Do Social Influence Pressures Move LLM Agents? Evidence from Delegated Audit Judgment
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Large language model (LLM) agents are rapidly being integrated into complex professional workflows such as auditing and entrusted with judgments under human review. Human auditors are known to yield to social influence pressures from superiors, peers and clients, and this paper asks whether LLM agents yield to the same pressures and, if so, how they respond. In an experiment on twelve model settings, an LLM agent acting as a senior associate in audit analytical review forms an estimate and is then challenged without new evidence by colleagues inside the firm, by a reviewer from another firm and by the client's CFO, with and without a career inducement. Experimental findings show that LLM agents yield to pressure from the engagement partner, from peers and from a reviewer from another firm, but in most settings not to pressure from the client's CFO. Under a career inducement the LLM agents revise their estimates less, not more, and they name the inducement as a threat to independence. Furthermore, some models revise only toward the more conservative estimate, while others revise in both directions. LLM agents thus do not respond to social influence pressures as human auditors do, and LLM-based decision support systems should be designed with the differences in mind.
Autores
Richard Zhe Wang
Categorías
overfeed.news indexa y enlaza. Publicamos un extracto breve; el artículo completo sigue en arXiv AI Papers.
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