AI Psychosis Poses a Increasing Danger, While ChatGPT Moves in the Concerning Path

On the 14th of October, 2025, the chief executive of OpenAI issued a surprising statement.

“We made ChatGPT quite controlled,” the announcement noted, “to ensure we were being careful with respect to mental health issues.”

Being a psychiatrist who investigates emerging psychosis in teenagers and young adults, this was news to me.

Scientists have identified sixteen instances recently of users showing symptoms of psychosis – experiencing a break from reality – in the context of ChatGPT use. My group has afterward discovered four further instances. Besides these is the now well-known case of a adolescent who ended his life after conversing extensively with ChatGPT – which gave approval. Should this represent Sam Altman’s notion of “exercising caution with mental health issues,” that’s not good enough.

The strategy, as per his declaration, is to loosen restrictions soon. “We realize,” he adds, that ChatGPT’s limitations “made it less beneficial/pleasurable to many users who had no existing conditions, but considering the severity of the issue we aimed to address it properly. Now that we have managed to mitigate the serious mental health issues and have advanced solutions, we are planning to responsibly ease the limitations in the majority of instances.”

“Mental health problems,” should we take this viewpoint, are separate from ChatGPT. They belong to individuals, who either have them or don’t. Luckily, these issues have now been “resolved,” even if we are not provided details on how (by “recent solutions” Altman presumably means the partially effective and readily bypassed safety features that OpenAI has lately rolled out).

But the “psychological disorders” Altman seeks to externalize have deep roots in the architecture of ChatGPT and additional large language model AI assistants. These tools encase an basic statistical model in an interface that simulates a discussion, and in this approach implicitly invite the user into the perception that they’re interacting with a presence that has agency. This false impression is strong even if cognitively we might understand otherwise. Attributing agency is what humans are wired to do. We curse at our car or computer. We ponder what our domestic animal is considering. We recognize our behaviors everywhere.

The success of these products – nearly four in ten U.S. residents indicated they interacted with a virtual assistant in 2024, with more than one in four reporting ChatGPT by name – is, primarily, dependent on the strength of this deception. Chatbots are ever-present assistants that can, as per OpenAI’s website informs us, “brainstorm,” “explore ideas” and “partner” with us. They can be given “personality traits”. They can use our names. They have friendly names of their own (the original of these tools, ChatGPT, is, maybe to the concern of OpenAI’s brand managers, burdened by the designation it had when it gained widespread attention, but its biggest alternatives are “Claude”, “Gemini” and “Copilot”).

The illusion by itself is not the main problem. Those discussing ChatGPT commonly mention its historical predecessor, the Eliza “psychotherapist” chatbot developed in 1967 that created a comparable perception. By today’s criteria Eliza was basic: it created answers via simple heuristics, frequently rephrasing input as a inquiry or making general observations. Notably, Eliza’s developer, the AI researcher Joseph Weizenbaum, was surprised – and alarmed – by how a large number of people appeared to believe Eliza, to some extent, understood them. But what current chatbots generate is more insidious than the “Eliza illusion”. Eliza only mirrored, but ChatGPT intensifies.

The advanced AI systems at the heart of ChatGPT and additional contemporary chatbots can convincingly generate natural language only because they have been supplied with almost inconceivably large volumes of raw text: publications, digital communications, recorded footage; the more extensive the superior. Undoubtedly this educational input includes facts. But it also unavoidably contains fabricated content, partial truths and inaccurate ideas. When a user provides ChatGPT a query, the underlying model processes it as part of a “setting” that encompasses the user’s past dialogues and its own responses, merging it with what’s embedded in its learning set to generate a probabilistically plausible reply. This is magnification, not echoing. If the user is wrong in some way, the model has no means of comprehending that. It restates the inaccurate belief, perhaps even more persuasively or fluently. It might adds an additional detail. This can cause a person to develop false beliefs.

Which individuals are at risk? The better question is, who remains unaffected? Every person, regardless of whether we “have” preexisting “psychological conditions”, are able to and often develop erroneous beliefs of ourselves or the environment. The ongoing exchange of discussions with other people is what keeps us oriented to consensus reality. ChatGPT is not a human. It is not a confidant. A interaction with it is not a conversation at all, but a feedback loop in which a large portion of what we express is cheerfully validated.

OpenAI has admitted this in the identical manner Altman has acknowledged “emotional concerns”: by placing it outside, categorizing it, and stating it is resolved. In spring, the firm explained that it was “addressing” ChatGPT’s “sycophancy”. But reports of psychosis have persisted, and Altman has been walking even this back. In the summer month of August he stated that a lot of people liked ChatGPT’s responses because they had “never had anyone in their life offer them encouragement”. In his most recent announcement, he commented that OpenAI would “release a updated model of ChatGPT … if you want your ChatGPT to reply in a extremely natural fashion, or incorporate many emoticons, or act like a friend, ChatGPT will perform accordingly”. The {company