How do "technical" design-choices made when building algorithmic decision-making tools for criminal justice authorities create constitutional dangers? Part II
Karen Yeung, Adam Harkens

TL;DR
This paper highlights how technical choices in designing criminal justice algorithms can pose constitutional risks, emphasizing the need for collaboration between developers and legal experts to ensure legal compliance and human rights protection.
Contribution
It reveals the overlooked legal principles in algorithm development for criminal justice and advocates for integrating public law expertise into technical design processes.
Findings
Technical choices can increase constitutional dangers in criminal justice algorithms.
Legal principles are often overlooked in algorithm design and implementation.
Collaboration between developers and legal experts can mitigate constitutional risks.
Abstract
This two-part paper argues that seemingly "technical" choices made by developers of machine-learning based algorithmic tools used to inform decisions by criminal justice authorities can create serious constitutional dangers, enhancing the likelihood of abuse of decision-making power and the scope and magnitude of injustice. Drawing on three algorithmic tools in use, or recently used, to assess the "risk" posed by individuals to inform how they should be treated by criminal justice authorities, we integrate insights from data science and public law scholarship to show how public law principles and more specific legal duties that are rooted in these principles, are routinely overlooked in algorithmic tool-building and implementation. We argue that technical developers must collaborate closely with public law experts to ensure that if algorithmic decision-support tools are to inform…
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Taxonomy
TopicsEthics and Social Impacts of AI · Artificial Intelligence in Law · Criminal Justice and Corrections Analysis
