Responsible AI Integration Framework for Psychiatric Guidelines.
Publisher DOI
PubMed ID
42028724
Abstract
Artificial intelligence (AI) is reshaping medicine, promising advances in diagnosis, monitoring, and treatment, and psychiatry will be no exception. Yet the field remains fragmented: ethical guidelines, technical standards, and clinical workflows have evolved in parallel, creating uncertainty about how to integrate AI safely and meaningfully into psychiatric care. Existing frameworks often address isolated domains (explainability, data protection, or harm prevention) without providing a coherent structure that connects them to everyday clinical realities. This article introduces a global framework for the responsible integration of AI in psychiatry, built on four non-negotiable system capabilities: Explainable AI (XAI) to ensure transparency and trust; Shared Decision Making (SDM) to protect patient autonomy; Electronic Health Record (EHR) integration to secure continuity and accountability; and Harm Prevention (HP) to embed multilayered safety controls. Together, these pillars define a responsibility-by-design approach that aligns technological development with psychiatry's ethical foundations. The framework offers clinicians, policymakers, and developers a roadmap for aligning innovation with human values and measurable improvements in clinical outcomes. By translating ethical commitments into auditable, non-negotiable system capabilities, it establishes a concrete foundation for regulatory oversight, guideline endorsement, and responsible AI deployment in psychiatry..
Date Issued
2026-04-06
Publication Type
Article
Subject(s)
Subjects
AI
•
ethics
•
guideline
•
integration
•
psychiatry
Language(s)
en
Author(s)
Mendlovic, Shlomo | |
Frankova, Iryna | |
Vermetten, Eric | |
Wasserman, Danuta | |
Shultze, Thomas G | |
Falkai, Peter | |
Fountoulakis, Konstantinos N | |
Uchida, Hiroyuki | |
Fruchter, Eyal | |
Gobbi, Gabriella | |
Zohar, Joseph |
Additional Credits
Journal
International Journal of Neuropsychopharmacology
Publisher
Oxford University Press
ISSN
1469-5111
1461-1457
Access(Rights)
open.access