From Risk Avoidance to User Empowerment in AI Mental Health Crisis Support
This addresses the issue of inadequate AI support for individuals in mental health crises, potentially improving access to care, but it is incremental as it builds on existing community helper models.
The paper tackles the problem of generative AI chatbots avoiding engagement in mental health crises to minimize developer liability, which may harm users and reduce help-seeking motivation. It proposes empowerment-oriented design principles to enable AI chatbots to act as supportive bridges to de-escalate crises and connect users to reliable care.
People experiencing mental health crises frequently turn to open-ended generative AI (GenAI) chatbots for support. However, rather than providing immediate assistance, some GenAI chatbots are designed to respond to crisis situations in ways that minimize their developers' liability, primarily through avoidance (e.g., refusing to engage beyond templated referrals to crisis hotlines). Withholding crisis support in these cases may harm users who have no viable alternatives and reduce their motivation to seek further help. At scale, this avoidant design could undermine population mental health. We propose empowerment-oriented design principles for AI crisis support, informed by community helper models. As an initial touchpoint in help-seeking, AI chatbots can act as a supportive bridge to de-escalate crises and connect users to more reliable care. Coordination between AI developers and regulators can enable a better balance of risk mitigation and user empowerment in AI crisis support.