Abstract A common criticism of the use of algorithms in criminal justice is that algorithms and their determinations are in some sense “opaque”—that is, difficult or impossible to understand, whether because of their complexity or because of intellectual property protections. Scholars have noted some key problems with opacity, including that opacity can mask unfair treatment and threaten public accountability. In this paper, we explore a different but related concern with algorithmic opacity, which centers on the role of public trust in grounding the legitimacy of criminal justice institutions. We argue that algorithmic opacity threatens the trustworthiness of criminal justice institutions, which in turn threatens their legitimacy. We first offer an account of institutional trustworthiness before showing how opacity threatens to undermine an institution's trustworthiness. We then explore how threats to trustworthiness affect institutional legitimacy. Finally, we offer some policy recommendations to mitigate the threat to trustworthiness posed by the opacity problem.
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CRIMINAL JUSTICE INTERVENTIONS DURING THE OVERDOSE CRISIS: NOTEWORTH TRENDS AND POLICY CHANGES
Executive summary As policymakers and criminal justice agencies review how they have addressed problems related to illegal drugs over the past decade, it is useful to examine relevant data and policy changes from this period. This paper first analyzes trends in multiple criminal justice indicators related to drugs, focusing primarily on the period from 2010 onward. It then highlights a handful of noteworthy policy changes that have been implemented, accelerated, or in some cases reversed during the ongoing overdose crisis. Finally, it presents some key findings from the analysis and offers some recommendations to policymakers and criminal justice practitioners.
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- Award ID(s):
- 2146230
- PAR ID:
- 10639656
- Publisher / Repository:
- Brookings Institution
- Date Published:
- Format(s):
- Medium: X
- Institution:
- Brookings Institution
- Sponsoring Org:
- National Science Foundation
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