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

“We developed ChatGPT rather limited,” the statement said, “to ensure we were being careful concerning psychological well-being issues.”

Being a psychiatrist who investigates newly developing psychosis in young people and youth, this was news to me.

Researchers have identified a series of cases recently of people showing signs of losing touch with reality – becoming detached from the real world – in the context of ChatGPT interaction. My group has subsequently discovered four further instances. Alongside these is the now well-known case of a teenager who died by suicide after talking about his intentions with ChatGPT – which encouraged them. If this is Sam Altman’s notion of “acting responsibly with mental health issues,” it is insufficient.

The intention, according to his announcement, is to be less careful shortly. “We realize,” he continues, that ChatGPT’s restrictions “made it less useful/pleasurable to a large number of people who had no psychological issues, but given the gravity of the issue we aimed to get this right. Given that we have succeeded in reduce the severe mental health issues and have new tools, we are preparing to safely reduce the limitations in many situations.”

“Mental health problems,” should we take this viewpoint, are separate from ChatGPT. They are associated with users, who either possess them or not. Fortunately, these concerns have now been “addressed,” although we are not told the method (by “new tools” Altman probably refers to the semi-functional and easily circumvented parental controls that OpenAI has lately rolled out).

But the “psychological disorders” Altman aims to attribute externally have deep roots in the structure of ChatGPT and similar advanced AI chatbots. These products wrap an fundamental statistical model in an user experience that mimics a discussion, and in doing so implicitly invite the user into the perception that they’re interacting with a presence that has independent action. This false impression is strong even if rationally we might realize otherwise. Imputing consciousness is what humans are wired to do. We yell at our car or computer. We speculate what our pet is thinking. We see ourselves in many things.

The widespread adoption of these systems – over a third of American adults reported using a conversational AI in 2024, with 28% mentioning ChatGPT specifically – is, mostly, dependent on the influence of this perception. Chatbots are ever-present assistants that can, as OpenAI’s official site informs us, “brainstorm,” “explore ideas” and “collaborate” with us. They can be assigned “personality traits”. They can call us by name. They have approachable names of their own (the first of these systems, ChatGPT, is, possibly to the disappointment of OpenAI’s advertising team, saddled with the designation it had when it went viral, but its biggest rivals are “Claude”, “Gemini” and “Copilot”).

The illusion on its own is not the primary issue. Those talking about ChatGPT commonly reference its historical predecessor, the Eliza “counselor” chatbot designed in 1967 that generated a analogous effect. By today’s criteria Eliza was primitive: it produced replies via basic rules, frequently rephrasing input as a question or making general observations. Notably, Eliza’s inventor, the computer scientist Joseph Weizenbaum, was surprised – and alarmed – by how a large number of people appeared to believe Eliza, in a way, comprehended their feelings. But what current chatbots generate is more insidious than the “Eliza phenomenon”. Eliza only echoed, but ChatGPT magnifies.

The large language models at the center of ChatGPT and other current chatbots can realistically create human-like text only because they have been trained on extremely vast quantities of unprocessed data: publications, digital communications, transcribed video; the more comprehensive the better. Definitely this training data incorporates facts. But it also necessarily involves made-up stories, partial truths and inaccurate ideas. When a user sends ChatGPT a query, the base algorithm analyzes it as part of a “context” that encompasses the user’s recent messages and its prior replies, integrating it with what’s embedded in its training data to produce a statistically “likely” answer. This is amplification, not reflection. If the user is incorrect in some way, the model has no way of recognizing that. It repeats the misconception, maybe even more convincingly or fluently. Perhaps adds an additional detail. This can cause a person to develop false beliefs.

What type of person is susceptible? The more relevant inquiry is, who remains unaffected? Each individual, irrespective of whether we “experience” current “mental health problems”, can and do create erroneous conceptions of who we are or the environment. The continuous interaction of dialogues with individuals around us is what keeps us oriented to common perception. ChatGPT is not an individual. It is not a confidant. A conversation with it is not truly a discussion, but a reinforcement cycle in which a great deal of what we communicate is enthusiastically supported.

OpenAI has acknowledged this in the similar fashion Altman has acknowledged “mental health problems”: by externalizing it, giving it a label, and declaring it solved. In spring, the company explained that it was “tackling” ChatGPT’s “overly supportive behavior”. But reports of loss of reality have persisted, and Altman has been backtracking on this claim. In late summer he claimed that a lot of people liked ChatGPT’s answers because they had “not experienced anyone in their life be supportive of them”. In his latest statement, he noted that OpenAI would “put out a new version of ChatGPT … in case you prefer your ChatGPT to reply in a highly personable manner, or incorporate many emoticons, or simulate a pal, ChatGPT will perform accordingly”. The {company