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Report on Algorithmic Risk Assessment Tools in the U.S. Criminal Justice System

This report was written by the staff of the Partnership on AI (PAI) and many of our Partner organizations, with particularly extensive input from the members of PAI’s Fairness, Transparency, and Accountability Working Group. Our work on this topic was initially prompted by California’s Senate Bill 10 (S.B. 10), which would mandate the purchase and use of statistical and machine learning risk assessment tools for pretrial detention decisions, but our work has subsequently expanded to assess the use of such software across the United States.

This report documents the serious shortcomings of risk assessment tools in the U.S. criminal justice system, most particularly in the context of pretrial detentions, though many of our observations also apply to their uses for other purposes such as probation and sentencing. Several jurisdictions have already passed legislation mandating the use of these tools, despite numerous deeply concerning problems and limitations. Gathering the views of the artificial intelligence and machine learning research community, PAI has outlined ten largely unfulfilled requirements that jurisdictions should weigh heavily and address before further use of risk assessment tools in the criminal justice system. Using risk assessment tools to make fair decisions about human liberty would require solving deep ethical, technical, and statistical challenges, including ensuring that the tools are designed and built to mitigate bias at both the model and data layers, and that proper protocols are in place to promote transparency and accountability. The tools currently available and under consideration for widespread use suffer from several of these failures, as outlined within this document. We identified these shortcomings through consultations with our expert members, as well as reviewing the literature on risk assessment tools and publicly available resources regarding tools currently in use. Our research was limited in some cases by the fact that most tools do not provide sufficiently detailed information about their current usage to evaluate them on all of the requirements in this report. Jurisdictions and companies developing these tools should implement Requirement 8, which calls for greater transparency around the data and algorithms used, to address this issue for future research projects. That said, many of the concerns outlined in this report apply to any attempt to use existing criminal justice data to train statistical models or to create heuristics to make decisions about the liberty of individuals…”

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