Data analytics companies are a relatively new type of information firm, the result of mass consolidation across information markets and a proliferation of data analysis technologies. We think of companies like RELX (Reed Elsevier LexisNexis) and Thomson Reuters as publishers, but they've made a transition away from being traditional content providers. Instead, they're crunching their warehouses of digital content through AI software, machine-learning technology, complex algorithms, and other types of data analytics systems to form new information products to sell. They've taken over multiple information markets, and they use their informational power to build "risk" and "insight" products that provide predictive and prescriptive information to law enforcement, lawyers, academic institutions, investors, and other entities that make big decisions about our lives. In an era of informational capitalism, they're engaging in anticompetitive, cartel-like behavior to maintain and expand their control of data and information markets.
This chapter focuses on the data analytics' companies' personal data brokering and "risk" data analytics products. Our current data analytics companies were some of the first data brokers. Instead of commercial data brokering (selling our data to companies that target us with ads), the data analytics companies sell our data to government agencies (including law enforcement) and to institutions that provide insurance, housing, employment opportunities, housing, and health care—essential services upon which we rely. The data companies amass invasive data dossiers on each of us by gathering data from thousands of sources, updated in real time. This data is used to assess whether we'll commit crimes, default on loans, use drugs, or pose other "risks." Governments work with data analytics companies to skirt their constitutional obligations and institutions use our data to avoid regulatory obligations meant to protect our privacy and provide transparency and public accountability.
This chapter focuses on the data analytics companies' academic research and "academic metrics" data analytics products. A small oligopoly of companies controls most of the world's academic research journals. Academic research is often publicly funded, and often conducted at public institutions by public employees. But the fruits of our academic labor are treated like private property by companies that are acting, more and more, like data analytics firms. The companies treat our public research like their personal portfolios of copyright assets. Their paywalls prevent people from accessing the information they need in order to make the best decisions and conduct their own research. People who can access the research platforms are subjected to surveillance because the companies have turned their websites into data collection tools that fuel data analytics products grant funders and research institutions use to determine which projects receive grant funding and who gets hired.
This chapter focuses on the data analytics' companies' legal information and "legal insights" data analytics products. Together, a few data analytics companies paywall our public laws, making it impossible for anyone who can't afford their legal information platforms to see the most accessible, up-to-date versions of case law, statutes, etc. The government edicts doctrine says that the law should be publicly accessible, but companies have found ways to turn the law into property they can sell. Now they are finding ways to use their legal information platforms, and personal data drawn from them, to help those who can afford legal data analytics services game the law by predicting which judges will be most favorable and which legal strategies will be the most lucrative. Meanwhile, pro se litigants, including prisoners who are often left to represent themselves, are unable to access the legal information they need.
This chapter focuses on data analytics' companies' financial data and analytics products. There is a wealth of financial information available online, but that glut of financial information is almost impossible to vet or verify. The top-shelf, most useful financial information is paywalled by a few financial data companies. The privatization of corporate data creates a two-tiered information system: the public can access outdated, erroneous, and hard-to-read public information, and people who can afford to subscribe to fancy financial data services can get minute-by-minute financial data and investment information. This information asymmetry causes the very problems that the Securities and Exchange Commission was tasked with preventing—consumers fall prey to online stock-buying scams and panics, losing money on bad deals, while people who can afford Bloomberg terminals and other expensive data tools have faster access information to better financial information than the general public.
This chapter focuses on the data analytics' companies' news information services and archives, which provide news content and feed the companies' other data analytics products. When public news becomes private property owned by data companies, both the quality and availability of news declines. Private data companies have participated in the collapse of the news industry. Over the past decade, local news sources have been shuttered and sold off to national news corporations, which has made local news hard to get, and has made the news that people receive more biased towards the viewpoints of whatever company owns the remaining news services. News was once considered a public necessity, and news infrastructure was supported and subsidized by federal, state, and local government. Moving away from government-supported news information systems has led to inaccessible, or disappearing, local news, and to the spread of misinformation instead of vetted, verifiable news.
This chapter concludes the book with a bird's-eye view of how data analytics companies have limited our information access and privacy online and urges the reenvisioning of our digital information infrastructure to prevent data cartels from interfering with information access and intellectual freedom. Information is an essential public resource, and open access to information is imperative for a healthy, informed society. Thus, we must re-up government programs that support public information access, and we must intervene to regulate data and information companies. Data analytics companies are part of our "big tech" problems and they should be under similar government scrutiny. It is still possible for public institutions to build and support public information infrastructures in our digital ecosystem.