Generative AI and Courts in the UK : a Candle in a Hurricane
Harkens, Adam and Morison, John; Zalnieriute, Monika and Limante, Agne, eds. (2025) Generative AI and Courts in the UK : a Candle in a Hurricane. In: Cambridge Handbook on Courts and AI. Cambridge University Press (CUP), Cambridge. (In Press)
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Abstract
In December 2023, the United Kingdom’s first set of guidelines relating to the judicial use of artificial intelligence (AI) was published by the Courts and Tribunals Judiciary. In the absence of a targeted legal framework pertaining to the use of AI by courts or public authorities in the UK, these guidelines are the primary source of regulatory guidance upon which judges can draw from to understand how AI ought to be appropriately used in their professional context. This contribution sets out to provide critical reflection upon the content and effectiveness of these guidelines, ultimately concluding that more extensive – and legally binding – regulatory action is needed to accurate and accountable judicial decision-making in the era of AI. In making this argument, this chapter first surveys general attitudes towards AI within the UK judiciary, before moving to engage directly with the technical foundations of AI and examples of its usage in administrative and judicial decision-making in the UK. It concludes with an analysis of the aforementioned guidelines, following discussion of a number of key legal and constitutional issues that may arise where AI is deployed in judicial settings. Throughout this contribution, we caution that the regular use of AI to make decisions does not simply change the process of discrete procedures, but rather, will challenge existing structures within the legal and political system at a broader level.
ORCID iDs
Harkens, Adam
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Item type: Book Section ID code: 92676 Dates: DateEvent23 April 2025Published23 April 2025AcceptedSubjects: Law Department: Faculty of Humanities and Social Sciences (HaSS) > Strathclyde Law School > Law Depositing user: Pure Administrator Date deposited: 25 Apr 2025 00:23 Last modified: 25 Apr 2025 00:23 URI: https://strathprints.strath.ac.uk/id/eprint/92676