Improving the gender balance among IT professionals by involving more women in IT spheres is a goal in many countries. In addition to achieving gender equality, it is of great economic importance, since there is a lack of IT professionals in many countries, including Russia. One possible solution to this problem is to increase the number of females in IT professions. This chapter will discuss the ICT education system in Russia, its history and major contributors to the field, careers in the field, and the relationship of these areas to gender issues. Below I give definitions of the main terms used in this chapter.

This chapter focuses on computer science (CS) education in Israel, which is known as the “Start-Up Nation” due to its high level of technological innovation and high number of start-ups in the country (Sensor and Singer, 2009). It tells a story, from a gender perspective, that starts in high school, passes through the military service and university stages, and concludes with what happens to female computer scientists in the job market, whether it be in academia or industry. We show that, as expected, external characteristics and cultural aspects matter in determining women’s participation in CS education and CS professions.

Behavioural data collection and analysis, and the beginnings of ‘mass surveillance’, can be traced back to early intelligence surveillance and political policing. Agents would gather information from multiple sources, both trivial and salient, about individuals with no prior contact with the criminal justice system, in an effort to predict their future behaviour. Often this happened in secret, and was justified by the threat of political violence. This chapter argues that much of the political thinking and technical logics of the contemporary intelligence surveillance environment have their origin in nineteenth-century political policing. It also argues that because this information gathering and analysis occurred in secret, it produced substantial social anxiety over the potential for inaccuracy, which ultimately filtered into subsequent legal protections.

Silicon Valley draws many cultures together from nearly all facets of computing to a single, sprawling 1,854-square-mile geographic location, and as of 2017, Silicon Valley boasted a population of more than three million people with over 37.5% of Silicon Valley residents having been born outside the United States (Joint Venture Silicon Valley, 2017). Silicon Valley has created a legend that has attracted people – so much so that they leave countries and continents behind to relocate there to work.

As we close this collection of many perspectives from multiple cultures and countries we hope to have shown that women’s participation in computing is largely determined by cultural factors. We hope this book has provided a convincing argument that alternative ways of thinking about, and acting on, gender and computing issues could benefit both the field and the people in it. We have argued for the examination of variables outside a gender dichotomy as possible sources of differences in women’s participation in computing. In particular, we have suggested and illustrated that a cultural approach, an approach that pays close attention to culture and environment, focuses on the many factors that can allow for, or hinder, women’s participation.

Automated profiling, predictive analytics, and data mining represent the extension of nineteenth-century statistical models through the lens of computation. Algorithmic pattern matching also has origins in supermarket management, as well as the discipline of operations research that developed through the Vietnam War. When applied to law enforcement, policing, and criminal justice, this has led to a plethora of systems used by governments, typically developed by private companies, used for intelligence, predictive policing, and criminal justice risk assessments. This chapter argues that the establishment and proliferation of these tools has cemented the primacy of statistical knowledge systems as the primary systems of evaluation by which individuals are interpreted and known by states.

This chapter will provide a current perspective of the gendered nature of computing in Australia. The underrepresentation of women is the most visible issue in this discipline, and may well be a product of the unique culture of the country that is at odds with the multicultural nature of the population. Many initiatives and interventions have been and still are in operation to encourage girls to consider a computing career. However, the proportional numbers of males and females in the discipline in universities and the workforce remains a concern in 2018.

Sweden is one of the most equal countries in the world and has been for several years (World Economic Forum, 2017; Swedish Institute, 2018). The ranking shows equality on a societal level, but in certain areas gender imbalance persists, for example, in education (Statistics Sweden, 2016). Education in Sweden, including postsecondary education, is free of charge for citizens of the European Union. Government financial contributions and favorable student loans are offered, as long as the study progress is satisfactory. Acceptance to study programs is based on grades from previous education, and in educational programs where practical skills are of importance such as art, design, and music, acceptance is also based on assessment of ability.

Access has become a keyword of the twenty-first century. However, even in the 1960s, government data collection and growing computational power facilitated new forms of statistical analysis that people thought could become new ‘intelligence’ systems. The legislative response to these threats were new data protection and information privacy regimes that included ‘data subject rights’ – mechanisms by which individuals could obtain access to information about them held by others, and rectify any inaccuracy. This type of transparency gave individuals a way to participate in the profiling regime, by attempting to ensure that the data used by profilers was accurate and relevant. Informed by the German constitutional concept of informational self-determination, limitations to profiling in data protection are premised on the idea that a person’s self-image ought to be the primary determinant of their identity. However, it is argued here that this approach loses traction as the profiling environment becomes more sophisticated.

Barlow’s declaration of independence was a cry for the preservation of the libertarian wild west of the early internet, an ideal of a space of limitless opportunity that its denizens could shape to their liking. He makes two claims here: first, that governments have no real power over the internet, which is a fundamentally unregulable, separate space, both outside of legal jurisdiction and practical reach of governments. The second – a moral claim – is that the rules of online social spaces would evolve to be better – more democratic, more free – than the rules of territorially bound nation-states.

Technology companies are the sheriffs of what used to be the wild west of the internet. In the 1990s, when the internet was young, the imagery of the western frontier really seemed like a good analogy. The internet seemed to radically decentralize power: no longer could massive publishers or broadcasters control the media; anyone could be a publisher and get their message out.1 The internet seemed inherently designed to preserve the freedom of individuals. It seemed impossible to enforce laws against the apparently anonymous masses of internet users distributed around the world. The commercial internet grew out of a military design that avoided single points of failure and was resilient against both nuclear attack and interference by hostile governments.2

In August 2017, several hundred white nationalists marched on the small university town of Charlottesville, Virginia. The rally turned tragic when one of the protesters rammed his car into a crowd of counterprotesters, killing 32-year-old Heather Heyer. The Washington Post characterized the protesters as “a meticulously organized, well-coordinated and heavily armed company of white nationalists.”1

In an article in January 2018 warning of an impending “techlash,” The Economist painted a bleak picture for the CEOs of Amazon, Facebook, Google, Apple, Netflix, and Microsoft. “Things have been rough in Europe for a while,” the article pointed out, and “America is not the haven it was” for the giants of tech that dominate the internet.1 From the presidential candidates in the next election to a group of concerned state attorneys general, The Economist predicted a great deal of anti-tech sentiment was coming from regulators. The year didn’t get much better for major tech companies from there. As the investigation into Russian interference in the 2016 presidential elections unfolded, not just Facebook, but all of the major technology companies faced a sudden shift in public opinion on a wave of negative press.

So far, we have heard a lot about how private actors are trying to regulate the internet. Governments across the world have also been very active in trying to get internet companies to regulate what information their citizens can access and share online. The decentralized, resilient design of the internet makes government censorship much more difficult than in the mass media era, where it was much simpler to embed controls within the operations of a small number of major newspaper publishers and television and radio networks. Governments are adapting, though, and quickly becoming much more sophisticated in how they monitor and control the flow of information online.

To an extent that nobody else has managed, the copyright industries have been able to bake protection for their rights into the very infrastructure of the internet. The challenge of limiting illicit file sharing is similar to many of the other difficult issues – like addressing offensive content, removing defamatory posts, or limiting the flow of misinformation – in internet regulation. How do you control what users do online without directly going after individual users? Legal actions against individuals are expensive; they only really make sense in high value cases. Changing the behavior of many individuals on a large scale is much more difficult, whether it’s users sharing copyrighted music and films or people using the internet to harass others. Any effective answer has to involve technology companies and internet intermediaries in some way, because they have the power to influence large numbers of users through their design choices and policies.