Cultural Validation as a Patient-Safety Priority in AI-Assisted Mental Health Care

Generative artificial intelligence (AI) is increasingly being integrated into mental health care, yet its safety and effectiveness across diverse cultural and linguistic contexts remain insufficiently established. This letter emphasizes the importance of cultural validation as a fundamental patient-safety requirement rather than a secondary consideration in the development and implementation of AI-assisted mental health interventions. Drawing on emerging evidence concerning AI-related risks and culturally adapted digital interventions, it highlights critical challenges associated with culturally specific expressions of psychological distress, somatic symptoms, linguistic diversity, stigma, and help-seeking behaviors. To address these challenges, participatory co-design, culturally sensitive clinical assessments, subgroup-specific evaluations, and continuous postdeployment monitoring are recommended. Integrating cultural, psychological, and bodily dimensions into AI evaluation frameworks may enhance clinical safety, promote equitable access to mental health services, and reduce the risk of culturally inappropriate recommendations. Cultural validation should therefore become an essential component of responsible AI implementation in mental health care.