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This study was an elaboration of ideas he first proposed in 1933 in his address to the Fifth International Conference for the Unification of Penal Law (1933), which argued that attacks on racial, religious and ethnic groups should be considered international crimes. Important for the prosecution of the Nazis, it helped to establish the framework for all subsequent efforts to punish crimes against humanity.

From 1932 to 1972, the United States Public Health Service conducted a non-therapeutic experiment involving over 400 black male sharecroppers infected with syphilis. The Tuskegee Study had nothing to do with treatment. It purpose was to trace the spontaneous evolution of the disease in order to learn how syphilis affected black subjects. The men were not told they had syphilis; they were not warned about what the disease might do to them; and, with the exception of a smattering of medication during the first few months, they were not given health care. Instead of the powerful drugs they required, they were given aspirin for their aches and pains. Health officials systematically deceived the men into believing they were patients in a government study of bad blood, a catch-all phrase black sharecroppers used to describe a host of illnesses. At the end of this 40 year deathwatch, more than 100 men had died from syphilis or related complications.

“Bad Blood” provides compelling answers to the question of how such a tragedy could have been allowed to occur. Tracing the evolution of medical ethics and the nature of decision making in bureaucracies, Jones attempted to show that the Tuskegee Study was not, in fact, an aberration, but a logical outgrowth of race relations and medical practice in the United States.

This article examines memory laws as a new form of social control, demonstrating the significance of cultural memory to law and society scholarship. It focuses on two Israeli laws that seek to control public debate by giving voice to one marginalized group in order to silence another. The article presents two forms of such utilization of the law: forced forgetting and the balancing of atrocities. Forced forgetting validates the memory of one group of people over another group. Balancing atrocities equates victims, pitting the suffering of one group against that of another for the purpose of dismissing the former’s claims for recognition and redress. The 2011 Nakba Law, an example of forced forgetting, dismisses the Palestinian minority’s experience to amplify the memory of the Jewish majority, while the 2014 Jewish Nakba Law creates an analogy between Palestinian redress claims and those of the Mizrahi Jews in order to balance the atrocities that these groups suffered. We show that both forms of control have limitations that create gaps between legislation and implementation, yet their political-symbolic impact is much greater.

This article explores the effects of the legalization of international human rights on citizens and non-citizens within states. Adopting a sociological approach to rights it becomes clear that, even in Europe, the cosmopolitanization of law is not necessarily resulting in greater equality and justice. In fact, ‘actually existing’ cosmopolitan citizenship is characterized by a proliferation of status groups that concretize new forms of inequality, including those of super-citizens, marginal citizens, quasi-citizens, sub-citizens and un-citizens. Far from inaugurating a new era of genuinely universal human rights, in some cases cosmopolitan law may even contribute to the creation of conditions in which fundamental human rights are violated.

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.

Liberal and marxist theories of civil society contain a conceptual paradox of `civil society without citizenship'. This article shows how the paradox about civil society comes about through an under-theorization of the multivalent character of citizenship and rights, which in turn reflects a rather impoverished understanding of culture, discourse and symbolization. The discussion starts with two related questions about civil society: (1) where is the locus of citizenship in classical liberal and marxist theories of civil society; and (2) what implication does the conventional state-civil society distinction have for the notion of citizenship as a category of status and agency? It further distinguishes among three different theses of state-civil society relations in the two different theoretical traditions. The article will conclude by outlining an alternative theoretical strategy whereby to go beyond the conceptual impasse and to meet the challenge of globalization.

From an analysis of actual cases, three categories of bias in computer systems have been developed: preexisting, technical, and emergent. Preexisting bias has its roots in social institutions, practices, and attitudes. Technical bias arises from technical constraints of considerations. Emergent bias arises in a context of use. Although others have pointed to bias inparticular computer systems and have noted the general problem, we know of no comparable work that examines this phenomenon comprehensively and which offers a framework for understanding and remedying it. We conclude by suggesting that freedom from bias should by counted amoung the select set of criteria—including reliability, accuracy, and efficiency—according to which the quality of systems in use in society should be judged.

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.

This Article’s central claim is that these strategies are at best superficial and at worst counterproductive because the source of racial inequality in risk assessment lies neither in the input data, nor in a particular algorithm, nor in algorithmic methodology per se. The deep problem is the nature of prediction itself. All prediction looks to the past to make guesses about future events. In a racially stratified world, any method of prediction will project the inequalities of the past into the future. This is as true of the subjective prediction that has long pervaded criminal justice as it is of the algorithmic tools now replacing it. Algorithmic risk assessment has revealed the inequality inherent in all prediction, forcing us to confront a problem much larger than the challenges of a new technology. Algorithms, in short, shed new light on an old problem.

Ultimately, the Article contends, redressing racial disparity in prediction will require more fundamental changes in the way the criminal justice system conceives of and responds to risk. The Article argues that criminal law and policy should, first, more clearly delineate the risks that matter and, second, acknowledge that some kinds of risk may be beyond our ability to measure without racial distortion—in which case they cannot justify state coercion. Further, to the extent that we can reliably assess risk, criminal system actors should strive whenever possible to respond to risk with support rather than restraint. Counterintuitively, algorithmic risk assessment could be a valuable tool in a system that supports the risky.

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. First, discretionary assessments of risk are supplemented and quantified using risk scores. Second, data are used for predictive, rather than reactive or explanatory, purposes. Third, the proliferation of automatic alert systems makes it possible to systematically surveil an unprecedentedly large number of people. Fourth, the threshold for inclusion in law enforcement databases is lower, now including individuals who have not had direct police contact. Fifth, previously separate data systems are merged, facilitating the spread of surveillance into a wide range of institutions. Based on these findings, I develop a theoretical model of big data surveillance that can be applied to institutional domains beyond the criminal justice system. Finally, I highlight the social consequences of big data surveillance for law and social inequality.