mlsanityData to 7 Oct 2026

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

arXiv 2409.07871 ↗First posted 12 Sep 2024cs.HC cs.CYcited by 16

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Abstract (arXiv)

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.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Sep 2024.

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Citing papers per year: 2024: 1; 2025: 5; 2026: 10.

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  1. 2024Persuasion with Large Language Models: A Survey of Empirical Evidence, Study Methodologies, and Ethical Implicationscited by 30
  2. 2025LLM Agent Meets Agentic AI: Can LLM Agents Simulate Customers to Evaluate Agentic-AI-based Shopping Assistants?cited by 15
  3. 2025How large language models judge and influence human cooperationcited by 3
  4. 2026Belief Offloading in Human-AI Interactioncited by 3
  5. 2025When Autonomy Breaks: The Hidden Existential Risk of AIcited by 2
  6. 2025Large Language Models as 'Hidden Persuaders': Fake Product Reviews are Indistinguishable to Humans and Machinescited by 1
  7. 2026Gender Bias in LLMs: Preliminary Evidence from Shared Parenting Scenario in Czech Family Lawcited by 1
  8. 2026Growth First, Care Second? Tracing the Landscape of LLM Value Preferences in Everyday Dilemmascited by 1
  9. 2026When AI Takes Sides on Questions of Faith: Persistent Asymmetries in AI-Mediated Faith Guidancecited by 1
  10. 2025Humans learn to prefer trustworthy AI over human partnerscited by 0
  11. 2026"Are You Sure?": An Empirical Study of Human Perception Vulnerability in LLM-Driven Agentic Systemscited by 0
  12. 2026Understanding U.S. Users' Security and Privacy Transparency Needs for Consumer-Facing Generative AIcited by 0
4 more
  1. 2026Implicit Humanization in Everyday LLM Moral Judgmentscited by 0
  2. 2026Beyond Accuracy: How Humans Evaluate Legally Correct but Socially Controversial Legal Advice from Machinescited by 0
  3. 2026Toward Human Rights Benchmarking for LLMs: A Pilot Methodologycited by 0
  4. 2026Annie, Are You Okay? How Style- and Context-Based Personalization Shape AI-Assisted Decision-Makingcited by 0