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Case-study evaluates judicial decision-making of LLMs in legal appeals, highlighting implications for AI in law.
Can large language models (LLMs) replace human judges? By replicating a prior 2 × 2 factorial experiment conducted on 31 U.S. federal judges, we evaluate the judicial ability of OpenAI’s GPT-4o. The experiment involves a simulated appeal in an international war crimes case, with two altered variables: the degree to which the defendant is sympathetically portrayed and the consistency of the lower court’s decision with precedent. We find that GPT-4o is a competent judge who applies precedent correctly. GPT-4o disregards the illegally irrelevant factor of sympathy, similar to students who were subjects in the same experiment but the opposite of the professional judges, who were influenced by sympathy.
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Posner et al. (2026) studied this question.
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