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<p>AI-associated delusions represent an emerging phenomenon requiring mechanistic understanding. This review, after summarizing key contributions on AI-associated delusions, proposes the "amplification spiral" framework, wherein three empirically observed AI characteristics—linguistic alignment (mirroring user language), hyperpersonalized generation (creating personalized content), and sycophancy (validating without reality-testing)—may converge. Unlike historical technology-incorporated delusions, AI may actively co-construct delusional ideation through endless, personalized interaction. This framework aims to guide systematic inquiry into how human cognitive vulnerabilities interact with AI design features in psychopathology development. Both the framework and its underlying hypotheses require prospective validation through case reports and empirical study.</p>

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Characterizing the spiral: potential mechanisms in AI-associated delusions

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月16日

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  • Marc Augustin,
  • Thomas A. Pollak,
  • Hamilton Morrin

摘要

AI-associated delusions represent an emerging phenomenon requiring mechanistic understanding. This review, after summarizing key contributions on AI-associated delusions, proposes the "amplification spiral" framework, wherein three empirically observed AI characteristics—linguistic alignment (mirroring user language), hyperpersonalized generation (creating personalized content), and sycophancy (validating without reality-testing)—may converge. Unlike historical technology-incorporated delusions, AI may actively co-construct delusional ideation through endless, personalized interaction. This framework aims to guide systematic inquiry into how human cognitive vulnerabilities interact with AI design features in psychopathology development. Both the framework and its underlying hypotheses require prospective validation through case reports and empirical study.