By Kathrin Hartmann & Georg Wenzelburger

Algorithms are increasingly used in different domains of public policy. They help humans to profile unemployed, support administrations to detect tax fraud and give recidivism risk scores that judges or criminal justice managers take into account when they make bail decisions. In recent years, critics have increasingly pointed to ethical challenges of these tools and emphasized problems of discrimination, opaqueness or accountability, and computer scientists have proposed technical solutions to these issues. In contrast to these important debates, the literature on how these tools are implemented in the actual everyday decision-making process has remained cursory. This is problematic because the consequences of ADM systems are at least as dependent on the implementation in an actual decision-making context as on their technical features. In this study, we show how the introduction of risk assessment tools in the criminal justice sector on the local level in the USA has deeply transformed the decision-making process. We argue that this is mainly due to the fact that the evidence generated by the algorithm introduces a notion of statistical prediction to a situation which was dominated by fundamental uncertainty about the outcome before. While this expectation is supported by the case study evidence, the possibility to shift blame to the algorithm does seem much less important to the criminal justice actors.

Policy Sci 54, 269–287 (2021)

By David Benjamin Joyce 

On October 25, 2023, Robert Card executed 18 civilians in mass shootings at Just-In-Time Recreation and Schemengees Bar and Grille Restaurant in Lewiston, Maine. Three months before the rampage, Card spent 14 days in a New York psychiatric hospital. His violent tendencies were known to family members, the Army Reserves, and law enforcement officials in Maine. Despite the warning signs, Card never faced a firearm prohibition. He maintained control of a high-powered Ruger SFAR rifle, which he turned on victims ranging in age from 14 to 76. The Lewiston tragedy brought renewed focus on Maine’s risk-based firearm removal statute. Phase One of this dissertation examines barriers and facilitators to use of Maine’s statute from the perspective of law enforcement officers, prosecutors, medical providers, and researchers in Maine. Phase Two of this dissertation reviews risk-based restriction statutes in three comparison states – Connecticut, Maryland, and Vermont – and examines implementation outcomes. Semi-structured interviews with stakeholders form the basis for the qualitative data in this study. The responses led to identification of key barriers and facilitators to effective implementation of risk-based firearm statutes. From these emerging themes, this dissertation offers eight recommendations to improve Maine’s risk-based firearm removal program. A plan for change is presented using an adaption of the Overseas Development Institute’s RAPID approach. The plan for change includes recommendations for legislative modification by the Maine legislature and implementation strategies to be employed by local stakeholder groups. Although no policy can eliminate the risk of gun violence, adoption of the recommendations in this dissertation will reduce the risk that the tragic events of October 25, 2023, repeat in the State of Maine.

Chapel Hill, NC: University of North Carolina, 2024. 140p.