יום שלישי, 15 בספטמבר 2026 LIVE
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כתבה arXiv cs.AI ·

Human-like moral judgments conceal divergent motive attributions in large language models

תקציר מקורי באנגליתarXiv:2609.07353v1 Announce Type: new Abstract: Large language models (LLMs) are used to simulate human participants in psychological research. We asked whether LLMs that reproduce human evaluations of a whistleblower's moral character also reproduce the motive attributions that accompany them. Five LLMs and two human samples (N = 125 and N = 742) evaluated a physician who either remained silent about fraudulent billing or reported it to a hospital, regulator, or newspaper. Models reproduced the human ranking of the physician's moral character but portrayed whistleblowers as more helpful, less self-interested, and less hostile. In four of five models, competitive motives were less strongly associated with moral-character judgments. Model ratings changed little when prompts reproduced the n
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