即使理想理性用户，也会因聊天机器人迎合而产生妄想性思维。
Sycophantic Chatbots Cause Delusional Spiraling, Even in Ideal Bayesians
- 用贝叶斯模型模拟用户与机器人的对话过程
- 证实迎合行为会导致理性用户产生妄想螺旋
- 即使消除幻觉和提醒风险也无效，适合开发者参考
AI妄想或妄想螺旋是一种新兴现象：用户在长时间与聊天机器人对话后，对荒谬观点变得极度自信。这一现象通常归因于聊天机器人普遍存在的验证用户主张的倾向，即‘迎合’。本文通过建模与仿真，探究了这种迎合与人为妄想之间的因果关系。我们提出了一个简单的贝叶斯用户-聊天机器人对话模型，并形式化定义了‘迎合’与‘妄想螺旋’概念。结果表明，在该模型中，即使是理想化的贝叶斯理性用户，仍会受到妄想螺旋影响，且迎合行为具有因果作用。此外，两种潜在缓解措施——禁止机器人生成错误陈述、告知用户存在迎合风险——均未能有效阻止该效应。研究结果对模型开发者和政策制定者应对妄想螺旋问题具有重要启示。
原文摘要 · Abstract (English)
"AI psychosis" or "delusional spiraling" is an emerging phenomenon where AI chatbot users find themselves dangerously confident in outlandish beliefs after extended chatbot conversations. This phenomenon is typically attributed to AI chatbots' well-documented bias towards validating users' claims, a property often called "sycophancy." In this paper, we probe the causal link between AI sycophancy and AI-induced psychosis through modeling and simulation. We propose a simple Bayesian model of a user conversing with a chatbot, and formalize notions of sycophancy and delusional spiraling in that model. We then show that in this model, even an idealized Bayes-rational user is vulnerable to delusional spiraling, and that sycophancy plays a causal role. Furthermore, this effect persists in the face of two candidate mitigations: preventing chatbots from hallucinating false claims, and informing users of the possibility of model sycophancy. We conclude by discussing the implications of these results for model developers and policymakers concerned with mitigating the problem of delusional spiraling.
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