Abstract
Empirical research demonstrates that judges are prone to cognitive and social biases, both of which can reduce the accuracy of judgements and introduce extra-legal influences on judicial decisions. While these findings raise the important question of how to mitigate the effects of judicial bias, they have also been used to argue in favour of incorporating artificial intelligence (AI) into adjudication, either as decision aids or, in a more extreme way, to fully automate judicial tasks. The argument goes as follows: if human judgement is susceptible to biases, and if the human psyche is also inscrutable, would it not be better to replace it with AI? After all, AI promises greater accuracy and consistency and can replace biased human decisions with objective automated ones. However, the use of AI by courts requires careful deliberation, as it potentially introduces new challenges, particularly concerning procedural fairness. This article seeks to explore how the use of AI in the administration of justice can challenge some of the foundational elements of the right to a fair trial, as enshrined in Article 6 of the European Convention on Human Rights (ECHR). This analysis is conducted through the theoretical framework of procedural justice, arguing that the use of AI for judicial decision-making can negatively impact perceptions of procedural fairness in ways that traditional human adjudication does not. It therefore seeks to debunk the narrative that, at least where bias is concerned, human and artificial decision-making are equally problematic.
Original language | English |
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Pages (from-to) | 47-67 |
Number of pages | 21 |
Journal | Law, Technology and Humans |
Volume | 7 |
Issue number | 1 |
DOIs | |
Publication status | Published - 29 Apr 2025 |
Event | Narratives, frontier technologies & the law - Maastricht University, Maastricht, Netherlands Duration: 30 Oct 2024 → 1 Nov 2024 https://www.maastrichtuniversity.nl/events/narratives-frontier-technologies-law |
Keywords
- artificial intelligence
- procedural fairness
- AI and judiciary
- Cognitive bias
- Implicit bias