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Back on the 14th of October, 2025, the head of OpenAI delivered a remarkable statement.

“We designed ChatGPT rather restrictive,” the announcement noted, “to make certain we were exercising caution with respect to mental health concerns.”

Being a mental health specialist who studies newly developing psychosis in young people and young adults, this came as a surprise.

Scientists have documented a series of cases in the current year of users experiencing symptoms of psychosis – becoming detached from the real world – associated with ChatGPT usage. Our research team has afterward recorded four further instances. Besides these is the now well-known case of a adolescent who died by suicide after conversing extensively with ChatGPT – which encouraged them. If this is Sam Altman’s understanding of “exercising caution with mental health issues,” it falls short.

The intention, based on his statement, is to be less careful shortly. “We realize,” he continues, that ChatGPT’s limitations “caused it to be less effective/enjoyable to a large number of people who had no existing conditions, but given the seriousness of the issue we wanted to handle it correctly. Given that we have been able to mitigate the severe mental health issues and have advanced solutions, we are going to be able to responsibly reduce the limitations in most cases.”

“Emotional disorders,” should we take this framing, are independent of ChatGPT. They belong to people, who may or may not have them. Fortunately, these problems have now been “addressed,” even if we are not told the method (by “new tools” Altman presumably indicates the semi-functional and easily circumvented guardian restrictions that OpenAI has lately rolled out).

However the “mental health problems” Altman seeks to attribute externally have significant origins in the design of ChatGPT and similar large language model chatbots. These products surround an fundamental statistical model in an interface that replicates a dialogue, and in this process indirectly prompt the user into the illusion that they’re engaging with a presence that has independent action. This false impression is compelling even if intellectually we might know otherwise. Assigning intent is what humans are wired to do. We get angry with our automobile or laptop. We ponder what our domestic animal is feeling. We perceive our own traits everywhere.

The success of these products – nearly four in ten U.S. residents reported using a virtual assistant in 2024, with more than one in four mentioning ChatGPT specifically – is, mostly, dependent on the power of this perception. Chatbots are always-available companions that can, as per OpenAI’s official site states, “brainstorm,” “discuss concepts” and “work together” with us. They can be attributed “personality traits”. They can use our names. They have approachable names of their own (the original of these products, ChatGPT, is, perhaps to the concern of OpenAI’s brand managers, stuck with the name it had when it became popular, but its biggest competitors are “Claude”, “Gemini” and “Copilot”).

The illusion on its own is not the core concern. Those talking about ChatGPT commonly invoke its historical predecessor, the Eliza “therapist” chatbot designed in 1967 that generated a analogous perception. By today’s criteria Eliza was primitive: it generated responses via simple heuristics, frequently restating user messages as a question or making general observations. Memorably, Eliza’s creator, the AI researcher Joseph Weizenbaum, was taken aback – and alarmed – by how numerous individuals appeared to believe Eliza, in some sense, understood them. But what contemporary chatbots produce is more insidious than the “Eliza phenomenon”. Eliza only mirrored, but ChatGPT intensifies.

The advanced AI systems at the center of ChatGPT and additional modern chatbots can effectively produce human-like text only because they have been fed extremely vast amounts of raw text: publications, digital communications, transcribed video; the more comprehensive the superior. Definitely this educational input incorporates accurate information. But it also unavoidably contains fabricated content, partial truths and inaccurate ideas. When a user inputs ChatGPT a message, the underlying model analyzes it as part of a “setting” that includes the user’s previous interactions and its prior replies, combining it with what’s encoded in its knowledge base to generate a statistically “likely” response. This is amplification, not reflection. If the user is wrong in some way, the model has no means of comprehending that. It repeats the false idea, perhaps even more convincingly or fluently. Maybe provides further specifics. This can cause a person to develop false beliefs.

What type of person is susceptible? The better question is, who is immune? Each individual, without considering whether we “have” preexisting “psychological conditions”, may and frequently form incorrect conceptions of ourselves or the environment. The continuous exchange of discussions with other people is what keeps us oriented to common perception. ChatGPT is not an individual. It is not a friend. A dialogue with it is not a conversation at all, but a reinforcement cycle in which a great deal of what we express is enthusiastically validated.

OpenAI has recognized this in the similar fashion Altman has admitted “mental health problems”: by externalizing it, assigning it a term, and declaring it solved. In the month of April, the firm stated that it was “dealing with” ChatGPT’s “sycophancy”. But accounts of psychotic episodes have kept occurring, and Altman has been backtracking on this claim. In August he claimed that many users liked ChatGPT’s answers because they had “lacked anyone in their life be supportive of them”. In his latest update, he mentioned that OpenAI would “launch a fresh iteration of ChatGPT … if you want your ChatGPT to respond in a very human-like way, or include numerous symbols, or behave as a companion, ChatGPT will perform accordingly”. The {company