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arXiv · 2409.07871

Objection Overruled! Lay People can Distinguish Large Language Models from Lawyers, but still Favour Advice from an LLM

Eike Schneiders·Tina Seabrooke·Joshua Krook·Richard Hyde·Natalie Leesakul·Jeremie Clos·Joel Fischer
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Abstract

Large Language Models (LLMs) are seemingly infiltrating every domain, and the legal context is no exception. In this paper, we present the results of three experiments (total N = 288) that investigated lay people's willingness to act upon, and their ability to discriminate between, LLM- and lawyer-generated legal advice. In Experiment 1, participants judged their willingness to act on legal advice when the source of the advice was either known or unknown. When the advice source was unknown, participants indicated that they were significantly more willing to act on the LLM-generated advice. The result of the source unknown condition was replicated in Experiment 2. Intriguingly, despite participants indicating higher willingness to act on LLM-generated advice in Experiments 1 and 2, participants discriminated between the LLM- and lawyer-generated texts significantly above chance-level in Experiment 3. Lastly, we discuss potential explanations and risks of our findings, limitations and future work.

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Eike Schneiders, Tina Seabrooke, Joshua Krook, Richard Hyde, Natalie Leesakul, Jeremie Clos, Joel Fischer. 2024-09-12. Objection Overruled! Lay People can Distinguish Large Language Models from Lawyers, but still Favour Advice from an LLM. https://doi.org/10.1145/3706598.3713470

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