arXiv — NLP / Computation & Language · · 3 min read

AI Can Be Easily Persuaded in Clinical Decision Making

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Computer Science > Computation and Language

arXiv:2608.29453 (cs)
[Submitted on 29 Aug 2026]

Title:AI Can Be Easily Persuaded in Clinical Decision Making

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Abstract:As AI becomes increasingly integrated into clinical practice, it is playing a growing role in medical decision making. Medicine, however, is a high stakes and evidence based field, where decisions can directly affect patients' lives. It is therefore important to understand whether AI can maintain objective judgment when others try to persuade it. In this paper, we study how easily AI can be persuaded through controlled experiments. We find that professional authority, national background, institutional affiliation, claimed past performance, multiple physicians, supported clinician views, and repeated pressure can all affect AI decisions. Surprisingly, the same persuasive input changes about 10% more cases when it comes from a senior clinician than from a medical student. Simply claiming a better performance history consistently makes the physician more persuasive. More strikingly, a plausible clinician view can persuade AI away from a correct decision even when it is fabricated to support an incorrect answer. This indicates that AI can be strongly influenced by convincing support without reliably determining whether this view from the clinician is correct. Together, these findings suggest that AI can be easily persuaded by what people say, who says it, and how the opinion is presented. Therefore, it is essential for AI to maintain sound judgment under persuasion, enabling its safe and reliable use in high stakes medical decision making.
Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as: arXiv:2608.29453 [cs.CL]
  (or arXiv:2608.29453v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2608.29453
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Jiayuan Zhu [view email]
[v1] Sat, 29 Aug 2026 22:13:04 UTC (461 KB)
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