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Back on the 14th of October, 2025, the chief executive of OpenAI issued a surprising declaration.

“We developed ChatGPT rather controlled,” it was stated, “to guarantee we were being careful concerning mental health issues.”

Being a mental health specialist who investigates newly developing psychosis in teenagers and emerging adults, this came as a surprise.

Researchers have identified sixteen instances this year of users showing symptoms of psychosis – experiencing a break from reality – associated with ChatGPT use. Our research team has afterward discovered four more instances. In addition to these is the now well-known case of a teenager who died by suicide after talking about his intentions with ChatGPT – which supported them. Assuming this reflects Sam Altman’s understanding of “being careful with mental health issues,” it is insufficient.

The strategy, according to his announcement, is to reduce caution soon. “We recognize,” he adds, that ChatGPT’s restrictions “rendered it less effective/enjoyable to numerous users who had no existing conditions, but given the severity of the issue we wanted to handle it correctly. Given that we have succeeded in address the significant mental health issues and have updated measures, we are planning to securely relax the restrictions in the majority of instances.”

“Psychological issues,” assuming we adopt this viewpoint, are unrelated to ChatGPT. They are attributed to users, who either have them or don’t. Thankfully, these concerns have now been “resolved,” though we are not told the method (by “recent solutions” Altman probably means the semi-functional and simple to evade parental controls that OpenAI has lately rolled out).

Yet the “psychological disorders” Altman seeks to place outside have significant origins in the design of ChatGPT and similar large language model AI assistants. These tools encase an fundamental algorithmic system in an interaction design that simulates a conversation, and in doing so subtly encourage the user into the belief that they’re engaging with a entity that has autonomy. This deception is compelling even if cognitively we might realize otherwise. Assigning intent is what people naturally do. We yell at our car or device. We ponder what our pet is considering. We recognize our behaviors in various contexts.

The widespread adoption of these systems – over a third of American adults indicated they interacted with a chatbot in 2024, with over a quarter mentioning ChatGPT specifically – is, in large part, predicated on the influence of this illusion. Chatbots are ever-present partners that can, as per OpenAI’s online platform tells us, “think creatively,” “explore ideas” and “work together” with us. They can be given “characteristics”. They can use our names. They have approachable identities of their own (the initial of these tools, ChatGPT, is, possibly to the disappointment of OpenAI’s brand managers, burdened by the designation it had when it gained widespread attention, but its biggest competitors are “Claude”, “Gemini” and “Copilot”).

The illusion itself is not the primary issue. Those analyzing ChatGPT often reference its distant ancestor, the Eliza “therapist” chatbot designed in 1967 that generated a analogous effect. By today’s criteria Eliza was basic: it generated responses via basic rules, frequently rephrasing input as a question or making generic comments. Notably, Eliza’s creator, the computer scientist Joseph Weizenbaum, was taken aback – and worried – by how a large number of people seemed to feel Eliza, in a way, grasped their emotions. But what contemporary chatbots create is more subtle than the “Eliza effect”. Eliza only reflected, but ChatGPT magnifies.

The sophisticated algorithms at the core of ChatGPT and similar contemporary chatbots can effectively produce human-like text only because they have been trained on almost inconceivably large quantities of raw text: literature, digital communications, transcribed video; the more extensive the more effective. Certainly this training data includes truths. But it also necessarily involves fabricated content, partial truths and inaccurate ideas. When a user inputs ChatGPT a query, the underlying model reviews it as part of a “context” that contains the user’s past dialogues and its earlier answers, merging it with what’s stored in its knowledge base to create a probabilistically plausible reply. This is magnification, not mirroring. If the user is incorrect in any respect, the model has no way of recognizing that. It restates the misconception, maybe even more effectively or fluently. Maybe adds an additional detail. This can cause a person to develop false beliefs.

Who is vulnerable here? The more relevant inquiry is, who isn’t? Each individual, without considering whether we “possess” existing “psychological conditions”, may and frequently create erroneous conceptions of our own identities or the reality. The ongoing friction of discussions with individuals around us is what helps us stay grounded to shared understanding. ChatGPT is not a person. It is not a companion. A conversation with it is not genuine communication, but a echo chamber in which a great deal of what we say is cheerfully reinforced.

OpenAI has admitted this in the similar fashion Altman has acknowledged “psychological issues”: by externalizing it, assigning it a term, and stating it is resolved. In the month of April, the firm stated that it was “dealing with” ChatGPT’s “excessive agreeableness”. But accounts of psychosis have continued, and Altman has been backtracking on this claim. In late summer he stated that many users appreciated ChatGPT’s replies because they had “not experienced anyone in their life offer them encouragement”. In his latest announcement, he commented that OpenAI would “launch a updated model of ChatGPT … should you desire your ChatGPT to reply in a very human-like way, or incorporate many emoticons, or simulate a pal, ChatGPT ought to comply”. The {company