whom an unrepresented person comes into contact within the civil justice system makes use of shared meanings and mental representations about what it means for people, in general, to be pro se within the civil justice system and why they are unrepresented. These shared meanings invariably shape how unrepresented persons are perceived and the interactions that unfold between unrepresented persons and others within the civil justice system. Many judges, lawyers, and court officials hold subtle (and sometimes overt) negative attitudes about unrepresented persons. Moreover, merely being unrepresented can serve as a justification for treating unrepresented persons poorly, particularly those who are racial/ethnic minorities or who belong to socially disadvantaged groups.

Finally, the theory of doing unrepresented status also posits that different classes and groups of unrepresented persons will experience pro se status somewhat differently.¹⁵ For example, these structural and psychological processes may unfold differently for persons who belong to advantaged societal groups who are on the “have” side of the digital divide than for low-income persons who belong to racially or socially disadvantaged groups on the “have-not” side of the digital divide.¹⁶

10.2 Doing Pro Se Status in Online Court: Persistent Digital Divides

How the digital divide impacts virtual court proceedings, especially given the technological asymmetries among represented and unrepresented parties, is a critical but unanswered question.¹⁷ The digital divide and differential access to modern information technology (e.g., internet communication technology, computing technology, high-speed internet) impinges on the ability of low-income Americans to participate in important dimensions of modern social-political life online, including: learning, seeking out employment, working, identifying and obtaining social services, and participating in democratic institutions.¹⁸ Americans find themselves increasingly separated into “digital haves,” with easy and fluent access to information technology, high-speed internet, and technical savvy, and “digital have-nots,” who rely primarily on smartphones for internet access, or the “smartphone dependent,” often with interrupted and low-quality connections.¹⁹

Troublingly, given these existing digital divides, the shift from in-person to virtual proceedings may exacerbate societal inequalities in the courtroom. In other words, if many courtrooms are using Zoom/Webex videoconferencing technologies, many low-income unrepresented persons may not have the stable access to internet communication technologies necessary to fully participate in hearings that affect their life outcomes.²⁰ Consistent with the theory of doing unrepresented status – and the social production of unrepresented persons in particular – we posit that these first-order digital divides lead many low-income unrepresented persons to use cell phones to dial into Zoom/Webex hearings with audio-only capabilities, rather than videoconferencing capabilities. These unrepresented persons who access Zoom hearings in audio-only form would visually appear to judges and lawyers in these Zoom hearings as depersonalized black Zoom tiles.²¹

10.2.1 First-Order Digital Divide(s): Access to Technology and Stable Internet Connection

Many unrepresented persons – indeed, those facing the most economic precarity – do not have reliable access to the Internet or the videoconferencing technologies to fully participate in virtual hearings. According to the Pew Research Center, many low-income Americans rely on their cellphones to access the Internet and are “smartphone-dependent” internet users, meaning that they access the Internet on their cellphones and do not have broadband internet at home. About one-in-three do not have a cell phone at all. Moreover, there are substantial disparities in access to internet broadband and computers at home,²² with Black, Hispanic,²³ and rural²⁴ households residing on the “have-not” side of the digital divide.

Troublingly, bridging these first-order digital divides by providing initial access may not be enough to ensure true, reliable, material access or meaningful participation. Material access is a multidimensional construct,²⁵ and the ongoing struggle to ensure material access may be better understood through a lens of technology maintenance.²⁶ Technology maintenance refers to the burdens of time, energy, and money required to maintain digital access even after ownership of a cell phone.²⁷ Technology maintenance practices that limit functionality include: counting cell phone minutes to avoid “going over”; switching between cell phones depending on minutes; or “beeping” (calling and hanging up) to communicate without minutes.²⁸ Moreover, users share cell phones with family members, which requires maintenance of personal relationships.²⁹

While most low-income Americans have intermittent access to the Internet, this access is often unstable and characterized by frequent periods of disconnection and cycles of reliable unreliability.³⁰ Low-income Americans contend with temporarily disconnected service, broken hardware, and barriers on public access. These disruptions diminish access to unemployment, healthcare, education, and social support.³¹

10.2.2 Second-Order Digital Divide(s): Inequalities in Technological Capabilities and Efficacy

The persistence of a second-level digital divide³² refers to the fact that differences in digital proficiencies produce inequality, often revealed by limited digital literacy or efficacy in navigating the web.³³ Barriers to first-order access and the frictions of technological maintenance compound to produce negative attitudes toward, and perceived lack of utility of, the Internet.³⁴ Relatedly, low-income Americans who lack a computer at home experience higher emotional costs than others when using computing technology. That is, barriers on home computers engender psychological friction toward computing technology.³⁵ Undoubtedly, first-order structural inequalities contribute to a vicious cycle: Structural inequalities produce second-order digital divides by reducing technological efficacy, creating psychological friction, and affecting the type and quality of online activity,³⁶ ultimately conditioning the benefits of being online.

10.3 Observations in Virtual Court

In spring 2020, we engaged in over 500 structured observations of virtual proceedings in Indiana in small claims courts among 20 Indiana judges who handle high volumes of small claims cases, debt-collection cases, and evictions online. Within these observations, our research team observed that the vast majority of low-income unrepresented persons are dialing into Zoom virtual hearings with their cell phones. The vast majority of these cases involve representational asymmetries in which opposing counsel has the full video capabilities of Zoom, while these unrepresented persons are limited to audio capabilities. In many instances, these unrepresented persons are members of racial and ethnic minorities, as judged by their paralinguistic intonations on the phone. These preliminary findings suggest that the effects of moving to virtual proceedings, both benefits and costs, are not evenly distributed between the “have” and “have-not” sides of the digital divide or between lawyers and low-income unrepresented persons. We now turn to the preliminary findings of this first phase of our multi-phase research program.

10.3.1 Study Overview

Method. A team of six law student observers at the Indiana University Maurer School of Law and Stanford Law School engaged in structured observations of over 500 live-streamed virtual proceedings among twenty Indiana judges who handle high volumes of small claims cases (e.g., evictions, debt collection, small claims) online. These observations were conducted between March 1 and April 23, 2021 (a seven-week window). These observers accessed the virtual hearings via the Indiana Office of Court Service’s live-streaming website. To ensure that these observations focused on small claims, debt-collection, and eviction cases, these observers accessed the courts’ public daily hearing calendars and private weekly hearing calendars provided by the Indiana Office of Court Services. A detailed coding scheme was developed, and these law students were trained over the course of two weeks on how to implement this coding scheme. The observation data was inputted via a Qualtrics survey.

Measures. For purposes of this chapter, which reports preliminary results, we report three coded measures: (1) Represented by an attorney? (2) Dialed in by phone to virtual hearing (e.g., Phone number on Zoom tile or only voice heard)? and (3) Camera on? The observers coded these features of each of the over 500 live-streamed hearings, indicating in categorical terms whether these features occurred: yes, no, unsure, NA.

Data preparation. Data was entered in Qualtrics, and analyses were performed in R version 4.0.2. The full dataset of live, virtual proceeding observations included n = 503 observations, and included hearings without a subject matter indicator. These miscellaneous hearings were removed from the dataset, and the dataset was narrowed to n = 455, which included observations of small claims cases, debt-collection cases, and evictions. Next, n =106 of these 455 cases were observed by multiple law students. Accordingly, we developed an inter-rater coding analysis strategy in which data in the above-mentioned measures were retained for purposes of analysis when a majority of these multiple observers agreed when resting whether (1) a party was represented or not at the virtual hearing, (2) a party dialed into the hearing on their phone or not, or (3) a party’s camera was on or not. In the vast majority of instances, coders agreed about these aspects of a party’s appearance at the hearing. After removing the duplicate observations from the dataset, n = 349 unique observations remained. Regarding the subject matter of these cases, these n = 349 cases entailed eviction cases (n = 150), debt-collection cases (n = 103), small claims cases (n = 90), and other cases (n = 6) appearing on these high-volume dockets.

10.3.2 Preliminary Results

Representational asymmetries. We first analyzed representational asymmetries (n = 349), and in doing so, we categorized parties as represented if a lawyer appeared in their case and classified cases in which defendants/respondents defaulted as cases in which they did not have counsel. As anticipated and consistent with the literature (Figure 10.1), a majority of hearings involved representation asymmetries in which plaintiffs/claimants were represented and defendants/respondents were not (n = 209, 59.9 percent). Defendants/respondents were rarely represented (n = 5, 1.4 percent). Both parties were unrepresented in nearly 40 percent of cases (n = 135, 38.7 percent).

Figure 10.1 Virtual proceedings represented status

Technological asymmetries. We first analyzed technological symmetries in a manner that included defaults by defendant/respondents and no-shows by plaintiffs/claimants (n = 338). As revealed in Figure 10.2, the most notable observation when including defaults and no-shows is that, despite the apparent conveniences provided by remote proceedings, defendants/respondents nevertheless default in approximately 55 percent of cases (n = 186, 55.0 percent), whereas plaintiffs/claimants rarely no-show (n = 6, 1.8 percent).

Figure 10.2 Virtual proceedings matrix of tech asymmetries (including defaults)

While this apparently reflects a decrease in the default rate, the conveniences provided by remote hearings are not a panacea for addressing the challenge of defaults in these cases. Over half of defendants/respondents still default in these cases; as such, the conveniences of remote proceedings may need to be coupled with other interventions that discern and more effectively address the underlying reasons why many defendants do not to attend court hearings.

Turning now to Figure 10.3, which describes virtual proceedings where both plaintiffs/claimants and defendants/respondents actually attend (i.e., excluding defaults) (n = 149), we found that a majority of these hearings involved scenarios in which defendants/respondents dialed into these Zoom/Webex hearings on their cell phones (n = 96, 64.4 percent). Many of these instances involved technological asymmetries in which the plaintiff had full Zoom virtual capabilities and the defendant/respondent dialed into the hearing (n = 56, 37.6 percent). Rarely did the technological asymmetry favor the defendant/respondent (n = 14, 9.4 percent). In many instances, the parties both dialed into these hearings, despite the possibility of appearing virtually on Zoom (n = 40, 26.8 percent). Both parties appeared virtually in a minority of cases (n = 36, 24.2 percent). Finally, we also revealed instances in which a party appeared via Zoom with their camera off, which is distinct from dialing in per se. In these scenarios, for example, a person would be able to see others on Zoom, but their camera would be turned off and they would not be able to be seen. This occurred in an extremely small fraction of cases (n = 3, 2.0 percent). In these cases, the defendant/respondent had turned their camera off, whereas the plaintiff/claimant had their camera on, another technological asymmetry.

Figure 10.3 Virtual proceedings matrix of tech asymmetries (excluding defaults)

Representational asymmetries × technological asymmetries. We then focused specifically on cases in which lawyers appeared for the plaintiff and unrepresented defendants appeared in these remote hearings (n = 96). This analysis (Figure 10.4) reveals ways in which representational asymmetries compound with technological asymmetries. In other words, the technological asymmetries are even more pronounced when plaintiffs with lawyers face unrepresented defendants.

Figure 10.4 Virtual proceedings matrix of tech asymmetries lawyers versus unrepresented/SRL defendants

As reflected in Figure 10.4, we found that a majority of these hearings involved scenarios in which unrepresented defendants/respondents dialed into these Zoom/Webex hearings on their cell phones (n = 68, 70.8 percent). Nearly half of these cases involved technological asymmetries in which plaintiff lawyers had full Zoom virtual capabilities while unrepresented defendants/respondents dialed into the hearing (n = 45, 46.9 percent). Rarely did the technological asymmetry favor unrepresented defendants/respondents (n = 6, 6.2 percent). In many instances, both a lawyer and an unrepresented defendant dialed into these hearings (n = 23, 24.0 percent). Both parties appeared virtually in a minority of cases (n = 20, 20.8 percent).

Again, we also revealed instances in which either the lawyer or unrepresented defendant appeared via Zoom with their camera off, which is distinct from dialing in. Although this rarely occurred (n = 2, 2.1 percent) and, when it did, it was the unrepresented defendant/respondent whose camera was off, and the plaintiff lawyer whose camera was on, compounding the technological asymmetries.

10.3.3 Discussion

In summary, we found that a majority of low-income defendants/respondents in these virtual hearings are unrepresented and most are dialing into virtual court (e.g., Zoom/Webex hearings) on their cell phones. These cases involve representational asymmetries, in which repeat-player plaintiff lawyers litigate against low-income defendants who are unrepresented. Troublingly, these cases also involve technological asymmetries, in which repeat-player plaintiff lawyers regularly employ the full range of virtual interaction and videoconferencing capabilities of Zoom/Webex, while low-income unrepresented defendants whom they sue are often limited to the audio-only capabilities of their cell phones.

10.4 Unrepresented in Virtual Court: The Social Production of Unrepresented Persons

Drawing on these findings, we now return to our framework, organized around Winner’s core insight that “the complex interaction between law, technology and human institutions … may lead to unanticipated and adverse social policy outcomes.”³⁷ In this section, we turn first to the social production of unrepresented persons in virtual hearings and discuss the situational affordances and barriers, and technological features and constraints, entailed by virtual hearings and how they may differentially affect lawyers and unrepresented individuals in virtual courtrooms. Then we turn to the social construction of unrepresented persons in these virtual hearings and discuss ways in which the social cognitive processes of judges, lawyers, and unrepresented persons are likely influenced by these asymmetries.

By way of background, our civil justice system presents persons navigating within the system with situational affordances and barriers, that is, conditions that prompt or permit some actions and conditions that conceal or foreclose others.³⁸ Often people are not consciously aware of the influence of these situational affordances and barriers; nevertheless, these conditions powerfully guide and constrain behavior, and influence how this behavior is understood by oneself and others. These conditioning factors include the use of technology in virtual hearings. In this regard, theories of mediated communication explain the relationship between features of these technologies, affordances, and the communication that ultimately results from using those technologies.³⁹ These mediated communication theories reveal that videoconferencing technologies (e.g., Zoom/Webex) and audio-only technologies (e.g., speaking over the telephone) entail qualitatively different features, affordances, and constraints. For example, these different modalities alter the range of communication possible – including whether facial expressions, head nods, gestures, gaze, and visual perception can occur – in turn, altering the process, content, and outcome of communication possible.⁴⁰

We focus first on the asymmetric affordances and constraints that shape how lawyers and low-income persons access and appear in virtual courts – that is, how technology produces unrepresented persons. Following that, we turn to how unrepresented persons are perceived by judges and other courtroom actors – that is, how technology constructs unrepresented status in the eyes of others. To raise just one possibility, might a judge’s motivations, perception, and empathy be shaped by an asymmetry in which a lawyer appears in a hyper-personalized visual form, while a low-income unrepresented person is depersonalized into a black Zoom tile in the virtual hearing?

10.4.1 Overview: Social Production of Unrepresented Persons

The civil justice system presents courts, lawyers, and unrepresented persons with a set of situational affordances and barriers.⁴¹ In this section, we will examine the ways in which virtual courts asymmetrically allocate situational affordances and barriers, and technological features and constraints, to lawyers and unrepresented persons. For example, lawyers can engage in fully virtual interactions, where they are able to hyper-personalize and can also Zoom in from staged law offices with reliable high-speed internet connections. Lawyers can also gaze directly into the camera – simulating eye contact with the court – while also using and perceiving nonverbal behavior to persuade. In contrast, low-income unrepresented persons who dial into Zoom court on their cell phones can only speak and hear from a distance, are often depersonalized into a black tile on the screen, cannot use or perceive nonverbal behavior, and are unable to use or perceive documents in Zoom hearings. These conditions and constraints are highly skewed and appear to exacerbate asymmetries between lawyers and unrepresented persons in virtual courts.

10.4.2 Lawyers

Situational affordances and technological features. Virtual courts provide lawyers a variety of situational affordances and technological features that may enhance their efficiency and effectiveness.

Virtual courts reduce the time and cost borne by lawyers who would otherwise have to travel to court and wait in courtrooms to attend in-person proceedings.⁴² As a result, lawyers can reallocate this time to prepare for other cases and multitask while waiting for their virtual hearings to be called, which we observed. Moreover, lawyers often have stable, reliable internet access in their law offices and homes, and these home and law offices often contain legal resources, equipment, and staff – for instance, case files on computers, phones, fax machines, scanners, access to online legal databases, and administrative support – not available to lawyers physically present in courtrooms. We observed an instance, for example, in which a judge asked a lawyer for information specific to a case, which the lawyer did not have in hand but was able to obtain after a brief pause from a colleague in an adjacent room during the hearing.

Second, research has revealed that the inclusion of gaze awareness and upper-body nonverbal cues in a video frame may engender empathy.⁴³ High-quality videoconferencing systems that preserve gaze and upper-body cues have been found to be as effective as face-to-face meetings in preserving empathic concern. However, when systems do not preserve these cues, empathy and rapport are degraded.⁴⁴ The challenge, again, is the asymmetry: lawyers are more likely to have this high-quality videoconferencing technology than low-income unrepresented persons who dial into these hearings.

Finally, Zoom virtual hearings allow lawyers and others with the most technological capital, capabilities, and expertise to enhance their self-presentation above and beyond what may have been possible in an in-person hearing. This phenomenon is referred to as hyper-personalization.⁴⁵ Lawyers can carefully curate their online impression in Zoom hearings, using filters to soften and touch up their images, placing their names on Zoom tiles, and by staging their background (whether actual or virtual).

Barriers and constraints. As many lawyers have stable, reliable high-speed internet access and the technologies necessary to participate in Zoom proceedings effectively from their home or law offices, the shift from in-person to Zoom hearings appears to impose few situational barriers. Furthermore, lawyers who Zoom into virtual hearings face few technological constraints as compared to low-income unrepresented persons who dial into Zoom hearings. These lawyers will often have access to videoconferencing equipment that preserves their gaze awareness and nonverbal behavior and have the ability to hyper-personalize their self-presentation.

10.4.3 Unrepresented Persons

Situational affordances and technological features. Like lawyers, unrepresented persons may gain conveniences, including reduced travel and child-care burdens.⁴⁶ They may also enjoy the comfort of attending Zoom hearings from home or work (rather than attending court in person). Indeed, the Self-Represented Litigation Network has noted that virtual court proceedings may reduce the time and expenses associated with traveling, transportation, childcare, and other day-to-day costs that litigants incur when going to court.⁴⁷

Relatedly, we observed instances where at least some unrepresented persons who attended these virtual hearings behaved quite confidently, perhaps more confidently than would be the case within an in-person hearing. This may be because, for some unrepresented persons, the convenience and lack of formality may decrease the sense of intimidation that may be present in an in-person hearing, an avenue for future research.

These conveniences may be translating to higher appearance rates, as suggested by the National Center for State Courts.⁴⁸ Yet caution is warranted before celebrating these court statistics.

For example, when a low-income person dials into a Zoom courtroom on a cell phone, this audio-only entry is counted as an “appearance.” However, these low-income persons can neither see nor be seen by other court participants, unlike the lawyers who Zoom into these virtual courts. They are unable to perceive the facial expressions and nonverbal behaviors of other courtroom actors or to review documents used by lawyers and judges in these virtual hearings. In short, not all “appearances” are appearances in the conventional sense of what it means for something to appear to someone as an object of sight perception. In the future, we should consider the utility of moving beyond a strict dichotomy of whether a party “appeared” or not, and consider a construct that considers a continuum of the qualities of what it means for a person to appear in court. Certainly, this continuum will lend itself to many important questions that go beyond mere access, centering on equity and the experience of attending court whether online or in person.

Barriers and constraints. Unlike lawyers, the shift from in-person to Zoom hearings imposes notable situational barriers and technological constraints on low-income persons.

First, unrepresented persons must prepare exhibits and documents in advance of hearings. While these documents are filed before Zoom proceedings, courts use these documents within the proceedings themselves. When low-income persons dial into Zoom proceedings, they are unable to see the court or documents shared by or with the court during the hearing. We observed that this led to miscommunication about documents (and negative outcomes) during Zoom hearings.

Second, the shift to Zoom removes situational affordances available to low-income people who attend court in person: mainly, access to in-court self-help ecosystems. This shift may impair the ability of navigators, self-help professionals, and legal-aid providers to help unrepresented persons. Relatedly, in immigration and criminal proceedings, lawyers have experienced difficulty meeting and privately conferring with their clients before virtual hearings.⁴⁹ Moreover, when low-income persons dial in to Zoom proceedings, they lose the ability to observe others and learn how the full complexity of the courtroom unfolds. While this may be of little value to lawyers, unrepresented persons often learn by watching. Without this opportunity to learn by watching, many unrepresented persons may not understand the process or the expectations of the court, which may decrease the effectiveness of their self-representation.⁵⁰

Third, most low-income unrepresented persons access the Internet via cell phones that are, themselves, reliably unreliable.⁵¹ Relatedly, many low-income Americans who have cell phones are on pay-as-you-go data plans and cannot afford to pay for the data required to attend. When these low-income Americans dial in to these hearings, they are depersonalized into black Zoom tiles in the hearing, set against a black Zoom backdrop, often with a case number (or phone number) attached to the Zoom tile. Many other low-income persons do not appear on the screen at all; rather, these Zoom tiles are hidden from the screen, and judges and lawyers merely hear their voice. For these persons, aside from this auditory presence, there is no sign that these unrepresented persons appeared at hearings at all.

10.5 Social Construction of Pro Se Persons

This section turns to the way in which the asymmetric affordances, barriers, and constraints present in these virtual proceedings may influence the social cognitive processes and social perception of judges, lawyers, and unrepresented persons. We present a model of these social cognitive processes and the ensuing civil justice interactions, with an emphasis on the contrast between in-person and virtual court proceedings in Figure 10.5. In this section, we outline the possible implications of our findings to date for unrepresented persons exhibiting digital disparities in court proceedings and underscore areas that we will seek to address in future stages of this research.

Figure 10.5 Model of civil justice interactions and social cognitive processes between judges, lawyers, and unrepresented persons in in-person and virtual court proceedings

10.5.1 Judge’s Perspective

From the judge’s perspective, judges can only see and be seen by the lawyer. From the judge’s vantage point, low-income unrepresented persons who dial into Zoom hearings appear as a black Zoom tile with a case ID or phone number appended to the black tile. As such, the asymmetries created by this technology may, despite the well-meaning of judges, subtly affect their impressions, empathy, and motivations. These affordances and barriers will alter the judicial role.

Motivation. The shift from in-person proceedings to Zoom virtual hearings may affect the motivation and goals of judges and court personnel who operate under severe resource constraints. While courts have shifted to a therapeutic or problem-solving orientation when addressing in-person cases, including evictions,⁵² the shift to Zoom court may affect this orientation. When low-income unrepresented persons dial into a Zoom virtual hearing, they appear as black Zoom tiles with a phone number (or merely a case ID), and this may hinder the empathic concern necessary for a therapeutic or problem-solving orientation.

Perception and impressions. Video-mediated communication alters the way people are perceived and the impressions formed.⁵³ In this context, unrepresented persons who appear in Zoom virtual hearings via video, rather than in person, may be perceived as less warm and competent than those who appear in person, especially relative to the lawyers who appear virtually in court.⁵⁴

Cognitive depletion. “Zoom fatigue” is depleting because video conferences are cognitively demanding, requiring one to “focus more intently on conversations in order to absorb information,” as opposed to the nonverbal cues we usually rely upon.⁵⁵ Relatedly, Zoom participants have the ability to watch oneself during these video conversations. Yet seeing one’s own video generates a state of objective self-awareness, which may increase the cognitive load of engaging in these technologies, and may impact a person’s interactions in a videoconference.

Empathy. These technologies also affect the empathy expressed and experienced. Facial expressions, gaze awareness, and nonverbal behaviors build trust and empathy between people, and they affect person-perception as well. When these technologies interrupt or conceal these nonverbal behaviors, empathy may be reduced. For example, the video framing of cell phones (if video is available at all) and a stable mounted computer will have different effects on the inducement of empathy⁵⁶ because the video framing of stable mounted computers may capture these nonverbal features of the upper body and correct for gaze error. Moreover, empathy is more easily generated between people who have ongoing relationships or frequent conversations; thus, strangers are at a distinct disadvantage when presenting over video.⁵⁷

Digital inequalities between lawyers and many low-income unrepresented persons may translate into disparities in the ability to gaze at the judge during these virtual hearings. Gaze awareness is an important factor that affects whether people are perceived as generally interested, trustful or approving, or attentive.⁵⁸ Gazing is an important expression of interpersonal attitude or affect. Indeed, lawyers are taught to gaze in order to enhance their persuasion,⁵⁹ ingratiate themselves to the judge and jury,⁶⁰ or assert dominance over opposing witnesses and parties.⁶¹ Because those who dial into these Zoom proceedings are unable to gaze at the judge or opposing lawyer, they may be construed as being “defensive” or “evasive.”⁶² Moreover, eye contact is an important ingredient to social interactions and may prompt recursive processes of trust and rapport, whereas an inability to gaze may generate distrust and harm rapport in intergroup encounters.

The increased psychological distances that these technologies create may lead to depersonalization or, in the worst scenario, dehumanization.⁶³ This may be in part because these technologies may shape the way others are construed: whether they are construed more abstractly or individuated, whether they are experienced as close or far,⁶⁴ which may impact depersonalization. The risk in the scenario at hand is that low-income unrepresented persons who dial into these Zoom virtual hearings may be depersonalized, that their appearance in a Zoom tile with a number and a disconnected voice may subtly dehumanize them in the eyes of the court officials and lawyers.

Behavior. At least two studies suggest that Zoom virtual hearings may elicit faster interactions and decisions than in-person hearings. That is, that the discrete hearing time is faster than would otherwise be the case because of the social-cognitive dynamics produced by the technology employed. This was observed, for example, in the impact of videoconferencing in judicial decision-making about deporting immigrants⁶⁵ and is documented in research on the effect of videoconferencing on team performance.⁶⁶

Contingent nature of the judicial role. Interactions between judges, lawyers, and unrepresented persons and their performances in the courtroom are contingent on the technologies employed within the civil justice system.⁶⁷ These court performances are shaped, in part, by the technological capital of these various actors.⁶⁸ For example, Rowden and Wallace, in studying the introduction of videoconferencing in Australia, found that the introduction of this technology had “a profound impact on the production, management and consumption of judicial images, [which] has implications for the judge’s in-court role both as traditionally conceived and in practicing new types of therapeutic jurisprudence that require increased emphasis on engagement with other court participants.”⁶⁹ In general, virtual hearings are associated with more distant or impersonal communication. Yet the introduction of these technologies has occurred at a time when there has also been a strong move toward more engaged styles of judging.⁷⁰

10.5.2 Lawyer’s Perspective

Like the judge, but unlike low-income persons who dial into these Zoom hearings, a lawyer will be able to see and be seen by the judge. This will affect their adversarial orientation and potentially exacerbate asymmetries against unrepresented people. These asymmetries may affect opposing lawyers, who are in an adversarial orientation, making it more likely for them to use nonverbal behaviors and documents that unrepresented people are unable to see. It may also lead them to dehumanize these unrepresented persons.

Initial face-to-face interactions and preexisting relationships. Initial face-to-face meetings are crucial for enhancing later virtual interactions.⁷¹ Research on distributed teams in the business context reveals that conflict is mitigated by in-person meetings followed by regular video conferences, which can help to maintain a cohesive team and a sense of shared identity. One leading study noted that people who met in person before video-mediated meetings were better at establishing trust with other group members than those who had not met beforehand.⁷² Another likewise found evidence that initial in-person contact could benefit later virtual conferences.⁷³ This research suggests that video conferences may be more effective for lawyers who are already acquainted with judges and have preexisting relationships with them.

10.5.3 Unrepresented Person’s Perspective

Finally, unlike judges and lawyers, an unrepresented person who dials into a Zoom hearing cannot see or be seen, and they appear as a black Zoom tile on the judge’s and lawyer’s computer screens. This may affect their participation, experience of justice, and the outcomes obtained.

Construal and meaning-making. When low-income unrepresented persons dial into Zoom virtual hearings, they have access to audio-conferencing capabilities only and are unable to see a courtroom at all. This will undoubtedly affect the sense of realism, solemnity, and gravity of the proceedings, when compared to in-person or videoconferencing enabled proceedings. This may leave them apathetic or confused, experiencing the process as less “real.” Moreover, friction and barriers accessing these Zoom virtual courtrooms may lead unrepresented persons to infer that these virtual court proceedings are not truly designed for people like them.

Experiences of procedural justice. Research suggests that in-person participation may be perceived as more procedurally just than technologically mediated participation.⁷⁴ For example, research in organizational justice has concluded that applicants were less attracted to organizations that used video interviews compared to in-person interviews.⁷⁵ Other studies have noted that in-person interviews were regarded as fairer than video-mediated interviews, resulting in higher levels of job acceptance.⁷⁶ In still another study, interviewees rated their interviewers as less friendly during the video-mediated interviews (in comparison to in-person and telephone interviews).⁷⁷ This research suggests that some unrepresented persons may experience videoconference proceedings as less procedurally just than in-person proceedings. Extrapolating this research a step further, one can infer that unrepresented persons may find it procedurally unjust to be limited to audio-only capabilities when their adversaries have access to the full range of video-conference capabilities.

Relational feedback, turns, interruptions. Physical proximity supports the interaction and cohesion of groups.⁷⁸ This is, in part, because of bandwidth and network cost limitations that reduce the rate, clarity, and frequency of communicative turns.⁷⁹ Because low-income unrepresented persons are unable to observe or communicate with nonverbal behavior, this may exacerbate miscommunication, while at the same time making judges, lawyers, and unrepresented persons slower to correct these misunderstandings.⁸⁰ Indeed, we observed several instances in which this kind of miscommunication occurred for unrepresented persons who were not proficient in English. Unfortunately, these unrepresented tenants dialed into Zoom court and were not able to overcome the language barrier. Similar issues may occur for persons with disabilities, though virtual proceedings may also increase access for persons with mobility-impairing disabilities as well.⁸¹

One challenge is that these faster hearing times may be coupled with more problematic intergroup interactions. The asymmetries in these interactions may harm intergroup interactions in virtual environments. For example, many judges and lawyers are majority group members, while many low-income members are racial or ethnic minorities or belong to vulnerable groups. Past research has found that an audiovisual lag in an interaction may incite tension in intergroup interactions, particularly when persons are not well acquainted.⁸²

Participation. If unrepresented persons experience the process as procedurally unjust, their participation and engagement may be dampened. Indeed, researchers have suggested that videoconferencing technologies may have prompted declines in participation, which may have explained adverse outcomes in research involving bail decisions⁸³ and immigration removal decisions.⁸⁴

Contingent nature of unrepresented persons. Finally, these technologies and the digital inequalities engendered reveal the contingent nature of being a self-represented litigant in the civil justice system. As has been described, the very act of appearing in court is altered and dependent on the technologies employed within these proceedings. At the same time, this technology may benefit the most advantaged unrepresented persons who have technological capital, capacity, and wherewithal. Technological capital is a subset of, and an addition to, Pierre Bourdieu’s cultural, economic, and social forms of capital in the information age,⁸⁵ marked by first-order and second-order digital divides in internet access, skill, and experience.⁸⁶ These societal patterns may, in part, explain why so many unrepresented persons dial into Zoom virtual hearings from their cell phones without videoconferencing capabilities.

10.6 Conclusion

In this chapter, we sought to illuminate how virtual proceedings unfold for low-income persons in the everyday by examining how these new technologies affect the experiences of low-income persons who encounter, and contend with, adversities within virtual court proceedings. Our preliminary findings revealed troubling phenomena in many small claims cases, including eviction and debt-collection cases, winding through virtual court proceedings in Indiana. We found that a majority of low-income persons in these cases are unrepresented, and most are dialing into virtual court (e.g., Zoom/Webex hearings) on their cell phones. The vast majority of these cases involve representational asymmetries, in which repeat-player lawyers litigate against low-income persons who are unrepresented. Of concern, many of these cases also involve technological asymmetries, in which repeat-player lawyers regularly employ the full range of virtual interaction and videoconferencing capabilities of Zoom/Webex, while the low-income unrepresented persons whom they sue are often limited to the audio-only capabilities of their cell phones.

We believe that examining how virtual proceedings unfold in the everyday contributes to the development and refinement of accurate and useful theories about our dynamic civil justice system and best practices for enhancing access to justice in virtual proceedings.

11 Online Dispute Resolution and the End of Adversarial Justice?

Norman W. Spaulding

There was a moment in the late-nineteenth and early-twentieth centuries when automobiles were being made with steam, electric, and internal combustion engines. As early as the 1840s, inventors had created “[r]echargeable batteries that provided a viable means for storing electricity onboard a vehicle.”¹ Porsche’s first car was an all-wheel-drive electric car that “set several records” in time and distance competitions, and by 1897 a fleet of taxis built by the Electric Carriage and Wagon Company of Philadelphia was running in New York City.

The internal combustion engine won out because of a conjunction of factors. Henry Ford figured out how to produce and sell the Model T at a price half that of standard electric vehicles. Charles Kettering made crankshaft starters obsolete. And the discovery of large petroleum reserves in Texas dramatically reduced the price of gasoline. The steam engine, on the other hand, took far too long to warm up – no one wanted to wait forty-five minutes before hitting the road. And although electric cars were cleaner, quieter, and initially easier to start than cars with internal combustion engines, they “disappeared by 1935,” as did the kind of investment and research that would have improved their performance and affordability. They disappeared even though scientists knew, as early as the 1850s, that pumping CO₂ into the atmosphere would affect the earth’s temperature.²

Knowing what we now know about the devastating effects of climate change and other negative externalities of crude oil extraction, one can’t help but wonder about what the counterfactual world of a century powered by electric vehicles would have looked like. The question is for the most part unanswerable – perhaps we would have had a century of lithium wars rather than oil wars. But it is hard to escape the feeling that almost any outcome would be preferable to the world of irreversible climate change in which we now live.

I raise the forgotten story of electric vehicles because it draws into relief an important feature of transformative innovation that is all too often obscured once path dependence and the leverage of market dominance set in. In the moment, there are often many design options, not just one obviously superior alternative, and the full cost (including negative externalities) of any one option can be difficult to calculate. But it is gravely irresponsible not to inquire what that cost might be when design options are still open and policy affecting incentives is being determined. Whatever one might have thought about this responsibility in a time before our own – eras preceding climate change, nuclear holocaust, and other apocalyptic consequences of technological innovation – we do not have the luxury of failing to inquire now.

The tech evangelism that reigns in Silicon Valley inhibits precisely this inquiry.³ Uber’s proponents spoke with religious fervor about the corrupt monopoly of cab companies and how that arbitrarily hindered both the mobility of customers and the autonomy of cab drivers. Very little was said about whether disrupting the industry would, on balance, be socially beneficial. But as it turns out, one of the negative externalities is likely diminished use of public transportation,⁴ with attendant effects on climate change and declining resources for innovation in public transportation. Moreover, Uber increasingly behaves toward consumers and drivers like the very monopoly it “disrupted.”⁵ In other ways, the company’s conduct is even more ominous. As one commentator has observed, “if you are one of its regular customers, Uber knows more about you than your own mother does.”⁶ And there are grounds to worry that the company’s use of these data is not entirely benign.⁷ Remarkably, despite its market valuation, the company has yet to prove it can turn a profit. It is far more convenient to hail a ride, and in this sense “access” to a form of transportation has increased. But the cost side of the ledger, as with other forms of “surveillance capitalism,”⁸ is daunting.

A third cautionary tale closer to the innovations in legal automation and access to justice I address in this chapter is TurboTax, software that has arguably revolutionized tax filing. As with taxi drivers and Uber, many accountants have either been displaced by Intuit’s product or incorporated it into the services they provide. For consumers, a process fraught with uncertainty has been made more accessible and efficient. On the other hand, Intuit has repeatedly used its market leverage and lobbying power to prevent states and the federal government from adopting legislation that would make free “prefilled” tax forms automatically available to taxpayers.⁹ The so-called disruptive innovator has become yet another monopoly rent seeker, blocking innovations that would be even more accessible, transparent, and consistent with the public good.

The three examples are commonsense reminders that some forms of innovation are transformative in ways we may (predictably) regret, that the rhetoric and fervor surrounding disruptive innovation can obscure sober assessment of the cost side of the ledger, that some transformations saturated with negative externalities become irreversible, and that the power reallocated by innovation – even innovation that increases access to a good or service – can be used to obstruct both broader public access and regulation.

Other examples could of course be given, enough to make the Panglossian enthusiasm surrounding artificial intelligence, legal tech, and online dispute resolution (ODR) smack of dangerously irrational exuberance.¹⁰ ODR’s moment, we are told, has arrived, “offer[ing] the promise of robust yet radically less expensive dispute resolution.”¹¹ Dispute resolution, we are assured, is no different from other sectors in which digital, online systems optimize information processing:

All forms of dispute resolution revolve around communication and information processing. For the Internet to be adapted to serve the needs of dispute resolution is no different conceptually from adapting the Internet to serve the needs of any other information intensive process, such as online banking, online auctions, online education, etc. Indeed, [these industries] often provide links on their home pages to dispute resolution systems.¹²

The excessive cost, delay, complexity, and confrontational culture of the adversary system, we are told, will be displaced by apps that resolve formal legal disputes as efficiently as eBay resolves auction disputes. In the most ambitious forms of ODR, there will be no more third-party mediators, arbitrators, or judges, and therefore no more conference rooms or courthouses.¹³

Justice will roll down in strings of code. Disputes suitable for ODR will not only be resolved cheaply and quickly; the conjunction of data mining, predictive analytics, and dispute systems design will help prevent disputes from arising in the first place.¹⁴ Academic conferences populated by scholars who are funded by or work in the very industry they write about are conducted with all the sobriety of an Elmer Gentry revival meeting. Skeptics are dismissed as unrepentant sinners – elitists too attached to the ancien regime to appreciate the miracles of the “internet society,” heartlessly indifferent to the crisis in access to justice, captive to self-serving, anachronistic ideas about the administration of justice. The capital offenders are judges and lawyers whose skepticism is dismissed as rationalization covering the prestige and monopoly rents they derive from the status quo. Fundamentally, law is not thought to be different from transportation or any other target of disruptive innovation: If you want to improve access, deregulate, disregard regulation that can’t be set aside, and expand competition by letting the information economy and disruptive innovation work their magic.

Anyone familiar with the history of professions knows that power struggles between professionals often involve characterizing an entrenched group of experts as corrupt and the newcomers (here, software engineers) as avenging angels whose primary care and concern is the welfare of others.¹⁵ New assertions of power are in this way masked by the discourses of progress and reform. At the same time, anyone familiar with the history of the Anglo-American legal tradition knows that legal elites have commonly and, it must be said, deservedly been targeted for many of the perceived flaws of the adversary system. The first movement to reduce law to code in America occurred in the early-nineteenth century, when Jacksonian populists launched an all-out assault on the complexity of common law pleading and the power of judges and lawyers.¹⁶ Drawing on the Napoleonic Code and the famous anti-lawyer tracts of Jeremy Bentham, they sought to replace the common law with a democratically enacted code. They simultaneously sought to expand access to the practice of law by eliminating standards for entry to the bar. Finally, they sought to make judges democratically accountable through popular election and recall – procedures that endure to this day in many states. This was the most pronounced anti-lawyer movement in American history, animated by a desire to make the law simple and more affordable. But it is scarcely the only one. Shays’ Rebellion pitted agrarian debtors against lawyers and judges who enforced the claims of elite creditors. The New Deal pitted progressive reformers and proponents of administrative agencies against conservative courts and the adversary system.¹⁷

What the anti-lawyer and anti-adversary system rhetoric of the current movement obscures is that the bar’s protectionist arsenal is weaker than it has been at any point since the Jacksonian populist threat more than a century ago. Indeed, both practically and doctrinally, the bar’s defenses have been decimated over the last fifty years. The network of price controls, minimum fee schedules, and restrictions on advertising and other rules that limited internal competition and “external” lay-lawyer combinations were dismantled by a series of landmark Supreme Court cases in the 1970s.¹⁸ Competitors in banking, accounting, and other fields renounced the “treaties” that kept them from offering competing services at the same time. The legal-form business expanded under the protection of First Amendment decisions insulating it from unauthorized practice rules.¹⁹ Mediators and especially private arbitrators now operate with the blessing of the Supreme Court, allowing corporations to use contracts of adhesion to displace millions of disputes from courts to alternative dispute resolution forums every year.²⁰

In fact, the status quo in access to justice is as much if not more the product of neoliberal defunding and restriction of legal services for the poor and defunding of state courts.²¹ Tellingly, some of the same players who never lifted a finger to help low-income Americans obtain meaningful access to the adversary system or support funding of the court system are now enthusiastically supporting ODR as a substitute.²² They are joined by liberal ethicists, lawyers, judges, and scholars who never much liked the adversary system to begin with – believing that ADR was the way of the future, that the New Deal vision of centralized, rational technocratic agency adjudication is more efficient and suitable to mass-processing of claims, or that, whatever the alternatives, adversary adjudication is morally flawed.²³ These are strange bedfellows, united by a shared desire to replace the adversary system – at least for people who cannot already afford it.

Once we understand the neoliberal aspects of the status quo, and liberals’ gradual abandonment of the goal of providing lawyers to poor people and funding courts, there is reason to question why ODR travels under the banner of access to justice and whether it will serve the people its advocates claim they care so much about. After all, if the interests of poor people were truly motivating these reforms, the law already recognizes the right of non-lawyers to create organizations that fund and coordinate not-for-profit legal services.²⁴ The failure to innovate in this space suggests that rent-seeking packaged in Silicon Valley “solutionism,”²⁵ not access to justice and the needs of ordinary people who stand before the law, is paramount in the current movement.

In the pages that follow I set the debate about AI and ODR on a different plane by granting that access to some form of “law” will be expanded. AI, data mining, predictive analytics, and the widespread use of mobile computing devices are generally superb tools for reducing the cost of large-scale bureaucratic and logistical tasks. They are already proving genuinely transformative in other sectors of the economy and society. There remain, however, questions about how the architecture of these information systems fits with basic ideas about the structure of due process and the rule of law in a pluralistic, democratic society. Ultimately, these are questions about what version of “law” ODR will increase access to and what kind of justice and what kind of legal subject are produced by these systems.

To begin with, ODR advocates and designers tell us there are many “simple” cases that don’t require adversary resolution, but when we look more closely, what we see is that simplicity is assumed from and defined by the monetary value of the case, not the simplicity of the issues involved or the social, moral, and economic stakes for the litigants and the public. Given that small value cases make up the vast majority of American litigation, ODR actually poses a direct challenge to the courts as sites of adversary adjudication for ordinary people. I take up the “simplicity” hypothesis in Section 11.1.

Section 11.2 describes the architecture of ODR that enables efficient mass processing and resolution of legal claims. Although ODR designers and promoters tell us that it is cheaper and faster than litigation and that it helps ordinary people with “simple” disputes, current ODR systems are cheaper and faster mainly because they replace decision on the merits with easier-to-code “interest-based” negotiated resolutions. Equally situated parties may reach mutually advantageous resolution on such platforms, but where the state or powerful creditors are pitted against unrepresented individuals, as is true in most small value claims, “interest-based” resolution may simply enhance collection compliance with respect to debts and other legal claims that the defendant has a right to resist. Far from expanding access to justice, ODR may rather ominously accelerate unwarranted compliance and legal subordination. When the government itself is a creditor, and court systems therefore profit from collection, the risk of conflicts of interest in adoption of ODR systems that the public cannot evaluate is especially acute. In other cases, even though ODR may be cheaper than litigation, fee-for-service structures appear designed to induce early resolution rather than merits resolution for people of limited means.

Finally, the conjunction of AI’s predictive analytic power and big data allows both public and private ODR system to achieve something dispute systems designers have long dreamed of: using data about existing disputes to prevent conflict in the future. As alluring as dispute prevention may seem in a conflict-ridden society, I argue in Section 11.3 that embedding dispute prevention and compliance into the architecture of the administration of justice through an automated system of surveillance and information control is inconsistent with human freedom. Asimov’s second “law of robotics” states that “a robot must obey the orders given to it by human beings,” not that humans must obey the orders of robots. Compliance-oriented and preventive ODR reverse this law, turning right holders into cogs in a machinery of compliance. I discuss alternative paths of ODR development and associated regulatory reforms to protect the due process rights of litigants, basic rule of law values, and the integrity of the administration of justice.

11.1 The Domain of ODR: “Simple” Cases?

They have no lawyers among them, for they consider them as a sort of people whose “profession it is to disguise matters; and therefore they think it much better that every man” should plead his own cause …. [T]he plainest meaning of which words are capable is always the sense of their laws. And they argue thus.

– Thomas More, Utopia

A foundational premise of current ODR systems is that there is a class of “simple” cases for which adversarial resolution is inappropriate, not least of which because the costs of the process exceed the value of these cases as measured by the size of the claim or judgment. The simplicity hypothesis has deep intuitive appeal. There are indeed many cases in which the costs of adversarial process exceed case value.²⁶ If these cases can be disposed of through an ODR system that does not require physical appearance in court, or even a judge, we are told, costs of adjudication are reduced for the state and perhaps for the parties. Resolution is faster and cheaper, giving the parties peace of mind sooner and the ability to move on with their lives. More complicated disputes might require the formalities of adversary procedure but due process can sometimes be provided without full judicial process. Finally, ODR will promote access to justice because it is precisely these simple cases in which ordinary people do not have access to counsel or avoid litigation altogether, believing that the game isn’t worth the candle. Ordinary people will thus be better off as ODR expands.²⁷

This simplicity/access nexus is pervasive in the ODR literature, the promotional materials of ODR vendors, and the webpages of court systems that have adopted ODR systems. One commentator observes that “the use of ODR to settle small claims and therefore free up judges and courtrooms for more complex cases is a given: ‘Small claims courts, with smaller dollar amounts and less complex issues, are ideally situated to transition their operations online.’”²⁸ ODR, the author continues, “has proven to significantly reduce the delays and costs normally associated with a court case by eliminating the need for travel and synchronous communications.”²⁹ Until the development of ODR, another advocate writes, “the average experience of a litigant ‘going to court’ amounts to … waiting in long lines” – if and when “a hearing actually begins, it is over almost at once. The outcome is generally predictable … as the decision is determined by standard pieces of information contained in the case file or provided by answers the litigant supplies.”³⁰ This is not only hugely inefficient, “access to justice is subverted by the fact that courts continue to operate on the age-old model.”³¹ The adversary system

makes much more sense for complex litigation in which credibility determinations … and diverse forms of evidence are standard fare. For disputes of this character, the costs of physically using a courthouse (even day in and day out) are relatively modest, if not negligible, given the stakes of the lawsuit .… But for minor disputes in state court, in which the stakes are at least initially fairly low and decisions can be made on the basis of papers and are usually straightforward, the tradeoff cuts deeply the other way.³²

Supposedly “[m]inor legal disputes” account for the majority of state trial court caseloads in the United States.³³ These include not only small claims cases between private litigants and landlord/tenant disputes, but “lesser misdemeanors and civil infractions” where the state is involved as the complainant or prosecutor.³⁴

The first problem with the simplicity/access nexus is the assumption that low value cases are in fact simple. They can be made to seem simple by comparison to more sophisticated causes of action, but for the parties involved in “simple” cases, this is an irrelevant comparator. For parties to a case, the judgment whether their case is simple rests on factors such as

• • whether they have dealt with similar disputes before and are familiar with the applicable law and procedure,

• • the relative value of the case as compared to their other assets and debts,

• • dignitary considerations linked to the harm they have suffered or are accused of causing as compared to other wrongs and emotionally charged problems they have dealt with,

• • dignitary considerations linked to the degree of participation and understanding litigants have about the process that results in resolution of a dispute

• • the capacity of designers of ODR systems to capture the interests of the parties, and

• • the actual merits.

With respect to the first consideration, an experienced landlord likely has dealt with tenant disputes in the past and can therefore navigate legal issues in a new dispute with some degree of comfort even if the matter is not free of frustration. By contrast, a tenant who has never had an abusive landlord will not likely regard even a small money value dispute about a repair, return of a deposit, or penalty for late rent as “simple.” With respect to relative value, the second consideration, even a seemingly “minor” fine or civil liability can loom large for a person of modest means, forcing painful choices about whether to put food on the table or pay up to avoid mounting fines and fees and continuing intervention on the part of the state. The stakes won’t seem “minor” to such a party.³⁵

Dignitary considerations are indeterminate and subjective, but an extensive, well-established body of social scientific and cognitive research makes clear that these considerations are central to the perceived legitimacy of dispute resolution systems. Quick resolution of emotionally charged cases in which people do not feel heard can have enduring negative repercussions not only for the parties, but for the administration of justice. As Alan Lind and Tom Tyler summarize, “people usually feel more fairly treated when they have had an opportunity to express their point of view about their situation.”³⁶ This is just as true, they note, in “simple” cases as it is for “complex” ones: “In small claims cases … all parties to a case would like to have an opportunity to tell their story, taking as much time as they feel they need to articulate the issues that matter to them.”³⁷ Unlimited participation obviously is not possible in any dispute resolution system. Finality matters to fairness. Judges are obliged to impose other limits as well, including legal relevance and consideration for the time that must be spent on other cases.³⁸ Nevertheless, Lind and Tyler emphasize, the tension between “objective justice and legal efficiency,” on the one hand, and “the experience of subjective justice on the part of the litigant,” on the other, doesn’t evaporate just because a case is a relatively “simple” one from the perspective of judges and other dispute systems designers.³⁹

They offer, as example, proceedings in a traffic court in Chicago:

Judges in that court often take the view that showing up for court and losing a day’s pay at work is punishment enough for a traffic offense. As a result, those who arrive in court often have their case dismissed without any hearing .… However, interviews with traffic court defendants suggest that despite these favorable outcomes they often leave the court dissatisfied. For example, one woman showed up for court with photographs that she felt showed that a sign warning her not to make an illegal turn was not clearly visible. After her case was dismissed (a victory!) she was angry and expressed considerable dissatisfaction with the court. … Outcome-based models might find the woman’s dissatisfaction difficult to explain, but process-based models would have little trouble in accounting for her reaction.⁴⁰

The feeling of not being given the time of day, of not being heard, can ramify in other forms of civic engagement, and in other dealings with the state. If they are tied to deeper mistreatment at the hands of the state, the consequences can be grave.⁴¹

Even a simple case can also prove quite complex to code in an ODR system. Complexity in coding arises not only from the costs of good ODR design but from limits in natural language processing capacities in even the most advanced AI systems and other algorithms.⁴² These systems are still capable of fairly comical errors in the interpretation of human language.⁴³ In some settings these errors present mere inconveniences – your Uber driver arrives late or drives to the wrong location. In law, the consequences can be catastrophic – including erroneous arrest and separation from one’s family, destroyed credit, even the use of deadly force in executing a bad warrant. Natural language processing capacities will improve gradually. However, as with any symbolic system that attempts to reproduce, measure, and operationalize content from another symbolic system (here, human language), there will always be gaps. All symbolic systems err, and all are to one degree or another ineluctably “leaky.”⁴⁴ This derives from the nature of representation itself – the fact that representation depends upon reduction of signified content to signs. Automated systems that displace human judgment offer advantages, but they also remove the possibility of real-time commonsense reconsideration.

This raises the question whether even truly “simple” cases are simple enough for ODR systems to handle.⁴⁵ The answer to that question cannot be found by comparing ODR to the cost of adversary resolution or to cases assumed to be more complex and therefore more suitable to adversary resolution. It can only be answered by taking stock of the merits.

Much of the adversary system is designed not only to maximize participation and party control (albeit for those who can afford it), but to avoid the problem of prejudging the merits – the temptation to decide a case based on reductive first impressions. This temptation is strong, reinforced by powerful cognitive biases (including confirmation bias, halo effects, etc.). A prominent nineteenth-century lawyer and judge famously admonished in defense of the adversary system that “the affairs of mankind are not so nicely adjusted as that one party in a law-suit should be entirely right and the other entirely wrong .… [T]ruth cannot be elicited and justice awarded unless both sides of a case are fairly represented.”⁴⁶ This is so not only because of the “intricacies” of “commercial relations,” the moral complexity of human action subject to legal regulation, or the “nice distinctions to be made in determining the degree of criminality,” but because long experience shows that “[m]any cases which at first seemed to be bad have on examination proved to be good.”⁴⁷ The adversary system thus rests on what one might call procedural skepticism – rules of procedure that reduce the risk of prejudgment.

The idea that there is a general category of “simple” cases and that the merits of these cases reveal themselves on first impression or on the initial pleadings is, from this perspective, a seductive fiction. It rests on a self-serving value judgment about small-dollar-figure claims – that they matter less and contain less complexity – and the triage imperatives of mass-processing.

As importantly, evidence from the last decade provides sobering proof that supposedly simple cases (small claims, landlord/tenant, and traffic and other misdemeanors) are not actually simple and that they have profound ramifications for the administration of justice. Firstly, we know that these cases dominate state trial court dockets, and that, in the vast majority, the individuals involved do not have counsel. So ODR is staking a claim to displace most state court adjudication, not experiment with a small subset of claims. We also know that, regardless of specific subject matter, these are mainly debt collection proceedings in which the plaintiff is either the state seeking to recover “legal financial obligations” (fines, fees, and other penalties imposed by the court) or a creditor (a lender, collection agency, or landlord) represented by counsel. There is thus a powerful repeat player (the state or a private creditor) on one side, and an individual defendant/debtor on the other. This contrasts sharply with the image of the facilitation of cooperative resolution between individuals painted by the ODR literature.⁴⁸

11.1.1 Public Enforcement in “Simple” Cases

With respect to public debts, the Department of Justice Investigation of the Ferguson Police Department and follow-on litigation against municipal courts around the country show that there has been widespread abuse of legal financial obligations as cash-strapped municipalities deprived of general funds by their states have converted courts into fee-for-service systems parasitic on the most financially vulnerable populations within their jurisdictions. In Ferguson, excessive fines and fees were imposed disproportionately on the African American population of the city. The Report’s section on the court system found that enforcement actions involved shocking deviations from basic principles of procedural due process, including failure to make the constitutionally required inquiry into litigants’ ability to pay before using imprisonment as a penalty or inducement for nonpayment.⁴⁹ Litigation in dozens of other jurisdictions reveals that the problems with setting and collecting legal financial obligations are widespread.⁵⁰ One report revealed that the

courts in St. Louis city and the county collected over $60 million in revenue in 2013 … with some cities depending on such fines for more than 40 percent of their general fund. The report found that the cities most dependent on such revenue were majority African-American with large impoverished populations .… In Jennings, which has a population of roughly 14,750, [a] lawsuit found that the city had issued about twice as many warrants as there were households, “mostly in cases involving unpaid debts for [traffic] tickets.” In 2013, a 24-year-old inmate in the Jennings jail who was imprisoned for unpaid tickets hanged himself.⁵¹

“Tragic incidents such as these draw into vivid relief the human cost of ignoring the connection between procedural due process and human dignity”.

As local courts have faced funding crises and failed to address racial bias, advocates of ODR have been marketing their platforms to court systems around the country and in the pages of law reviews by packaging enhanced efficiency in collecting public debts in the language of “access to justice.” ODR advocates insist that in traffic cases faster, cheaper resolution benefits individual defendants because they get closure and avoid the additional fees associated with failure to appear and default.⁵² But when one examines the use of the platforms marketed to court systems, one finds things like the Fort Collins, Colorado, municipal court’s ODR system for “camera radar/red light tickets.”⁵³ The ODR system provides for resolution of traffic camera tickets.⁵⁴ The sophisticated cameras cost $10,000 a month each to operate. Tickets are $75.⁵⁵ The city claims that the cameras are making a “huge difference” in driver education and safety, and it points to data showing reductions in accidents at one of the intersections where the cameras are used.⁵⁶ But the program also reportedly nets the city about $200,000 a year over operating costs, including payments to the private contractor who services the cameras.⁵⁷ Camera citations well exceed officer written traffic tickets in the city, and in other jurisdictions there is evidence that this enforcement tool invites politically corrupt outsourcing to private contractors and generates revenue without improving traffic safety at all.⁵⁸

The Fort Collins ODR system does not appear to follow a pure bargaining model where the resolution results from negotiating what will be paid irrespective of the merits. Nor, however, does it appear to be designed to fully and faithfully ascertain the merits in each case, including educating defendants about how to explore and assert standard defenses. The defendant is assured there is a prosecutor who will review the case and the website’s “About Online Case Review” page indicates that a defendant could “potentially have … fines and fees reduced or in some cases, dismissed altogether.”⁵⁹ The FAQ page, however, characterizes ODR as a process to enter a guilty plea through an “Online Plea” process.⁶⁰ The page indicates that “You can plead guilty, be sentenced, and pay your fines/costs without going to court in person.”⁶¹

If the system is mainly designed to enter guilty pleas and collect the fines and fees – if, that is, the private “review” conducted by prosecutors and the court is perfunctory, designed to “improve compliance” on the same terms as the designer’s platforms sold to other jurisdictions⁶² – then the efficiency gains accrue mainly to the city.⁶³ In cases where guilt is unclear or revenue generation dominates public safety priorities, defendants are saddled with unwarranted debts and the public with rent-seeking law enforcement. Indeed, a compliance-oriented ODR system that primarily increases the speed of collection for traffic camera fines raises the specter of fully automated law enforcement in derogation of every procedural value other than reduced cost to the state.⁶⁴ Nor does such an ODR enforcement process provide a public forum, as court proceedings do, for airing systemic concerns about whether revenue generation dominates legitimate public safety concerns. Public and media scrutiny of enforcement is literally short-circuited.⁶⁵

Remarkably, ODR advocates commonly ignore or suspend the merits question altogether – either not seeking to measure it, excluding it from the design of ODR systems, or both.⁶⁶ Traffic cases are indeed minor relative to felony cases, but the lesson of Ferguson and broader litigation about excessive fines and fees is that incursions on civil liberty and civil rights in the design of dispute resolution systems for these offenses can be substantial. Recent scholarship on criminal law and procedure reinforces this conclusion, showing that twenty-first-century misdemeanor enforcement has been used to criminalize poverty, to impose onerous systems of regulation and continuing supervision on marginal populations, to feed mass incarceration, and to subordinate racial minorities through biased forms of “order maintenance,” policing, and punishment.⁶⁷ To submerge these distortions in the administration of justice in automatic collection-compliance processes would obviously be inconsistent with the mission of enhancing access to justice for ordinary people.

11.1.2 Private Enforcement in “Simple” Cases

Even when the state is not a party to supposedly “simple” cases, recent empirical studies show that the simplicity hypothesis is untethered from the realities of the administration of justice. As ODR advocates describe small claims, it would be easy to assume not only that private individuals are on both sides of the litigation, but that in many “simple” cases people gin up “highly emotional conflicts over matters with relatively low monetary value.”⁶⁸ This happens, to be sure, but the data show that far more often an individual unrepresented defendant is sued in small claims court by a powerful creditor or landlord represented by counsel. The greater leverage of these plaintiffs is mobilized not to force costly merits adjudication, but rather to accelerate reduction of a claim to a final judgment and proceed with enforcement.

The National Center for State Courts Landscape of Civil Litigation study in 2015 found that three-quarters of all judgments in the state courts were less than $5,200.⁶⁹ Even among non–small claims cases that went to trial, “[t]hree quarters of judgments entered in contract cases following a bench trial were less than half of those in small claims cases ($1,785 versus $3,900). This contradicts assertions that most bench trials involve adjudication over complex, high-stakes cases.”⁷⁰ Whatever the nature of modern trial, most civil cases, the study emphasizes, were “disposed of through an administrative process,” and for cases that reached judgment, the most common resolution was a default judgment.⁷¹ In these cases, then, there is no meaningful deliberation on the merits, often no hearing whatsoever preceding the entry of judgment.

Most revealingly, the Landscape Study found that

[t]he vast majority of civil cases that remain in state courts are debt collection, landlord/tenant, foreclosure, and small claims cases. State courts are the preferred forum for plaintiffs in these cases for the simple reason that in most jurisdictions state courts hold a monopoly on procedures to enforce judgments. Securing a judgment … is the mandatory first step to being able to initiate garnishment or asset seizure proceedings. The majority of defendants in these cases, however, are self-represented.⁷²

The conjunction of self-representation and default judgments in small value debtor-creditor disputes suggests that some state courts are operating as accelerated debt collection forums. In the forty-four states where judges, clerks, magistrates, and justices of the peace are allowed to issue capias warrants for failure to appear at post-judgment asset examination hearings, defendants in civil cases face arrest and incarceration with bond often set equals to the debt owed.⁷³ As with misdemeanor criminal cases then, civil litigation for people in financially precarious situations can result in restraints on liberty in order to force payment.

On this evidence, as with the use of ODR for misdemeanor cases and legal financial obligations to courts, the simplicity/access nexus looks quite ominous. The access-to-justice problem is not how to speed things up and substitute automated bargaining over settlement value (or private deliberation on facts adduced through strictly circumscribed online submissions) in place of public inquiry into the merits in small value cases. It is (1) how to slow creditors and other repeat players down in order to ensure attention to the merits and (2) how to address the systemic disparities in power that shape both the debts being collected (click-wrap and other contracts of adhesion; payday lending schemes, etc.) and enforcement procedures (default judgment, capias, etc.). ODR systems oriented toward speed and automated online resolution may be quite attractive to plaintiff creditors and other repeat players, but for individual defendant debtors, the risk is great that ODR systems will not include adequate exploration of defenses available under the relevant contract, lease, or state and federal consumer protection and fair debt collection practices laws.⁷⁴ These defenses are not generally regarded as “simple” by experts. A 2010 FTC report found that even basic affirmative defenses such as state statutes of limitations “on filing actions to recover debt are sometimes variable and complex, and generally not understood by consumers.”⁷⁵ An allegation of identity theft raised by a debtor can “increase the complexity and time required” to resolve a matter.⁷⁶ The Truth in Lending Act’s enforcement structure – which contemplates use of the statute as a counterclaim in a debt collection proceeding – is famously “confusing.”⁷⁷

Enough has been said, I hope, to make clear that small values cases are by no means simple or low stakes either for the parties concerned or the administration of justice. Nor are these cases small in number – they compose a substantial part of court dockets and therefore of the cases handled by the adversary system. The simplicity hypothesis is false. If there is a class of truly simple claims suitable for ODR, the hard question is how to define standards for accurately identifying them without having to adjudicate the merits along the way – the very task the avoidance of which makes ODR so affordable. As matters currently stand, then, the principal effect of using low money-value claims as a proxy for simplicity will be to produce a bifurcated system of justice – one in which low- and middle-income people already priced out of meaningful participation in the adversary system⁷⁸ will have no alternative but to avail themselves of ODR systems. This bifurcation in the administration of justice will merely formalize, encode and multiply, not mitigate, problems of access to justice.

In the most ambitious ODR systems – those that remove the third party neutral human decision-maker altogether – low- and middle-income people will receive justice defined by software engineers unregulated by standards of judicial ethics except to the extent that courts supervise their outsourcing contracts. And we know that supervision will be limited by the fact that the best AI systems to date are opaque in their operation even to their designers.⁷⁹ So, for instance, a deep learning system used to generate “reasonable” settlement values might not be explainable – even by the engineers who program it. Systems that are more transparent because they rely on expert design rather than deep learning, on the other hand, remain highly reductive.⁸⁰ Absent regulation, this bifurcated system for the administration of justice will flourish on terms that limit assessment and accountability.

11.2 The Architecture of ODR: Access to Justice, Harmony, or “Just Harmony”?

The last section focused on the pervasive assumption that ODR will enhance access to justice because it is suitable for so-called simple cases as measured by money value. In this Section, I shift from the nature of the cases ODR systems regularly handle to the design of the systems themselves in order to examine exactly how the architecture of ODR promotes efficient resolution.

11.2.1 ODR’s Design Features

Although the overall ecosystem is heterogenous and evolving rapidly, most current ODR platforms function by breaking dispute resolution into its component phases, reducing legal forms and rules to plain language questions, instructions, and guidance, and then using asynchronous electronic communication, document storage, retrieval, and review to facilitate the flow of information needed to define and resolve the dispute, as shown in Table 11.1.

Table 11.1 Five phases of ODR

Phase	I Opt In Phase	II Diagnosis/Intake	III Negotiation	IV Third Party Neutral/ Algorithm	V Closure / Opt Out
Process	Information to users about process and applicable substantive rules	Information gathered from users	– Open – Structured – Algorithm or AI System	– Review and approve – Facilitate to reach agreement – AI System	– Approval of enforceable order – Online adjudication by third party neutral – Referral to courts/arbitration

In the first phase there is typically a webpage with plain language text, videos, and graphical information describing the specific ODR process. In some instances, general information on the law is provided (at varying levels of detail). In others, there is little or no information about the underlying rights and defenses that apply to the dispute or resources for ascertaining what the law is. The emphasis is instead on identifying the parties’ interests. Rechtwijzer, the Dutch online ODR system that, until its demise in 2017, handled divorce, family law, debt, and neighbor disputes, explicitly encouraged the parties to approach the process through the framework of interest-based resolution.⁸¹ Divorcing parties were initially informed of “rules such as those for dividing property, child support and standard arrangements for visiting rights so that they could agree on the basis of informed consent,” but the software’s negotiation framework prioritized interests, not rights.⁸²

British Columbia’s vaunted Civil Resolution Tribunal (CRT) includes a statute-of-limitations information page that defines what a statute of limitations is and advises parties that it is not tolled during the first phases of the CRT process. But it does not answer the question of what statute of limitations applies to the dispute the party has, how to determine either when it started to run, or when it will expire. The page ends with the statement: “We can’t answer these questions for you. You may want to get legal advice. The CRT can’t provide legal advice.”⁸³ Indeed, CRT’s detailed downloadable forms to help parties prepare for negotiation generally ignore rights and defenses, instead prompting the parties to identify and articulate their interests.⁸⁴

To generate enthusiasm and induce users to opt in, introductory pages of ODR websites also include substantial promotional content highlighting perceived advantages of ODR relative to adjudication in court. The CRT home page begins: “Save time, money, and stress! The CRT lets you resolve your dispute when and where it’s convenient for you …. The CRT helps you resolve your dispute quickly and affordably.”⁸⁵ Rechtwijzer, the online divorce settlement platform, billed itself as providing a chance to “separate together” without the adversity and acrimony of divorce in court.⁸⁶ ODR websites generally do not counterbalance their self-promotion regarding the advantages of online resolution with sober assessment of potential downsides, clear notice about rights waived, or alternatives.

In Phase II, once users have opted in, questions are directed to the users through a range of graphical interfaces in order to gather basic information about the dispute, classify it, populate relevant forms, and upload relevant documentary evidence. Advanced systems use chatbots or other interfaces modeled off of apps people use daily on their smartphones and other devices. Matterhorn, the ODR system behind the Colorado traffic camera enforcement discussed in Section 11.1 has an online process for “the uploading of statements by parties, law enforcement and court personnel from afar and in lieu of court hearings.”⁸⁷ In this phase, assuming the design for information sharing is not reductive, there are obvious efficiency gains in cost, time, and convenience associated with “asynchronous processes” for fact gathering relative to filing papers in court.⁸⁸

In the negotiation phase, Phase III, there is a wide range of approaches. Some, such as CRT’s, simply provide online portals for direct, unmediated negotiation between parties with some basic ground rules about abusive communication and guidance about how to prepare and conduct a successful interest-based negotiation. Others introduce a human third-party neutral to guide negotiation. Still others are automated and more rigidly structured, channeling the parties into online negotiation in the form of blind bidding with an algorithm that is designed to identify an optimal settlement from the highest one party is willing to offer and the least the other is willing to accept.⁸⁹ This ostensibly allows parties to “overcome tactics often employed in face-to-face negotiations that hinder reaching an agreement despite the existence of a ‘zone of possible agreement.’”⁹⁰ Smartsettle’s software forces parties to “list their interests and assign numerical values to them, thereby creating a weighted spectrum of issues” from which an algorithm “generated various ‘packages’ or combinations of issues that might satisfy both parties” along with “a graph as a visual display of the level of satisfaction each package of issues represented for the parties.”⁹¹ Overall, both public and private ODR platforms share some of the following algorithmically automated features at varying levels of sophistication: “identifying dispute types; exposing parties’ interests; asking questions about positions; reframing demands; suggesting options for solutions allowing; allowing some venting; matching solutions to problems; and drafting agreements.”⁹²

In the phase IV, a third-party neutral human expert may be brought in online to review and approve a deal reached between the parties. This was the case with Rechtwijzer. If online negotiations resulted in an agreement, an independent lawyer would be brought in to review the deal “to ensure that it meets legal requirements and is fair to both parties.”⁹³ If no agreement was reached, a mediator or arbitrator would be brought in online to help facilitate resolution. Costs were a fraction of traditional costs for counsel in divorce proceedings in court, and “[e]ven at the higher end,” costs were “lower than the costs to the Legal Aid Board for representing both parties to divorce proceedings in court.”⁹⁴ In the near future algorithms may not only structure negotiation and suggest solutions but displace the third-party neutral altogether by using artificial intelligence to review and validate negotiated solutions.⁹⁵

In the fifth and final phase, an agreement reached online is reduced to an enforceable contract or court order. Generally, ODR negotiations cannot be introduced in court, but there are many exceptions. CRT participants, for instance, lose confidentiality if they use what the system designers determine is “abusive” language in settlement negotiations. ODR websites also vary widely in the promises they make regarding the use of user data (information such as identity, location, negotiation documents and communications, history of participation in ODR or other litigation, etc.), sale of such data to third-party data brokers, and how and on what terms such information is shared with court systems with whom they contract and other government entities. Generally, there is no public access to the ODR process in real time, no public ODR docket, and unlike codes of procedure and evidence in courts and the decisional law interpreting them, the lines of code in ODR systems are proprietary, insulated from public review, and treated as trade secrets by ODR companies.

11.2.2 ODR as Interest-Based Dispute Resolution

What can be inferred from this structure about ODR as a form of dispute resolution? What theory of justice does its architecture embody? The most important thing to notice is that the overwhelming emphasis in the structure of ODR systems is on “integrative negotiation” or interest-based, win-win bargaining, rather than the merits.⁹⁶ The “archetypical ODR approach is to provide an online forum and tools to facilitate the full settlement of claims without any human intervention.”⁹⁷ However, users unfamiliar with law are not in a position to recognize that ODR is oriented toward integrative resolution rather than resolution based on their legal rights and defenses.⁹⁸

Although even the earliest theories of interest-based negotiation insisted that interests must be “legitimate” to warrant consideration, and that “community concerns” are relevant to bilateral negotiation,⁹⁹ some ODR systems eliminate these factors entirely. Blind bidding and other mathematical representations of interests have this effect – resolution arises from overlapping settlement values defined by the parties irrespective of any independent assessment of how the merits relate to the parties’ quantification of their interests. In other ODR systems, such as CRT and Rechtwijzer, attention to the legal merits and third-party effects is backloaded into the review phase (phase IV) when a third-party neutral steps in. But at that stage, rejection of a settlement entails losing the efficiency gains accumulated through the ODR negotiation process. Delayed intervention of the third-party neutral thus virtually guarantees the subordination of concerns about the merits and negative externalities imposed on third parties and the community. The prize of agreement, once reached, is exceedingly difficult to refuse. As importantly, fact development to that point may not illuminate defects even for a third-party neutral deeply comitted exercising independent judgment and disposed to resist the allure of the prize.¹⁰⁰

Even systems that bring a third-party neutral in earlier may not improve attention to the legal merits. As the orientation of many third-party neutrals is toward efficiency, “harmony and overcoming conflict,” not the legal merits,¹⁰¹ their disposition, training, and docket pressure may lead the them to “‘trade justice for harmony.’”¹⁰² This has long been a criticism of the alternative dispute resolution movement, sharpened by evidence that by privileging “harmony” in pluralistic societies (where there are competing conceptions of the good and systematic marginalization of minority groups), interest-based resolution can “suppress … or silence … the voices of those without political power.”¹⁰³ In cases involving public debts to courts, revenue generated from these cases may diminish impartiality, attention to the merits, and community concerns. Some ODR systems are marketed to courts on precisely these terms, touting increased collection rates, decreased defaults, and reduced time to collection. For example, Matterhorn’s contract with the court in Washtenaw County, Michigan, for traffic violations helped the company expand ODR to dozens of other counties on the back of reports that it produced a more than 40 percent increase in fines paid within thirty days.¹⁰⁴

Although facts can generally be elicited efficiently online relative to live hearings and paper filings, important information can be lost in shifting from a hearing/forms combination to text-only,¹⁰⁵ writing skill is a built-in advantage for high-literacy litigants,¹⁰⁶ and without tailored advice about how the law applies to the facts of their case, litigants may omit relevant evidence. Everything hinges on how questions posed to elicit the facts are framed by the ODR platform. On the other hand, the more detailed the questions and guidance, the more expensive the code. Even the most advanced current AI systems thrive in bound environments, not open-ended, indeterminate ones.¹⁰⁷ The temptation, therefore, is ever to manufacture a bounded environment in coding for dispute resolution – reducing complexity in order to code efficiently.

Modria’s brochure for courts considering adoption of its ODR software, proudly declares that it “helps courts resolve all manner of case types faster without sacrificing accuracy,” but if we take the architecture of ODR systems seriously, the truth is that it is quite difficult to assess the accuracy of ODR systems.¹⁰⁸ Indeed, the earlier cases settle and the more interest-based bargaining drives resolution, the less certain we can be that any given settlement is a just reflection of the relevant rights and defenses of the parties.¹⁰⁹

11.2.3 ODR Funding

Funding remains one of the greatest barriers to the development of ODR and, ironically, one of the weakest pillars in its claim to expand access to justice. Many systems have failed because they have not produced a durable financial model despite receiving public subsidies and favorable user reviews.¹¹⁰ The systems are costly to develop, and both the law and technology change in ways that make it costly to keep the systems up-to-date. One prominent provider, CRT, therefore relies heavily on a fee-for-service model. The parties using CRT pay not only initial filing fees, but fees for every subsequent phase of the process, making the process more expensive as it unfolds if no negotiated solution is reached.¹¹¹ CRT also charges a substantial fee ($200) to file a notice of objection in a small claims dispute.¹¹² This means that for a small claims dispute involving $1,000, challenging a settlement would cost 20 percent of the value of the dispute (on top of $75 to file the complaint, $75 to add a claim against a third party, $10 per records request, and $50 to switch from negotiation to an adjudicator).¹¹³ Fee structures like this induce people who have financial constraints to resolve disputes quickly and accept a resolution that may be unjust. People of means, on the other hand, can afford to take advantage of every avenue of relief.¹¹⁴

Other ODR systems are free to users¹¹⁵ and presumably paid for by courts. Contract terms between courts and private vendors of ODR software are not generally available to the public.¹¹⁶ This makes any comparison with the costs of alternatives to ODR such as civil Gideon¹¹⁷ difficult to assess. It also contrasts sharply with the public budget process of funding courts as well as rules of judicial ethics that strictly regulate financial conflicts of interest in the judiciary.

11.2.4 ODR Party Structure

Although the ODR literature focuses on small value civil law disputes between roughly equally situated, unrepresented private parties, ODR is currently being used for disputes that involve parties of radically unequal status. These include criminal disputes between the government and individuals, where ordinary people are negotiating with prosecutors and judges regarding fines and fees the nonpayment of which could lead to incarceration, disputes between landlords and tenants, property associations and owners, creditors and debtors, contractors, subcontractors and home owners, nonunion employees and employers, insurers and parties harmed in an accident,¹¹⁸ and couples who brought vastly different resources into the marriage and are unequally situated.¹¹⁹ Some ODR systems permit parties to be represented if they can afford to do so, introducing potentially vast disparities in the level of expertise that one side brings to negotiations. Experience with other ADR systems such as arbitration is sobering on this front, indicating that powerful repeat-players not only fare better but are able over time to shape ADR procedures to maximize their interests.¹²⁰ Nor do the opt-in pages of ODR systems adequately disclose information to support knowing and informed waivers of due process rights and other rights a party would have in court.

In sum, democratically enacted and public rules of procedure and evidence are displaced by the proprietary technology of ODR systems.¹²¹ Lawyers who work in principal-agent relationships for clients, and who have expertise in the rules of procedure and evidence, are replaced by software engineers whose highest loyalty is to investors and, secondarily, to the courts who retain them to help reduce costs. There is no malpractice cause of action for users against ODR providers, and no enforceable ethical code requiring fiduciary duty, competence, diligence, loyalty, communication, or confidentiality. Users of ODR platforms, who are constitutional right holders in the adversary system, become mere tertiary beneficiaries of contracts entered between courts and ODR providers. And as with other forms of alternative dispute resolution, ODR replaces the public appearance and reason-giving function of the judge either entirely (in systems that displace these decision makers with AI) or partially by changing the scene of adjudication from a public courtroom to a private online forum where third-party neutrals facilitate or impose resolution behind encrypted walls of code. We know that the reasons for conducting adjudication publicly in adversarial space are not exclusively performative.¹²² Doing so helps prevent corruption, bias, and arbitrary decision. Justice, the saying goes, must not only be done, but must be “seen to be done.”¹²³

No one should therefore be surprised to see ODR systems that serve principally to induce settlement and improve compliance with judgments on behalf of the state, powerful creditors, and other well-resourced, represented parties, while failing either to establish the rights and defenses of unrepresented parties or make transparent potentially systemic abuses of the laws being enforced.

11.3 ODR and Preventive Justice

This chapter has so far focused on pragmatic concerns about current ODR systems. In closing I want to raise a more fundamental challenge: ODR systems rest on a theory of justice at odds with liberal democratic principles of the rule of law. For decades the dream of alternative dispute resolution advocates has been to design systems that not only resolve disputes when they arise, but to use information about such disputes to detect patterns of conflict and prevent them from occurring in the first place.¹²⁴ The ultimate goal is preventive justice, a culture of seamless compliance. ODR offers the means to realize this goal because it relies on the technology of algorithmic governance – coding that relies on big data to predict and steer human decision-making.¹²⁵ Whatever the appeal of preventive justice within a corporation for its ability to induce compliance with internal corporate norms and external regulations, or in other domains such as public health, as a general theory for the administration of justice it is destructive of human freedom.

Outside authoritarian regimes, the default rule for the administration of justice is that the law intervenes in the lives of ordinary people (1) after wrongdoing, not before, and (2) in response to specific instances of wrongdoing, not the broader collective conditions giving rise to them. Strict standards of substantive liability generally apply to inchoate offenses. Ex ante intervention and regulation are possible, as is structural relief addressed to conditions that repeatedly cause serious harm, but they are both exceptional – higher standards have to be met to authorize these remedies – and they are generally reserved for misconduct on the part of the state and regulated entities, not ordinary people.

These default rules can be found in the law of procedural due process, remedies, the prohibition on prior restraints against free speech, and so forth. Their purpose is to protect the sphere of social action from domination by the state and others who have the means to maximize enforcement of their interests and bend the law to their will. The adversary system embodies these default rules. It grounds the administration of justice not in a substantive concept of justice but in decentralized, participatory, public, ex post adjudication.¹²⁶

ODR systems are oriented toward a very different theory of justice. Their proponents are quite frank about this, drawing on the work of earlier analog dispute systems designers. Ury, Brett, and Goldberg famously argued from the study of wildcat strikes that employee-employer conflict and ex post resolution costs could be avoided by studying patterns in those labor disputes and altering institutional structures to reduce conflict. For dispute system designers, conflicts are unfortunate and avoidable events; rights assertion and adjudication are disfavored, costly projects that amplify adversity. With the correct information, well-calibrated interest-balancing, and appropriate ex ante interventions, both social conflict and conflict in court can be avoided.¹²⁷ The true promise of the ODR is thus not merely to streamline dispute resolution, it is to develop products that realize the potential of dispute systems’ design to prevent conflicts from arising in the first place – to instantiate a culture of compliance. As one commentator puts it, just as the value of Uber is the relevance of its data to a future market of automated cars, “the seeds of an effort to prevent disputes may lie in the technology employed to resolve disputes.”¹²⁸ How? “[T]he use of technology provides ODR with more opportunities to identify systemic contribution to conflict and systemic opportunities to reduce conflict.”¹²⁹ These opportunities arise from the capacity of ODR systems to exploit the information they gather about pending disputes to provide “automatic detection of problems, obviating the need to passively wait for complaints to arrive and allowing proactive remedying of the problem even before a potential complainant has been made aware of its existence.”¹³⁰

If this sounds futuristic, it is not. Private ODR systems are already valued by corporations for their capacity to prevent customer, user, and employee disputes.¹³¹ It is now “commonplace” for private ODR systems to “captur[e] data and analyz[e] it for insight into the disputing environment of a particular institution to help prevent future disputes.”¹³² The objective is to identify patterns and sources of conflict, anticipate new ones, and snuff them out in advance. It’s one thing of course when the lens is directed inward, to identify policies and practices of a corporation that are producing conflict or misconduct.¹³³ But it is quite another to direct the lens outward, combining the information saturation of digital interaction and predictive analytics to continuously monitor and manipulate the preferences, choices, and norms of users.

Private ODR already involves both – internal and external preventive surveillance, intervention, and restructuring of code to optimize compliance.¹³⁴ For companies like Airbnb, the

effortless recording of large amounts of data relating to anyone operating on the site creates a huge database that can be cross-checked with information on problems and resolutions, generating unique insights on how to structure more satisfactory transactions, what problematic patterns need to be dealt with, what rules and practices require clarification or amendment, and which participants require mentoring or instruction.¹³⁵

In order to promote transactions that “are less likely to generate problems,” the company may alter things like “which listing to display first” to a particular user.¹³⁶ There are plenty of nondigital examples of decisions like this inviting or reflecting bias – for example, one renter gets access to “A list” properties from an agency or landlord based on race, ethnicity, or assumptions about credit or past experience with the renter; another does not. The difference in an online platform is that the user may have no idea she is not seeing all the available properties in a location – code presents a smooth surface relative to live interaction that can obscure not only the fact that the user’s information is siloed, but also the basis for the decision to do so, and thus, crucially, the opportunity to challenge it in court or any other forum.

Conflict prevention grounded in unjustified restriction of users rights which cannot be detected and challenged by the user thus creates a double silo – limiting choices as well as information about the limitation that might subject it to legal scrutiny. Conflict may be reduced, but in the manner of a falconry hood. In some settings the stakes may be relatively trivial, but errors in other settings can have significant life consequences.

Preventive justice is actively used in other areas of private ODR such as automated content moderation of speech on social media platforms, employment, and preventive medicine. Automated prescreening systems have become a significant form of content moderation.¹³⁷ They have the capacity to significantly reduce online disputes, but they can easily err by failing to incorporate important “contextual information” such as language and cultural differences that affect semantic meaning.¹³⁸ There is evidence that these preventive systems have overenforced copyright law to the detriment of fair use, and they “raise concerns about the limits of public speech, cultural sensitivities, and individual rights.”¹³⁹ In the domain of medical prevention, genetic data can save lives, but it has also been incorrectly used to exclude children from school to prevent the spread of disease.¹⁴⁰ In the workplace, dispute prevention efforts can improve safety and performance, but they can also amplify the power of employers, undercut the rights of workers, and inhibit worker mobilization and unionization.¹⁴¹

In public ODR systems, the lines between dispute resolution and prevention are already “increasingly being blurred.”¹⁴² The data gathering and processing technology underlying ODR provides means previously unavailable to extend preventive intervention beyond the boundaries of individual organizations to the administration of justice.¹⁴³ Commentators emphasize that data produced by ODR systems “will enable … the identification of large-scale trends and patterns we have never seen before, often through automated means instead of human analysis …. Those in control of these large data sets will be able to analyze the data and … prevent the occurrence of a dispute.”¹⁴⁴ Indeed, “[b]y overcoming the need to rely on the aggrieved party’s ability to recognize and pursue a remedy, a larger portion of society’s problems can be addressed and prevented regardless of the aggrieved party’s awareness of his or her injury.”¹⁴⁵ For example, the data gathered by ODR systems and data being aggregated to inform predictive policing may prove lucrative for tech companies to combine and market, and tempting for prosecutors and law enforcement to exploit.¹⁴⁶ Or someone who loses the confidentiality protections of CRT’s online mediation process because she uses what the system unilaterally defines as “abusive” language may find herself classified by any number of databases relying on predictive analytics as mentally unfit, a safety threat, a credit risk, unsuitable for hiring or admission into a training or credential program, and so forth. These cross-referencing effects are possible in analog record-keeping, but with big data and the power of the algorithms driving predictive analytics they can disseminate pervasively, instantaneously, and without public transparency.

The “politics of the preventive has a strong element of irresistibility built into it, since it generally appears perverse to argue against a preventive measure. Who could be against the prevention of harm? … [C]ritics … can be portrayed as courting insecurity and jeopardizing public safety” and harmony.¹⁴⁷

The problem is that the same class of elite software engineers who delight in disruptive innovation and flagrantly disregard regulation is developing ODR systems that would embed compliance in the architecture for the administration of justice for ordinary people. Doing so in the name of access to justice is not just ironic or hypocritical, it masks a potentially transformative struggle over the nature of the rule of law. Preventive compliance by code might be welcome if dispute system designers were right that legal conflict is usually a sign of social malaise, and if software engineers were uniquely adept at distinguishing legitimate from illegitimate conflict and resistance to law.

But neither proposition is true.

Not all resistance to law and noncompliance is a sign of delinquency or a threat to the body politic; in fact, noncompliance can be one of the very highest forms of civic engagement. Our most important progress in racial justice is the product of nonviolent civil disobedience. Indeed, on some accounts of liberal democratic theory under conditions of value pluralism, “justice is conflict.”¹⁴⁸ Law without resistance is not law – it is domination, simpliciter, a panoptic prison of code. And software engineers have no particular expertise (or incentive) to correctly draw lines between socially desirable and undesirable rights assertion or defiance. No one does. That is precisely why the adversary system vests decisional authority in decentralized, democratically accountable jurors, judges, and regulators subject to appellate review, and, for the latter two, establishes legally enforceable standards of impartiality and professional conduct.¹⁴⁹

ODR systems alter this structure – placing a single, professionally, and democratically unaccountable group of elites in control of the procedures for dispute resolution. Using these proprietary systems to prevent, not merely resolve, disputes would subvert the structure altogether. What has traditionally been understood as an exceptional form of the administration of justice would become the rule, at least for those priced out of the adversary system.

I hold no crystal ball, but we don’t have to guess about the ominous authoritarian implications of big data in the hands of tech companies and the state.¹⁵⁰ ODR firms are currently modest in market capitalization. This gives courts and bar regulators some leverage in negotiating terms. Reliance on AI is nascent, reducing some of the problems for court administrators and the public of opacity in assessing how these systems run. But we know from other sectors of innovation that it doesn’t take long for market concentration to emerge, and AI is evolving rapidly in ways that may amplify opacity. We also know that when tech companies consolidate a market, they not only exclude competitors in anticompetitive ways;¹⁵¹ they use their position to exclude inexpensive public alternatives. This is precisely what TurboTax has done.

But these are not inevitable outcomes. ODR systems can be improved in a variety of ways if judges, court administrators, and state bar regulators recognize that we have arrived at the legal equivalent of the combustion engine–electric car design decision. On one path, unwarranted faith in innovation will lead to deregulation or lax regulation. Rent-seeking in the administration of justice will masquerade as innovation. By the time the costs of this path become clear, ODR providers may be too powerful to control. Alternatively, ODR could support and preserve human judgment on the part of all participants by exploiting the technology’s efficient information gathering capacity while providing greater transparency. To achieve this ODR systems have to:

• • be opt-in;

• • include strict disclosure and consent requirements to validate opt-in decisions;

• • protects the privacy of user data and require publication of ODR rules and system design;

• • develop more precise heuristics for separating cases appropriately eligible for ODR from those that are not;

• • elevate procedural values in ODR system design other than compliance and efficiency, especially merits assessment;

• • strictly distinguish interest-based negotiation platforms from adjudication platforms;

• • require that mediators, judges, and prosecutors document their reasons on record for resolutions they reach in ODR systems;

• • gather and report performance data to promote assessment of biases and other distortions in relation to established standards of impartiality;

• • reduce the costs of appeal;

• • publicly disclose court/ODR firm contracts.

A third path would permit ODR systems to resolve disputes without human mediators or adjudicators subject to heightened scrutiny under the above regulatory standards. A fourth would refocus courts’ access-to-justice initiatives on some combinations of paths two or three and increasing direct funding for access to counsel. Whatever the path, ODR’s costs and benefits must be placed in relation to a tangible innovation baseline. All too often ODR’s proponents compare it to “no justice” – the position of a party who cannot afford to appear in court or cannot afford a lawyer. But just as new medical interventions and drugs are assessed in relation to an evidence-based standard of safety and efficacy, not the condition of the untreated, ODR should be judged by comparison to standards of procedural fairness and the costs of alternatives such as expanding access to counsel.

In sum, innovation worthy of the name should improve the administration of justice for ordinary people, not just impose different and potentially more tragic trade-offs than the adversary system and traditional forms of alternative dispute resolution. ODR proponents contend that without the freedom to experiment, the best designs may never be developed. But just as any automobile must have more than an efficient engine, ODR must do more than end disputes for ordinary people quickly and cheaply.

The promise of ODR has prompted courts and bar associations to rush to deregulate under the banner of exemptions that promote experimentation.¹⁵² Solemn language about the importance of consumer and public protection and risk assessment can be found in these materials, but all too often without reducing these lofty principles to concrete design parameters. ODR is no longer on the salt flats. It seeks to transform the rule of law. The brave new world will not be a form of code as law in the conventional sense – the way code architecture structures online behavior. It will be a (re)codification of law, of the administration of justice itself. We leave design parameters to unregulated engineers at our peril.

12 Using ODR Platforms to Level the Playing Field Improving Pro Se Litigation through ODR Design

J.J. Prescott

A sea change is under way in how we talk and think about court technology.¹ For decades, court officials – judges and staff – have relied on computers for word processing and internal scheduling, case management systems to store and organize digital records, the internet for research, and email to communicate. Like many organizations, courts have long conceived of technology exclusively as a way to improve their operational efficiency, reducing the time and effort it takes for them to do what they have always done:² provide neutral, real-time, face-to-face proceedings to resolve disputes, with a judge or a magistrate overseeing safe and purportedly transparent hearings in a physical, courthouse setting.³

This perspective is changing. The advent of online dispute resolution (ODR) platforms has reminded courts that providing in-person, real-time proceedings in a physical courtroom is just a means to an end; courts exist first and foremost to resolve disputes, at least in state courts handling everyday matters.⁴ Presumably, there is no single best way to resolve disputes,⁵ and courts are beginning to recognize that ODR – with its potential to improve accessibility while maintaining the integrity and values of traditional judicial process – can improve on conventional face-to-face courtroom proceedings for a significant fraction of cases.⁶ But precisely how far such technology can take courts remains an open question – one with huge implications for the future of formal adjudication in our society.

In this chapter, I argue that court-based ODR platforms can do far more to improve dispute resolution than simply puncture the barriers inherent to accessing physical courthouses, as important as this achievement is in its own right. In particular, I show that ODR systems also have the capacity to reduce the pro se representation gap in adjudication by incorporating tools that mimic many of the essential functions of legal counsel. In the years ahead, courts should grasp the opportunity to design and deploy technology with this goal in mind to advance their core function of successfully resolving disputes, even when the prospect of doing so may push them out of their comfort zone and blur or even redraw traditional boundaries regarding court neutrality and concerns over “helping” litigants.

The first step in this argument is recognizing that effective dispute resolution depends on robust access to justice. While the defining virtue of ODR technology to date is its capacity to improve the accessibility of courts for litigants, the phrase “access to justice” hinges on what it means to achieve justice,⁷ and any useful access-to-justice criterion must ask whether laws and institutions resolve disputes appropriately – that is, accurately and fairly.

One important class of access-to-justice issues relates to the sheer difficulty of using courts to resolve disputes.⁸ If individuals cannot make meritorious claims or defend themselves against improper allegations because doing so is too costly or difficult, the system implicitly “resolves” disputes inappropriately – for instance, through default, coerced settlement, uninformed verdicts, or other outcomes that are more a function of litigation and court-imposed costs than underlying substance.⁹ For this reason, some access-to-justice advocates have criticized the justice system’s reliance on physical courthouses that are few and far between, open only during business hours, difficult to navigate, and intimidating to use.¹⁰ Especially in relatively low-stakes legal cases (a large majority of cases, in fact), like traffic or small claims matters, these hurdles leave large swaths of people out in the cold, unable to seek protection under the law.

First-generation court-connected ODR (or ODR 1.0)¹¹ has already shown technology’s potential to overcome this particular class of access-to-justice barriers. First-gen ODR has opened up courts by leaving courthouses behind. In many states, and across a variety of dispute types,¹² ODR platforms allow people to interface with their cases using mobile phones from their homes at any hour of the day. Software design and “smart” forms simplify processes.¹³ Notifications and error checks keep litigants in the know, allowing them to engage more quickly.¹⁴ All in all, ODR platforms make accessing courts much easier.¹⁵ Moreover, while today’s ODR platforms are available for minor legal disputes, they also show potential for certain aspects of more significant litigation matters. The recent success of online voir dire proceedings, and even trials, intimates that the need for in-person hearings to resolve disputes with accuracy and fairness may be limited.

But existing court ODR systems do not go far enough. Even if these platforms were capable of allowing everyone to resolve their disputes from a place and at a time of their choosing, a meaningful access-to-justice gap would remain. In a society with significant socioeconomic disparities, the mere power to invoke the law, even at near-zero cost, hardly levels the playing field. Wielding the law effectively requires experience and expertise.¹⁶ While some litigants can accrue experience and build expertise through repeated play, other parties to a legal dispute – usually, the “haves” – typically acquire these assets by hiring a lawyer.¹⁷ Lawyers provide many services to their clients, but perhaps first among them is assessing likely outcomes in any matter. Lawyers also explain the nuts and bolts of the law and the range of options available to their clients, including the option to do nothing. Lawyers physically represent their clients in courtrooms as well, muting or obscuring demographic and/or educational differences between litigants when appearing before court (at least if we assume lawyers are likely to be more alike in background and training than any particular set of litigants).

Therefore, simply easing access to a courtroom through technology can only do so much to move us toward ideal dispute resolution. Indeed, access-to-justice advocates devote the lion’s share of their attention to ensuring adequate legal representation in courtrooms, lambasting any system rife with pro se litigants as likely to get it wrong far too often.¹⁸ For this reason, as first-gen ODR platforms proliferate, disparities in outcomes that are attributable to disparities in representation are unlikely to shrink and will probably increase. After all, as those long shut out of courthouses newly turn to ODR to pursue their legal interests, the significance of the representation chasm will become even more stark. A lot more “have-nots” will be seeking justice without a fair shot.¹⁹

Looking forward, a key goal for second-generation ODR platforms must be using data science techniques, design opportunities, and the treasure trove of data ODR platforms and court systems collect every day to bridge the legal representation gap.²⁰ Court-connected ODR platforms, if designed appropriately, can offer – for free – many of the same “services” that lawyers currently deliver to those fortunate enough to have a lawyer. The idea is not for courts to provide all litigants with a robot lawyer.²¹ Instead, the idea is to recognize that much of what lawyers do to help their clients involves providing them with information (e.g., options, predictions) about how their case “stacks up” and helping them to put their best foot forward (e.g., presentation, representation). If courts enhance ODR platforms so that they may offer some of these same functions in the right way, the future of dispute resolution will not only be low cost and easy to access but will also disadvantage pro se litigants much less than traditional court processes.

12.1 The Current State of the Art: First-Generation, Court-Connected ODR

As a concept, ODR emerged from the commercial consumer sector, as companies like eBay sought a means of resolving disputes (usually involving small-dollar values) that arose online between physically separated individuals. Many state court cases resemble small-stakes commercial disputes, and while litigants are often geographically proximate to each other, going to court to resolve a small-stakes case (say, under $500) still makes little sense to many. Even proceeding pro se routinely requires missing work, finding transportation, navigating the courthouse, and facing an intimidating judge. Add to this the fact that court is always a gamble – the prospect of improving one’s chances, from 0 percent (default) to even a modest 50 percent, is uncertain, but a litigant pays the cost of accessing the law at a courthouse with certainty – and it is unsurprising that many individuals in small-stakes disputes simply default, wrongly admit fault, or decline to file a meritorious case.

12.1.1 Where the Story Begins: Courts, ODR, and Access to Justice

Less than ten years ago, state courts began implementing ODR platforms for high-volume, small-stakes cases, like alleged traffic violations and other cases where physical resolution of the matter could be very costly to one of the litigants (e.g., outstanding failure-to-pay warrants), making remote resolution particularly attractive. One of the very first ODR platforms, if not the first, to be widely adopted in US courts was Matterhorn, which Michigan adopted starting in 2014.²²

The earliest Matterhorn ODR implementations sought to resolve disputes between individuals and the government: traffic, civil infractions, warrants, and a couple of misdemeanors. These ODR platforms were in many ways designed to “mimic” traditional proceedings, with a few key differences: ODR was made available at any time of day, information was exchanged asynchronously by text, and litigants could access the platform with any online remote device. But in most respects, litigants could expect to experience a process similar to going to court on their own. These systems inform the litigant of the charge or issue, “ask” the litigant whether they would like the court to review their case, and then ask the litigant to answer questions, including an open-ended invitation to “let the court know” anything else they felt was potentially relevant. These implementations are easy to use and make the process much easier to follow than what a litigant walking into a courthouse should expect to face, but at their core, they are an online version of a pro se courthouse experience.²³ The individual locates their case, makes a request for relief, and answers questions from the court.²⁴

Matterhorn ODR soon grew to address disputes between private individuals. Early examples include ongoing family court cases, where parties negotiate in the online presence of a case manager without the need for in-person hearings,²⁵ and small claims disputes, where parties use an online text-based negotiating (chat) space (and perhaps online mediators) to engage in informal discovery or settle their case outright. These ODR implementations sought to reduce default by making it easier for everyone to come together outside of court in an informal way before being compelled to come together in court. Parties usually negotiate a resolution, and by making online negotiation and mediation free, easy to use, and court-sanctioned, courts were soon playing an important role via ODR in a significant fraction of cases. What’s more, some tentative evidence hints that early engagement with court-connected ODR promotes traditional courtroom engagement later, which might have social benefits,²⁶ even if a case ultimately ends in face-to-face litigation.

Regardless, first-gen ODR works by moving courtroom or court hallway activity to a more amenable online venue that can be streamlined/individualized for the type of case. A pro se litigant may find it easier to negotiate with a counterparty or contest a civil infraction through an ODR platform, but such litigants are just as “pro se” during an online interaction as they would have been during an in-person tête-à-tête.²⁷ Whether first-gen ODR moves into asynchronous text-based exchanges or real-time video-based hearings (or any number of other ways parties can communicate, make offers and demands, share/present information, and work through outcome-determinative decisions), existing ODR platforms can make dispute resolution easier, faster, cheaper, and therefore more accessible, but the value of legal advice is likely to matter just as much as it does in traditional settings. True, more “have-nots” will be able to use courts and access the law. But the “haves” (with their lawyers, experience, and mastery of the rules of the game) will remain just as privileged (if not more so, given digital divide concerns) relative to their “have-not” counterparts as before.

Empirical evidence on ODR outcomes is consistent with this story. This expanding literature speaks to the improvements enjoyed by pro se litigants (as opposed to represented parties): Cases proceed more quickly, default rates plummet, and communication between parties, court staff, and judges increases.²⁸ This accessibility leads to more accurate outcomes (primarily by reducing default), giving more muscle to substantive law and reducing the role litigation costs play in determining legal outcomes.²⁹ In the case of Matterhorn, at least, litigants also report that they find ODR proceedings fair, the online process easy to understand, and the software straightforward to use.³⁰ On the whole, ODR-based improvements in pro se litigant outcomes (both quantitative and qualitative) appear significant, although these advances are relative to a pro se baseline where the relevant control groups of litigants are also unrepresented.

12.1.2 From Courtrooms to ODR: Responding to Critics

Moving from courtrooms to ODR is no panacea, of course. Critics raise a number of concerns, including the importance of the courtroom and human interaction in how litigants experience justice, the ability of efficiency-oriented designers to reduce choice and induce compliance, the lack of transparency in ODR hearings, the rigidity and inflexibility of procedures, and many others.³¹ Most of these complaints, however, focus less on ODR’s basic principles and more on the weaknesses critics observe in specific first-gen systems.³² Like traditional procedures, ODR will only be as good as its design. Yet ODR’s inherent flexibility gives courts the means to resolve many worries raised about existing systems, if they have the will: for example, all ODR-related policies, choices, and outcomes can be made public, and the workflow can be designed to maximize litigant voice, even if current instances of ODR score poorly on these measures. Furthermore, ODR is almost always an option, not a requirement, so those who object to ODR must defend disallowing low-cost access alternatives for litigants who retain more expensive “Cadillac” access to justice and yet prefer ODR when given a choice.³³

More importantly, most criticisms fail to reckon with the very real problems of traditional adjudication, especially in low-stakes cases. Detractors compare ODR processes to a stylized and idealized version of traditional adjudication.³⁴ But this perspective ignores the existing brick-and-mortar system’s huge access-to-justice issues – including regressive costs, biases, disparities, confusion, and intimidation – as well as the paper-thin procedures that many if not most litigants experience in courtrooms. These critics compare the best of courts to the worst of ODR.

Some criticisms rightly focus on ODR being peddled by the private sector and the implications of long-term profit motives.³⁵ But there is nothing inherent in ODR as a concept that requires deferring to a private vendor; courts can and do build their own ODR systems (albeit, often via work-for-hire, which is par for the course when it comes to government software adoption). There are potentially negative, more indirect consequences to making courts and the law easier to access, too. Once lawsuits are extremely easy to file, answer, and navigate, more disagreements will become lawsuits. While ODR can be designed to balance access costs for plaintiffs and defendants, for instance, it may actually increase litigation rates. But the argument that making courts more efficient and accessible in a party-neutral way might be socially problematic simply proves too much; a corollary would be that courts ought to move back to pen-and-paper orders and file cabinets.

12.1.3 Auguries: First-Gen ODR and the Representation Gap

With respect to pro se litigants and the “representation gap,” at least some evidence suggests that ODR systems, even first-generation ones, can level the playing field just as retaining legal representation does. For instance, ODR proceedings in the traffic context are associated with fewer race- and age-based disparities, either because switching to online proceedings (for example, text-based, asynchronous communication or at-home, video-based hearings) differentially benefits some groups over others or because ODR platforms reduce implicit bias by limiting decision-maker exposure to legally irrelevant identity traits.³⁶ The precise mechanism here is unclear, but this reversal is important and ties into questions about the benefits of corporeal representation in court. Lawyers “represent” their clients and so may disrupt implicit biases or other cognitive/behavioral distortions that attach to litigants who appear in person on their own. ODR may do this, too. At the same time, by offering litigants an alternative to a single, one-size-fits-all track, any single limitation a litigant might have in, say, communication (e.g., difficulty speaking in open court) is less likely to matter. In this sense, the addition of ODR makes our legal system more robust in its ability to accommodate pro se litigants.

Existing ODR platforms also implicitly provide guidance on the law and litigation process to litigants. For instance, ODR hearings are configured for the litigant and legal issue in question. All content is targeted and laid out in a single dashboard, and material that speaks to irrelevant contingencies can be omitted. Now consider a litigant’s experience walking into a state courthouse, which is, by design or happenstance, an all-purpose space we use to resolve many types of legal matters. A courtroom is not hung with customized signs. The litigant must digest, sort, and navigate. This is costly and often confusing and scary. By contrast, ODR is akin to being met at the door by an usher who helps you to where you need to be, reminds you of your to-dos, and tsk-tsks when you cut a corner or appear distracted. ODR makes the experience less stressful and reduces error. Lawyers also play this role. Thus, even first-gen ODR mitigates the effect of pro se status, but ODR today is better analogized to an usher than to a counselor. A lawyer can help you decide whether going to your seat is a good idea; an usher can just tell you how to get there.

12.2 A New Frontier: Next-Generation Court-Connected ODR

In this section, I contend that legal representation – what lawyers do for clients – can be disaggregated into distinct functions and that many of these can be approximated, achieved, and perhaps even exceeded within a pro se architecture of next-gen ODR. The confluence of online technology, data collection and storage, and computational power in effect blurs the distinction between “mere” access to a forum like a courthouse and actively supplying pro se litigants with many of the benefits of legal representation. When designing and implementing ODR systems, courts that care about access to justice and successfully resolving society’s disputes ought to set aside any historical reticence to offering robust litigant support – even when that support overlaps with what lawyers do, such as providing objective information, even-handed guidance, and physical representation in court.

Thinking about next-gen ODR begins with a clear-eyed discussion of what (human) lawyers do and what they bring to the table – as well the drawbacks of legal representation (e.g., agency costs, limited communication). Lawyers serve many functions in a litigation context. Lawyers offer predictions,³⁷ counseling, representation, influence, and access,³⁸ and the option to litigate in ways that raise rivals’ costs. Not surprisingly, represented parties often experience better litigation outcomes than pro se litigants.³⁹ But a better litigation outcome does not equate to a litigant being better off overall, and involving lawyers in dispute resolution is socially costly,⁴⁰ especially when attorney efforts on opposing sides are offsetting. From society’s perspective, the relevant question is not how much a party’s individual prospects improve with a lawyer, but how much net value a lawyer adds to the case in terms of outcome accuracy and its attendant benefits.

Even when a lawyer has critical skills and experience, a litigant’s choice to hire that human being is always an imperfect strategy born of necessity. Lawyers as representatives suffer from agency issues,⁴¹ at times second-guessing their client on the basis of “independent professional judgment.”⁴² Even when interests are roughly aligned, the frictions inherent to human communication limit the value of legal representation. Litigants hire people – not their expertise and experience. Litigants cannot download an attorney’s judgment and know-how, nor can they upload the whole of their history and hopes. A client must communicate their preferences, constraints, and knowledge about the case to the attorney without knowing the law or what is possible and relevant. A lawyer has only limited time to prepare to “channel” their client when the moment of truth arrives. Far superior would be the ability to evaluate one’s own case through the prism of a lawyer’s training and professional history (and perhaps objectivity). All of this is to say that legal representation, even at its best, is far from perfect.

In what follows, I identify three specific benefits of legal representation – outcome prediction, options guidance, and obfuscation/translation – and I argue that they can be approximated through court technology. When evaluating this claim, keep in mind that the relevant comparison is to a costly, limited, and sometimes selfish human agent. I do not claim that ODR platforms can or will render lawyers obsolete. But in weighing its relative merits, enhanced ODR may be able to deliver, implicitly or explicitly, many of the benefits of an expert counselor. I also do not claim that ODR systems have yet to push any of these frontiers.⁴³ Rather, I maintain only that adopting courts ought to think holistically about how ODR can support litigants in ways that reduce the pro se representation gap. By keeping in mind what lawyers do and how clients and society benefit from their involvement, future ODR systems may generate better outcomes and more satisfaction.

12.2.1 Experience and Predicting Outcomes

One of the most important services a lawyer provides a litigant is an informed, experienced perspective on the likely outcome of a case, with some overall take on whether the outlook is “good.”⁴⁴ Typically, during intake, the prospective litigant describes the nature of the dispute, key aspects of the case, and the like, and the lawyer may even offer some preliminary advice. Once retained, however, the lawyer will engage in more intense prediction-oriented activity on behalf of the client, perhaps after researching the law, collecting more information, and weighing the necessary investment, probable venue, expected legal rulings, possible judges, and even likely jurors. These predictions are necessarily fuzzy; there is considerable uncertainty, but as time resolves many contingencies (e.g., the identity of the opposing attorney), predictions will become more accurate. Consequently, the lawyer is likely to revisit the prediction task repeatedly, presumably at each important decision point, when the litigant might seek advice on how to proceed. In a traditional litigation setting, the prediction problem is a complicated one; the environment is relatively unstructured, and the variables are nearly infinite. There are also conflicts of interest and cognitive biases tugging on a lawyer’s predictions.

A lawyer’s ability to “predict” a dispute’s outcome builds on the human equivalent of supervised learning.⁴⁵ In most cases, the client defines a “good” outcome for the lawyer.⁴⁶ But even if the target is unclear or moving, the client and the lawyer are normally decided on the type of outcome that matters (e.g., damages, liability, share of custody, opportunity to be heard, etc.). The lawyer’s task is to take the client’s account, the law, the client’s set of plausible “moves,” the presiding judge, and anything else observable to the lawyer and then predict an outcome using the agreed-upon metric of success. This prediction may come in the form of an expected outcome alone and possibly with some measure of uncertainty that implicitly conveys the expected accuracy of the prediction (e.g., “I think you’ll get $75K, give or take $10K”). If the client defines a minimally acceptable outcome, the lawyer will review the likely consequences for each set of potential moves and either report that this outcome is unrealistic or that taking a particular set of actions will be necessary (under current circumstances).

How does a lawyer do this? The lawyer effectively cognitively “models” prior cases to understand the complicated relationships between facts, choices, and outcomes. Put another way, lawyers detect patterns between predictors and outcomes.⁴⁷ The greater the number and variety of cases and types of predictors that lawyers incorporate into their modeling, the more flexible, unbiased, and accurate their predictions can be. A mental model is what we mean when we talk about the value of experience. An expert lawyer has witnessed many cases with many different characteristics proceed under many different circumstances. Delivering accurate predictions is helpful because they can guide a litigant’s behavior toward their preferred outcome, whatever it happens to be. If the litigant’s goal is to maximize their net “return” from a dispute, a schedule of litigation strategies (including their costs) and their likely outcomes (and uncertainties) produced by a lawyer is what a litigant needs to succeed.

ODR platforms can perform this task. In fact, under the circumstances, they may be able to do a better job.⁴⁸ First-gen ODR platforms already access an individual litigant’s case, drawing information from the court’s case management system. Once a case resolves, the platform archives the record and moves onto the next case. But there is no reason an enhanced platform cannot build models from all prior cases and even from data outside the court’s case management system. Models can incorporate any plausible predictor, including judge identity, hearing timing, and docket backlog. By contrast, lawyers build models only from their own cases or those about which they hear or read (inevitably with error and uncertainty), and only with what they can observe about those cases and their circumstances. In effect, an enhanced ODR platform could display a distribution of how similar past cases – or, with enough data, only identical ones – fared using the litigant’s preferred measure of success. These “predictions” (tendered as descriptions of what happened in prior cases – not as promises or legal advice!) can be presented at decision points and can be joined with statistics to impart precision.⁴⁹

The challenges to operationalizing these ideas are manageable.⁵⁰ In many ways, litigation that occurs in an ODR environment may be more amenable to accurate prediction than litigation in a more traditional environment because the platform can easily capture the information about cases, choices, and outcomes needed for prediction. An ODR system may be more structured and less nuanced, either by necessity or design, which might also simplify the prediction problem. Consider an enhanced platform with asynchronous, text-based communication that requires parties to answer the same questions in the same order with the same answer options as part of an online hearing (versus open court with a judge asking different questions in different ways and expecting a narrative response on the spot) and where the system necessarily prevents or obscures certain actions (e.g., a litigant can’t visibly sigh or roll their eyes at a judge).⁵¹ The number of predictors would no longer be infinite because the environment eschews legally irrelevant details; in other words, the medium itself might simplify some of the prediction problems a lawyer would normally face in court.⁵²

12.2.2 Navigating, Counseling, and Identifying Options

Lawyers often present options. They take raw facts and abstract law and suggest possible legal solutions. They also identify various strategies (or implement them directly), and they help clients weigh the upsides and downsides of those strategies. Lawyers do not necessarily perform this task well. The quality of counseling, when it occurs, is often suspect. Lawyers implicitly build models, but they also suffer from biases (e.g., availability), have limited observational and processing capacity, and must navigate their own conflicts (like economizing on time and avoiding high-risk innovations). In most contexts, lawyers are also busy. Identifying options, discussing them with clients – these activities take time. Consequently, lawyers work from scripts,⁵³ stocked with standard “moves” that usually do the trick in the vast majority of situations. Lawyers may deliver these options in rote fashion, with little thought paid to details that are individually unlikely to make a material difference in the long run (even if, collectively, such details can alter a legal dispute’s trajectory).

This account is designed to present a human lawyer as a fairly simple algorithm. The lawyer asks intake questions, processes the answers, identifies the nature of the dispute and a set of typical solutions, explains the most common approaches to the client, and translates the client’s reaction into a set of choices or next steps. Two tasks are occurring here. One is pattern recognition (the main point here). The second is prediction combined with an interpretation of what the client values. Put differently, lawyers determine the sort of dispute they face, collect relevant information for a dispute involving such features, identify an array of potential approaches or strategies, and assist the client in understanding and deciding between them.

This last step – helping a litigant understand and evaluate various options – falls squarely in the camp of outcome prediction. Enhanced ODR can define a large number of potential outcomes. Not all, true, but easily those outcomes that would matter to 99 percent of litigants. Counseling between options can be carried out simply by informing litigants of the likelihood that certain outcomes will manifest if the litigant pursues, say, track 1 or track 2.

With a real lawyer, counseling involves nuance.⁵⁴ But much of that nuance is the lawyer attempting simultaneously to ascertain a client’s preferences. An enhanced ODR platform would do less “screening” and instead make much more information available to the client so they may digest with their own priorities in mind instead of relying on a black-box lawyer. There are challenges here: Litigants also face cognitive limits, and while they may have more time to immerse themselves in their own affairs, too much data can be worse than too little.⁵⁵ Just as an intimidating courthouse can paralyze, so too can an environment that dumps unstructured information on litigants and then asks them to sift it.⁵⁶ Thus, ODR platform structure and design must not only be accessible but also support effective decision-making.⁵⁷ We already use technology to help people make important choices about many things.⁵⁸ Even in the legal-aid and access-to-justice contexts, existing decision support tools streamline processes, minimize confusion, and improve decision-making.⁵⁹ Efforts are imperfect but improving,⁶⁰ and one must remember that the relevant benchmark is a pro se world with no support whatsoever.

To counsel, lawyers categorize a dispute and then compile the information necessary to identify options, avoid legal and factual pitfalls, and assemble plausible strategies (matched with predictions). This is complex, and early versions of enhanced ODR will likely be subject-matter specific. But precedents for algorithmic technology of this sort already exist, and courts should avoid letting the perfect be the enemy of the good. Legal aid groups already deploy triage and intake forms that are “smart.”⁶¹ An initial goal for next-gen ODR might be to determine a litigant’s eligibility for digital or other assistance by collecting critical information about the litigant’s situation.⁶² The law’s many branches can be incorporated directly into questions put to users.⁶³ Structure in the law and implicit groupings of fact patterns will lay bare most likely strategies.

There is no limit to how complex any enhanced ODR data collection process might be. But this is also true when a litigant hires an attorney: The litigant explains their situation, and the attorney asks questions in response. The attorney may also look over papers, review video, or examine other evidence. This exchange might take a while, but lawyers ultimately triage and end their information gathering, and ODR software can too. As natural language processing improves, faster intake methods that ask open-ended questions instead of closed-ended questions can reduce the total number of questions.⁶⁴ Analysis of narrative answers can trigger relevant follow-up inquiries.⁶⁵ But there are reasons doctors don’t only ask “so, what’s bothering you?” at an appointment. Instead, you are first subjected to a long list of questions designed to prompt you to think about every system and part of your body.⁶⁶ Any natural language response to an open-ended question like “what’s your legal problem?” may come from a person unfamiliar with the law whose take on what matters may be off-base.⁶⁷ Still, natural language responses, perhaps even voice submissions, might be a better, more accessible option for some litigants.⁶⁸

A barrier to making data-collection functionality successful in next-gen ODR platforms is simply how long it might take a litigant to get in the front door. So much of what is good about ODR is that it is easy to use and minimally costly to try. Next-gen ODR might dissuade people from using courts all over again if it bogs down with seemingly countless questions and checklists. But consulting with a lawyer takes no small amount of time, and stacks of forms are not new to human institutions. Nevertheless, enhanced ODR platforms might be more attractive to more people if guidance and counseling functions were designated as optional.

12.2.3 Replication/Obfuscation/Translation versus Representation

Lawyers aren’t just analytical input-output machines offering a litigant legal expertise in the background. Lawyers are corporeal and play a physical role on the stage of our justice system.⁶⁹ They actually “do” law by going to a courthouse to serve as their client’s mouthpiece. The corporeal representation function of lawyering matters in at least three ways in the context of court-connected ODR: lawyers replicate a litigant’s ability to be physically present, lawyers obfuscate litigant traits, and lawyers translate and distill a litigant’s lay arguments into an “expert’s” legal arguments. Considering these roles separately demonstrates that enhanced ODR can advance these functions through text on a screen or other digital-information display even without a human body in a courtroom.

First, lawyers allow clients to be in two places at once. This function reduces the cost of litigation to clients, courts, and other parties, since schedule conflicts can slow litigation. Representation offers flexibility to meet competing obligations. Often, a client and their attorney come together in a courtroom at critical junctures, but there are many stages when a lawyer can physically “be” the client for purposes of advancing a case. Technically, ODR is unable to fulfill this function because, whatever it is, software does not stand in for a litigant before other parties or decision-makers. Yet, in an ODR environment, there is arguably no need for such a service in the typical case. Indeed, unlike hearings that take place at a particular time and place, ODR can be more flexible, accessible, and efficient, making the use of a lawyer to “cover” for someone less important.

Second, lawyers can “obfuscate” client traits. When judges walk into a courtroom and see a litigant’s race, gender, age, or other identity traits, evidence suggests that unconscious implicit bias, if not explicit bias, affects subsequent decision-making.⁷⁰ Furthermore, the anticipation of such bias can alter a litigant’s ability to communicate well in a courtroom. One strategy for a litigant facing the possibility of discrimination is to hire a lawyer with different – perhaps socially “preferred” – characteristics to block, blunt, or attenuate any such bias. Lawyers even advertise on this basis – for example, hinting at the advantages of a female lawyer defending a male defendant accused of sexually assaulting a female victim.⁷¹ True, having a lawyer does not necessarily preclude a judge from ascertaining litigant identity traits, but outside of explicit, intentional discrimination, even sharing the stage with an in-group lawyer may disrupt the psychological processes that lead to bias.

For those unable to reduce their exposure to bias by using a lawyer,⁷² ODR offers a substitute, perhaps superior solution. ODR can structure online communication to insulate judges and other decision-makers from legally irrelevant information that might trigger implicit biases (or allow purposeful discrimination). At least some first-gen ODR systems, for example, do not include a litigant’s driver’s license picture in the judge’s dashboard. At least one court collects required picture ID information only after the judge decides the case but before the ruling is entered. First-gen ODR systems, by tracking traditional in-person processes, still tend to make a litigant’s name visible (which may reveal gender and ethnicity) and, in some instances, date of birth (which, with some math, reveals a litigant’s age).⁷³ ODR platforms can go further by thoughtfully, comprehensively obscuring litigant traits that are legally irrelevant (or even legally relevant when they are likely to bias or confuse decision-making),⁷⁴ whenever it is consistent with fair process.

Third, lawyers provide a “translation” function to clients. Lawyers distill what they learn from clients into core substantive facts, and then assemble and present those facts in the highly reticulated way that legal actors expect from legal professionals.⁷⁵ This professional repackaging may augment a litigant’s story and substantive arguments by making them more palatable, reliable, and understandable to a judge.⁷⁶ Or it may just be a key into the club. If there are lawyers on both sides, any imprimatur may cancel out, yet the dynamics of the prisoner’s dilemma apply, so all who can “lawyer up” still do so. Pro se litigants are left behind. Even if translation and delivery by an expert improves the litigant’s prospects (relative to a counterparty), it remains an open question whether this function enhances the accuracy or efficiency of any adjudication. Regardless, if only one party has access to an attorney’s stamp of approval or can speak “legalese,” a pro se gap might develop.⁷⁷

Enhanced ODR can diminish the role that legalese and professional status might play in litigation by reducing their use, making them ambiguous or less salient, or facilitating a pro se litigant’s ability to employ them within the platform. ODR design can encourage (or require) litigants to use plain language, either via the structure of its data collection strategies (e.g., forms) or through ex post screening of user language. Alternatively, one can imagine a more involved ODR process that educates litigants about the meanings of legal words or legal communication norms or that offers something closer to a translation service, much the way smart form procedures operate today, by giving people choices. Either way, ODR platform “rigidity” in the allowable scope and style of communication can be a disparity-reducing positive;⁷⁸ such structure can ensure that parties speak the same language while also giving them equal opportunities to be heard.

Importantly, reducing “degrees of freedom” in ODR communications can also close a back-door source of implicit bias. An ODR system that scrubs case materials of identity-trait data after having encouraged a litigant to submit an open-ended statement may be closing the barn door after the horse has bolted. Intentionally or unintentionally, litigants reveal personal traits in their communications:⁷⁹ they explicitly indicate their race, gender, occupation, or age,⁸⁰ or they implicitly reveal these traits through language that correlates with demographic characteristics.⁸¹ In any event, to the extent that legal representation liberates litigants from the need to speak legalese in the courtroom and insulates litigants from implicit bias by insulating judges from triggering face-to-face interactions, ODR systems have the potential to do much the same through careful design and creative solutions.

12.3 Conclusion

Courtrooms (spaces) and lawyers (people) complement each other in the resolution of disputes. Courts appear to be fixed, reactive, and generically available to all; lawyers, by contrast, seek justice by customizing how courts resolve disputes to align with client circumstances and preferences. A lawyer “configures” a court and the law it embodies by leveraging their experience, expertise, and corporeality to serve their client’s interests. First-gen ODR makes courts more accessible, but platform technology, data science, and thoughtful design allow for so much more. In this chapter, I argue that courts should view ODR going forward not only as a potential opportunity for courtroom-like engagement in the traditional sense but as a substitute for many of the services historically provided by lawyers, which, in the end, are mostly about helping litigants understand how a court will perform and what it will produce in the specific instance of their case. Conceiving of ODR in this way – as the use of online communication technology and data science to make it easier for potential litigants to use, understand, and benefit from law in action – will get us much closer in the years ahead to “courts as a service.”