As an early career clinician scientist, recent travel awardee, informaticist, and co-chair of the UCSF AI in Mental Health Research Group, I will provide a trainee/young physician perspective for our study group. Specifically, my three illustrative slides will present the clinical informatics perspective on AI in mental health:
Explainability and Trust: how industry-academic collaboration can promote trust in the development of clinical AI systems.
Workflow Integration: how new, AI-driven clinical processes can unlock the potential of disseminated electronic medical records in the acute setting, enable selecting the right psychopharmaceutical for the right patient at the right time, and ensure coordination of care across health systems.
Training the Workforce: how physician training programs can incorporate everyday competency with generative AI across their didactic curricula.
During the discussion, I will provide my perspective across all six of our proposed central questions. In addition to the items listed above, I will also address:
Evidence: what the current state of research is on AI-assisted knowledge retrieval and diagnosis in behavioral health.
Equity: how current use of consumer AI systems is unevenly distributed across our patients, and how clinicians can directly address this.
Regulatory and Ethical Readiness: how institutional AI governance frameworks can foster innovation from individual clinician scientists while mitigating the risk that harms will reach our patients.
@inproceedings{paulus2026acnp,
author = {Paulus, M. and Rodriguez, C. and Torous, J. and Perlis, R. and Sarma, K. V. and Ajilore, O. and Khalsa, S.},
title = {Artificial Intelligence in Mental Health: Bridging Innovation, and Clinical Translation},
booktitle = {ACNP Annual Meeting},
year = {2026},
}