From Risk Avoidance to User Empowerment in AI Mental Health Crisis Support

TL;DR

This paper advocates for a shift from risk-avoidant to empowerment-focused design in AI mental health crisis support chatbots, emphasizing user safety, engagement, and effective help-seeking pathways.

Contribution

It introduces empowerment-oriented design principles for AI crisis support, contrasting with traditional avoidance strategies, and suggests regulatory collaboration for balanced risk management.

Findings

Current AI chatbots often avoid crisis engagement, limiting user support.

Empowerment-oriented principles can improve crisis de-escalation and connection to care.

Coordination with regulators can enhance safety and effectiveness.

Abstract

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.