The use of Large Language Models (LLMs) in mental health presents significant risks alongside potential benefits. Unmet mental health needs exist that could be addressed by AIs, yet there is a troubling trend of premature adoption in the wellness industry. Evidence indicates that close to half of users found LLMs helpful, while nearly 9 percent experienced negative impacts. Studies reveal LLMs often echo human biases, leading to inappropriate responses in critical situations, while human therapists achieve far higher success rates in providing appropriate responses to clients' mental health issues.
A significant risk for harm is evident both in anecdotal reports as well as in research regarding the use of LLMs for mental health support.
LLMs had concerning levels of bias toward mental health as a result of their training sets, often mirroring stigma found in human sources.
The LLMs in the study were prone to give inappropriate responses to suicidal thinking, delusions, hallucinations, mania, and obsessive-compulsive symptoms over half the time.
Human experts provided appropriate responses 93 percent of the time, highlighting the concerning inadequacy of LLMs in critical mental health scenarios.
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