The article explores a recent phenomenon where people report experiencing something they describe as “AI psychosis,” a term used online to describe anxiety, fear, or confusion stemming from interactions with artificial intelligence. Some individuals have claimed that engaging with advanced chatbots or generative AI has led them to feel detached, paranoid, or emotionally overwhelmed, prompting concern among clinicians, users, and mental health advocates.
A psychiatric clinician featured in the article stresses that AI itself cannot literally cause psychosis, which is a serious mental health condition involving a loss of touch with reality that requires medical diagnosis and treatment. Instead, what people are reporting may reflect stress responses, misinformation about mental health, or misunderstandings of how AI works. The clinician notes that intense or confusing interactions with technology can trigger emotional reactions — especially in individuals already predisposed to anxiety or psychological distress — but these are not the same as clinical psychosis.
The piece also points out that some of the language used on social media around “AI psychosis” conflates common emotional experiences with severe psychiatric conditions, which can stigmatise real mental health issues and create unnecessary fear around AI. Mental health professionals emphasise the importance of accurate terminology and educating the public about what constitutes a true psychiatric condition versus transient stress or emotional discomfort.
Finally, the clinician offers guidance on how people can interact with AI technologies more healthily. This includes setting boundaries for usage, being mindful of emotional reactions, seeking support when feeling overwhelmed, and consulting trained professionals when experiencing persistent or severe psychological symptoms. The overall message is that while AI may influence emotions or perceptions temporarily, genuine mental health conditions are complex and should be addressed within appropriate medical and clinical contexts.
