Overview
As more people turn to AI chatbots during moments of mental health crisis, this resource examines how leading AI companies are responding today—drawing on a workshop that convened AI and mental health organizations, clinicians, researchers, and people with lived experience, alongside the authors’ own analysis. It maps the range of approaches currently in use, organizes them into a taxonomy of six common intervention types, and lays out the practical challenges companies face across detecting risk, assessing it, responding to users, and evaluating whether those responses actually help. It is candid that the field is at an inflection point: the problems are well enough understood to motivate action, but the shared infrastructure for coordinated, cross-industry action does not yet exist. The resource closes with the key questions the field still needs to resolve and suggested next steps, making it a useful orientation for anyone working on responsible AI, product safety, or the intersection of AI and well-being.
Do you have feedback on this resource?
Thank you for your feedback as we strive to curate and publish resources to help social impact organizations succeed with data.
Related Resources
How to prioritize efforts when strengthening an organization’s data maturity
This guide aims to help organizations develop objectives and prioritize efforts when becoming more data mature.
How to apply an intersectional and IDEA lens to your data practice
Despite good intentions, data is sometimes collected, analyzed, and used in ways that can replicate or even amplify existing injustices and inequalities.
