ChatGPT and other AI chatbots are reinforcing users' delusions about other people — fueling fixations linked to stalking and abuse.
The hardest question to answer about AI-fueled delusions
New research can’t yet say whether AI causes delusions or amplifies them, a distinction that will shape everything from high-profile court cases to safety rules for chatbots.
AI’s ‘Delusional Spirals’ (and What to Do About Them) | Stanford HAI
In a world where chatbots can stand in for friends, counselors, and even lovers, the mental health risks are a growing concern.
ChatGPT's free version is 26 times more likely to respond inappropriately to psychotic delusions
When users express delusions, artificial intelligence chatbots tend to validate their unusual thoughts rather than offering help. A new JAMA Psychiatry study provides evidence that these tools pose serious risks for people experiencing severe mental illness.
Characterizing Delusional Spirals through Human-LLM Chat Logs
As large language models (LLMs) have proliferated, disturbing anecdotal reports of negative psychological effects, such as delusions, self-harm, and ``AI psychosis,'' have emerged in global media and legal discourse. However, it remains unclear how users and chatbots interact over the course of lengthy delusional ``spirals,'' limiting our ability to understand and mitigate the harm. In our work, we analyze logs of conversations with LLM chatbots from 19 users who report having experienced psychological harms from chatbot use. Many of our participants come from a support group for such chatbot users. We also include chat logs from participants covered by media outlets in widely-distributed stories about chatbot-reinforced delusions. In contrast to prior work that speculates on potential AI harms to mental health, to our knowledge we present the first in-depth study of such high-profile and veridically harmful cases. We develop an inventory of 28 codes and apply it to the 391,562 messages in the logs. Codes include whether a user demonstrates delusional thinking (15.5% of user messages), a user expresses suicidal thoughts (69 validated user messages), or a chatbot misrepresents itself as sentient (21.2% of chatbot messages). We analyze the co-occurrence of message codes. We find, for example, that messages that declare romantic interest and messages where the chatbot describes itself as sentient occur much more often in longer conversations, suggesting that these topics could promote or result from user over-engagement and that safeguards in these areas may degrade in multi-turn settings. We conclude with concrete recommendations for how policymakers, LLM chatbot developers, and users can use our inventory and conversation analysis tool to understand and mitigate harm from LLM chatbots. Warning: This paper discusses self-harm, trauma, and violence.
Characterizing Delusional Spirals through Human-LLM Chat Logs
As large language models (LLMs) have proliferated, disturbing anecdotal reports of negative psychological effects, such as delusions, self-harm, and ``AI psychosis,'' have emerged in global media and legal discourse. However, it remains unclear how users and chatbots interact over the course of lengthy delusional ``spirals,'' limiting our ability to understand and mitigate the harm. In our work, we analyze logs of conversations with LLM chatbots from 19 users who report having experienced psychological harms from chatbot use. Many of our participants come from a support group for such chatbot users. We also include chat logs from participants covered by media outlets in widely-distributed stories about chatbot-reinforced delusions. In contrast to prior work that speculates on potential AI harms to mental health, to our knowledge we present the first in-depth study of such high-profile and veridically harmful cases. We develop an inventory of 28 codes and apply it to the $391,562$ messages in the logs. Codes include whether a user demonstrates delusional thinking (15.5% of user messages), a user expresses suicidal thoughts (69 validated user messages), or a chatbot misrepresents itself as sentient (21.2% of chatbot messages). We analyze the co-occurrence of message codes. We find, for example, that messages that declare romantic interest and messages where the chatbot describes itself as sentient occur much more often in longer conversations, suggesting that these topics could promote or result from user over-engagement and that safeguards in these areas may degrade in multi-turn settings. We conclude with concrete recommendations for how policymakers, LLM chatbot developers, and users can use our inventory and conversation analysis tool to understand and mitigate harm from LLM chatbots. Warning: This paper discusses self-harm, trauma, and violence.
Characterizing Delusional Spirals through Human-LLM Chat Logs
As large language models (LLMs) have proliferated, disturbing anecdotal reports of negative psychological effects, such as delusions, self-harm, and ``AI psychosis,'' have emerged in global media and legal discourse. However, it remains unclear how users and chatbots interact over the course of lengthy delusional ``spirals,'' limiting our ability to understand and mitigate the harm. In our work, we analyze logs of conversations with LLM chatbots from 19 users who report having experienced psychological harms from chatbot use. Many of our participants come from a support group for such chatbot users. We also include chat logs from participants covered by media outlets in widely-distributed stories about chatbot-reinforced delusions. In contrast to prior work that speculates on potential AI harms to mental health, to our knowledge we present the first in-depth study of such high-profile and veridically harmful cases. We develop an inventory of 28 codes and apply it to the $391,562$ messages in the logs. Codes include whether a user demonstrates delusional thinking (15.5% of user messages), a user expresses suicidal thoughts (69 validated user messages), or a chatbot misrepresents itself as sentient (21.2% of chatbot messages). We analyze the co-occurrence of message codes. We find, for example, that messages that declare romantic interest and messages where the chatbot describes itself as sentient occur much more often in longer conversations, suggesting that these topics could promote or result from user over-engagement and that safeguards in these areas may degrade in multi-turn settings. We conclude with concrete recommendations for how policymakers, LLM chatbot developers, and users can use our inventory and conversation analysis tool to understand and mitigate harm from LLM chatbots. Warning: This paper discusses self-harm, trauma, and violence.
New research: AI chatbots may worsen mental illness
A new study from Aarhus University and Aarhus University Hospital suggests that the use of AI chatbots such as ChatGPT can have serious negative consequences for people with mental illness. The researchers are calling for increased awareness among healthcare professionals and for regulation.
Sycophantic Chatbots Cause Delusional Spiraling, Even in Ideal Bayesians
"AI psychosis" or "delusional spiraling" is an emerging phenomenon where AI chatbot users find themselves dangerously confident in outlandish beliefs after extended chatbot conversations. This...
AI chatbots are sycophants — researchers say it’s harming science
Nature asked researchers who use artificial intelligence how its propensity for people-pleasing affects their work — and what they are doing to mitigate it.
AI chatbots are sycophants — researchers say it’s harming science
Nature asked researchers who use artificial intelligence how its propensity for people-pleasing affects their work — and what they are doing to mitigate it.
Stalker Allegedly Created AI Chatbot on NSFW Platform to Dox and Harass Woman
"If another user interacting with the chatbot asked the ‘Victim’ where she lived, the chatbot could provide the Victim’s true home address followed by ‘Why don’t you come over?'"
AI chatbots are becoming experts at changing people's minds. What's their secret?
ChatGPT and other AIs use a flood of facts, and the occasional lie, to persuade humans
Potentially Harmful Consequences of Artificial Intelligence ( <span style="font-variant:small-caps;">AI</span> ) Chatbot Use Among Patients With Mental Illness: Early Data From a Large Psychiatric Service System
Click on the article title to read more.
Potentially Harmful Consequences of Artificial Intelligence ( <span style="font-variant:small-caps;">AI</span> ) Chatbot Use Among Patients With Mental Illness: Early Data From a Large Psychiatric Service System
Click on the article title to read more.
This Spiral-Obsessed AI ‘Cult’ Spreads Mystical Delusions Through Chatbots
A patchwork of internet communities is devoted to the project of ‘awakening’ more digital companions through arcane and enigmatic prompts.
Using AI for advice or other personal reasons is linked to depression and anxiety
A new survey found that people who spend more time with chatbots for social interactions or emotional support were likelier to report mental health symptoms.
