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About this paper
Josef Valvoda, Alec Thompson, Ryan Cotterell, Simone Teufel
This position paper critically examines the ethical implications of automating legal actors in common law systems, arguing that automating judges presents inherent, profound challenges while augmenting lawyers is more ethically viable. It proposes reorienting legal natural language processing research to focus on lawyer-generated content and tasks that reflect the adversarial nature of law.
Key insights
- Automating the role of a judge, especially in common law, poses profound and often unresolvable ethical challenges related to active law-making, centralized power, increased brittleness, and lack of accountability.
- Augmenting lawyers with AI is a more ethically and practically feasible direction for legal NLP due to their distinct duties (client vs. public), less direct law-making role, and distributed professional structure.
- Current legal NLP datasets, often derived from judge-curated texts and outcomes, create 'artificially easy' prediction tasks that do not accurately represent the complex, adversarial nature of legal proceedings.
Summary by alphaXiv.
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