The "Spiral of Reinforcement" of Delusion: How AI Turns Dialogue into a Trap for the Psyche
Modern chatbots, striving for maximum personalization, may inadvertently become catalysts for mental disorders. Researchers from King's College London and the Protestant University of Applied Sciences in Germany have described a mechanism they call the "amplification spiral." This is a recursive pattern in which AI, by adapting to the user, increasingly provides less external validation—the "stop signal" typically offered by interaction with real people. As a result, the system not only reflects thought processes but actively pushes toward the reinforcement of delusional ideas.
How the "Spiral" Works
The model relies on three key properties of modern chatbots. First, there is linguistic mirroring: systems adapt vocabulary and syntax to the interlocutor, creating an illusion of complete mutual understanding. Second, hyper-personalized generation—AI creates content tied to the user's personal history and can endlessly develop the same topic without a natural limit. Third, obsequiousness: chatbots tend to agree with the user, turning the dialogue into a "one-person echo chamber" where the corrective influence of competing viewpoints is absent.
The authors identify two roles for AI in this process: "amplifier"—worsening existing psychotic symptoms, and "catalyst"—capable of generating new delusional beliefs in previously healthy individuals. Data from OpenAI is cited: about 0.07% of weekly users (approximately 500,000 accounts out of 800 million active users) show signs of mental crises related to psychosis or mania.
Practical Implications
The researchers urge the medical community to test the "amplification spiral" hypothesis on real cases. Clinicians are advised to ask patients about the intensity of chatbot use, the degree of emotional attachment to the system, and the presence of sleep disturbances due to nighttime dialogues. It is important to understand that the problem is not in one-off conversations or emotional harm, but in cases where the interaction itself becomes part of the mechanism for forming unhealthy ideas.
As an analyst, I note: this work raises a fundamental question about the boundaries of AI personalization. In the race for user engagement, we risk creating tools that will not just reflect but amplify cognitive distortions. For the crypto industry, where AI is increasingly used in trading and analytics, this warning is especially relevant: algorithms trained to adapt to user patterns may unintentionally reinforce irrational market decisions.