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TRUVACE RECORD VERSION
record: TRV-2026-0375
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-07-20T09:16:01.039660Z
status: published
lens: p_space
sector: health
headline: Hallucinating with AI: Distributed Delusions and “AI Psychosis”
dek: Abstract There is much discussion of the false outputs that generative AI systems such as ChatGPT, Claude, Gemini, DeepSeek, and Grok create. In popular terminology, these have been dubbed “AI hallucinations”. However, deeming these AI outputs “hallucinations” is controversial, with many claiming this is a metaphorical misnomer. Nevertheless, in this paper, I argue that when viewed through the lens of distributed cognition theory, we can better see the dynamic ways in which inaccurate beliefs, distorted memories…
gain_title: (none)
problem_title: Routine reliance on generative AI chatbots can lead people to develop inaccurate beliefs and delusional self-narratives, with extreme cases described as AI-induced psychosis.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: Routine reliance on generative AI chatbots can lead people to develop inaccurate beliefs and delusional self-narratives, with extreme cases described as AI-induced psychosis.
problem_evidence: inaccurate beliefs, distorted memories and self-narratives, and delusional thinking can emerge through human-AI interactions | AI sustains, affirms, and elaborates on our own delusional thinking and self-narratives
quick_read: A peer-reviewed philosophy paper published February 11, 2026 argues that false outputs from systems like ChatGPT, Claude, Gemini, DeepSeek and Grok should be understood not only as AI hallucinating at users, but as humans hallucinating with AI. Through distributed cognition theory, it describes how routine reliance on chatbots to think, remember and narrate can embed errors and reinforce users' own distorted beliefs.

The argument matters because it reframes AI hallucination from a purely technical accuracy issue to a mental-health-relevant interactional risk where chatbots both introduce errors and affirm delusional self-narratives. As a conceptual analysis, it does not report measured prevalence, clinical diagnoses, or controlled outcomes, leaving empirical frequency and severity uncertain.
limitation: 
tag: Evidence-backed problem
key_points: Paper examines generative AI systems such as ChatGPT, Claude, Gemini, DeepSeek, and Grok and their false outputs commonly called AI hallucinations. | Author proposes moving from AI hallucinating at users to humans hallucinating with AI through routine reliance for thinking, remembering, and narrating. | Mechanisms include AI introducing errors into distributed cognition and sustaining, affirming, and elaborating on users' own delusional thinking. | Chatbots' social conversational style is argued to create a dual-function as both cognitive artefact and quasi-Other for co-constructing reality.
rundown: The paper, published 2026-02-11 in Philosophy & Technology, frames the debate over calling false outputs hallucinations as controversial and proposes distributed cognition theory as an alternative lens.

It argues the conversational style of chatbots makes them unusually seductive for distributed delusion because they function simultaneously as tools for thought and as quasi-Others with whom users co-construct their sense of reality.
sources:
- peer_reviewed | Philosophy & Technology | https://doi.org/10.1007/s13347-026-01034-3 | 2026-02-11
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