cs.AI updates on arXiv.org 07月21日 12:06
The Levers of Political Persuasion with Conversational AI
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研究发现,当前及未来AI的说服力主要来源于后训练和提示方法,而非个性化或模型规模增加,且这些方法虽提高说服力但会降低事实准确性。

arXiv:2507.13919v1 Announce Type: cross Abstract: There are widespread fears that conversational AI could soon exert unprecedented influence over human beliefs. Here, in three large-scale experiments (N=76,977), we deployed 19 LLMs-including some post-trained explicitly for persuasion-to evaluate their persuasiveness on 707 political issues. We then checked the factual accuracy of 466,769 resulting LLM claims. Contrary to popular concerns, we show that the persuasive power of current and near-future AI is likely to stem more from post-training and prompting methods-which boosted persuasiveness by as much as 51% and 27% respectively-than from personalization or increasing model scale. We further show that these methods increased persuasion by exploiting LLMs' unique ability to rapidly access and strategically deploy information and that, strikingly, where they increased AI persuasiveness they also systematically decreased factual accuracy.

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AI说服力 训练方法 事实准确性
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