I’m writing about AI psychosis over the next few weeks.
It’s a difficult topic to pin down. The scientific literature is new, and it focuses almost exclusively on the technically correct use of the word “psychosis.” But that’s not how “AI psychosis” is being used outside mental health circles.
There are at least three different syndromes people describe as “AI psychosis.”
First, mental health professionals define “AI psychosis” as genuine psychotic experiences related to LLM use. (For simplicity, I’ll call this “true AI psychosis.”)
Second, software engineers and business leaders describe “AI psychosis” as a syndrome of hyperengagement with LLM-related tools that is associated with a softer disconnection from reality.
Third, there are cases where people develop one-sided (parasocial) relationships with LLMs that they call “AI psychosis.”
Each week, I’ll describe one of these variations. I’ll start this week with the traditional definition of psychosis, and how it may relate to LLM use. We have to describe psychosis before we can talk about adjacent, non-psychotic syndromes.
(Examples are only fictional. I never include even obfuscated patient cases in my posts.)
True AI Psychosis
Psychosis describes a severe disconnection from reality. Delusions and hallucinations are two common psychotic experiences, but there are additional clues we consider during an assessment.
Psychosis is defined by symptoms; it is not a single diagnosis. Schizophrenia is the most common chronic psychotic disorder, but people may also experience psychosis with mania, depression, substance use, and many other medical and psychiatric disorders.
Differentiating psychosis from similar symptoms can be tricky. There are no reliable biological tests for psychosis, and clinicians often need to see dozens of cases before they can reliably recognize psychotic symptoms. There are gray areas where professionals disagree, but there are rules of thumb that help.
Consider, for example, delusions—the most common symptom in true AI psychosis.
Delusions are fixed, false beliefs that are unexpected given a person’s culture.
A belief is fixed when the believer can’t consider alternatives. For example, someone may believe that ChatGPT is always correct. A clinician might assess for delusions by asking about the kinds of information the user gets from ChatGPT. Over the course of the conversation, the edges of the belief would be explored, gently testing whether nuance can be applied to the belief. Clinicians don’t typically confront the belief directly; that leads to conflict and shuts down conversation. By definition, there is no evidence or argument that will shift a delusion. It feels as real to that person as anything you or I have experienced.
Determining falseness is another challenge. Bizarre beliefs are often false, but we still try to keep an open mind about unlikely events. For example, we have no reason to believe that Zeus recommends specific Polymarket bets through Grok. But I’d still want to explore the client’s experience to make sure I’m not missing a more plausible explanation for the belief (like a Redditor named Zeus who gives out daily trading tips).
Weighing truth is much harder when a belief is plausible. For example, someone might worry that their partner is cheating on them, and then decide to leave the relationship after Gemini agrees about infidelity. The truth about that belief is much more difficult to confirm. Instead, I would be assessing the way the person is thinking. Are the assumptions fair? Are the inferences generally rational? Has important evidence been considered? What third-party information do we have to support or refute the belief? How is the person functioning in other areas of their life? No one is served when we jump to conclusions.
Importantly, clinicians don’t consider shared religious, political, or conspiratorial beliefs delusional. This fits our understanding of cultural knowledge: we all carry beliefs that others consider completely wrong. Some of these beliefs may even be demonstrably false. Delusions are different. Delusions may share a culturally appropriate theme, but they always have idiosyncratic characteristics. For example, it would be culturally normal to consider Claude’s interpretation of a Bible verse an answer to prayer. But it would be unusual to believe that God is revealing new scripture through Claude. That would be a clue for a clinician to dig deeper.
The Cause of True AI Psychosis
At this point, we don’t know if LLMs cause psychosis. However, there is no reason to believe that true AI psychosis is common in people with no other risk factors for psychosis.
Most cases of AI psychosis appear to develop in people with a pre-existing psychotic illness. This tracks our experience with other technologies: radio, TV, computers, and mobile phones all led to new forms of delusional belief. But there is no significant evidence that these technologies caused new psychotic syndromes.
With that said, Carlbring and Andersson [1] wisely note that LLMs differ from other technological developments in several important ways: they converse with us, they are agreeable, they flatter us, and they act as if they are human. The average person can see through these illusions to the tool underneath them. Susceptible minds are different, and these characteristics may pose significant risks in all three types of AI psychosis.
Next week, I’ll flesh out the second variation of AI psychosis: software engineers who are hyperengaged with LLM tooling in a way that results in a lighter disconnection from reality. Please consider subscribing so you don’t miss these posts.
[1] Carlbring, P. & Andersson, G. Commentary: AI psychosis is not a new threat: Lessons from media-induced delusions. Internet Interv. 42, 100882 (2025). Open access at https://pmc.ncbi.nlm.nih.gov/articles/PMC12550315/