No abstract

In Roper v. Simmons (2005), the U.S. Supreme Court banned the death penalty for offenders under the age of 18 years. Central to Simmons's defense was new brain imaging evidence suggesting that the regions of the brain responsible for decision making and impulse control are not as well developed in adolescents as in adults, thereby rendering adolescents less culpable for the crimes they commit. Although these images were not explicitly cited in the Court's decision, they were hailed by anti-death penalty advocates as the wave of the future. However, legal advocates and scientists should be cautious in using cutting-edge neuroscience for criminal justice purposes for several reasons. First and foremost, no definitive link between brain structure and deviant behavior has been established. Furthermore, very little is known about the developmental threshold that separates juvenile decision-making ability from adultlike decision-making ability.

Citizen video and other publicly available footage can provide evidence of human rights violations and war crimes. The ubiquity of visual data, however, may overwhelm those faced with preserving and analyzing it. This article examines how machine learning and computer vision can be used to make sense of large volumes of video in advocacy and accountability contexts. These technologies can enhance the efficiency and effectiveness of human rights advocacy and accountability efforts, but only if human rights organizations can access the technologies themselves and learn how to use them to promote human rights. As such, computer scientists and software developers working with the human rights community must understand the context in which their products are used and act in solidarity with practitioners. By working together, practitioners and scientists can level the playing field between the human rights community and the entities that perpetrate, tolerate, or seek to cover up violations.

DNA analysis is increasingly used to identify the remains of victims of conflicts and disasters. This is especially true in cases where remains are badly damaged and fragmented, or where antemortem records are unavailable. Incidental findings (IFs)—that is, genetics-related information for which investigators were not looking—may result from these identification efforts employing DNA analysis. Because of the critical role played by family members of the missing in identification efforts, as well as the familial nature of DNA, identification initiatives employing DNA analysis are particularly prone to reveal IFs about familial relationships, such as misattributed paternity or false beliefs about sibling relationships. Despite forensic scientists’ widespread awareness of the possibility of generating IFs, to date there has been relatively little explicit guidance about their management. This paper fills that gap. It offers substantive guidance about the ethical management of IFs in this context. To ensure that the analysis addresses actual needs and practices in the field, one author (JDA) conducted semi-structured interviews with key informants from six regionally diverse organizations involved in post-conflict or post-disaster identification efforts. The paper first describes how methods of DNA analysis give rise to IFs. Next, it explains the importance of developing an ethically justified general policy for managing IFs and discusses features of DNA identification efforts that are relevant to such a policy. Then it presents an argument in support of a general policy of nondisclosure—specifically, that considerations of fair access to the individual and social benefits of identification efforts, and the concern to minimize and fairly distribute the risks of participation, support a policy of nondisclosure. It concludes by considering some implications of this argument for the choice among scientific practices involved in using DNA analysis to identify human remains, as well as for managing non-genetic incidental findings.