U.S./Canada

Police, prosecutors, judges, and other criminal justice actors increasingly use algorithmic risk assessment to estimate the likelihood that a person will commit future crime. As many scholars have noted, these algorithms tend to have disparate racial impacts. In response, critics advocate three strategies of resistance: (1) the exclusion of input factors that correlate closely with race; (2) adjustments to algorithmic design to equalize predictions across racial lines; and (3) rejection of algorithmic methods altogether.

In 2014, Black Lives Matter (BLM) ignited an urgent national conversation about police killings of unarmed Black citizens. Online tools have been anecdotally credited as critical in this effort, but researchers are only beginning to evaluate this claim. This research report examines the movement’s uses of online media in 2014 and 2015. To do so, we analyze three types of data: 40.8 million tweets, over 100,000 web links, and 40 interviews of BLM activists and allies.

This article examines the intersection of two structural developments: the growth of surveillance and the rise of “big data.” Drawing on observations and interviews conducted within the Los Angeles Police Department, I offer an empirical account of how the adoption of big data analytics does—and does not—transform police surveillance practices. I argue that the adoption of big data analytics facilitates amplifications of prior surveillance practices and fundamental transformations in surveillance activities.

Shoshana Zuboff provides startling insights into the phenomenon that she has named surveillance capitalism. The stakes could not be higher: a global architecture of behavior modification threatens human nature in the twenty-first century just as industrial capitalism disfigured the natural world in the twentieth. Zuboff brings to life the consequences as surveillance capitalism advances from Silicon Valley into every economic sector.

In the beginning, the World Wide Web was exciting and open to the point of anarchy, a vast and intimidating repository of unindexed confusion. Into this creative chaos came Google with its dazzling mission—“To organize the world’s information and make it universally accessible”—and its much-quoted motto, “Don’t be evil.” In this provocative book, Siva Vaidhyanathan examines the ways we have used and embraced Google—and the growing resistance to its expansion across the globe.

If you wanted to build a machine that would distribute propaganda to millions of people, distract them from important issues, energize hatred and bigotry, erode social trust, undermine respectable journalism, foster doubts about science, and engage in massive surveillance all at once, you would make something a lot like Facebook. Of course, none of that was part of the plan.

Who is a Native American? And who gets to decide? From genealogists searching online for their ancestors to fortune hunters hoping for a slice of casino profits from wealthy tribes, the answers to these seemingly straightforward questions have profound ramifications. The rise of DNA testing has further complicated the issues and raised the stakes.

We live in the age of the algorithm. Increasingly, the decisions that affect our lives—where we go to school, whether we can get a job or a loan, how much we pay for health insurance—are being made not by humans, but by machines. In theory, this should lead to greater fairness: Everyone is judged according to the same rules.

In Algorithms of Oppression, Safiya Umoja Noble challenges the idea that search engines like Google offer an equal playing field for all forms of ideas, identities, and activities. Data discrimination is a real social problem; Noble argues that the combination of private interests in promoting certain sites, along with the monopoly status of a relatively small number of Internet search engines, leads to a biased set of search algorithms that privilege whiteness and discriminate against people of color, specifically women of color.

We know DNA is a master key that unlocks medical and forensic secrets, but its genealogical life is both revelatory and endlessly fascinating. Tracing genealogy is now the second-most popular hobby amongst Americans, as well as the second-most visited online category. This billion-dollar industry has spawned popular television shows, websites, and Internet communities, and a booming heritage tourism circuit. The tsunami of interest in genetic ancestry tracing from the African American community has been especially overwhelming.