APA Looking Beyond Webinar - AI and the Future of Psychiatric Assessment: A Focus on Equity-Resource Handout

Resource Handout

Pdf Summary

The “APA Looking Beyond” series session, <strong>“AI and the Future of Psychiatric Assessment: A Focus on Equity,”</strong> features Dr. Steven Chan, Keris Myrick, and Dr. Peter Yellowlees.

The accompanying resources cover the evaluation of mental health apps, applications of AI in mental health care, and efforts to improve transparency and address bias in medical AI. They also include information on a health AI assurance initiative and the Division of Digital Psychiatry at Beth Israel Deaconess Medical Center and Harvard Medical School.

The listed scientific articles examine machine-learning approaches to detecting depression and potential demographic bias in AI systems. Topics include implicit gender, racial, and ethnic biases in automated psychiatric diagnoses, sociodemographic bias in medical decision-making by large language models, and racial bias in a population health-management algorithm. Together, these materials frame the session around the equity considerations involved in using AI for psychiatric assessment.

Keywords

AI and psychiatric assessment

equity in mental health care

machine learning and depression detection

bias in medical AI

implicit gender bias

racial and ethnic bias

large language models

mental health apps

digital psychiatry

health AI transparency