Public Trust, Institutional Legitimacy, and the Use of Algorithms in Criminal Justice
| Autor: | Duncan Purves, Jeremy Davis |
|---|---|
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Public Affairs Quarterly. 36:136-162 |
| ISSN: | 2152-0542 0887-0373 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|