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Course Description

Course Description

Artificial intelligence (AI) is rapidly reshaping the landscape of mental health research, clinical care, and patient engagement. At the same time, the increasing use of AI in mental health raises important questions about trust, safety, lived experience, and the appropriate role of technology in understanding and supporting human well-being.

The Future of Artificial Intelligence and Mental Health is an asynchronous distinguished speaker series developed as part of the AIM-AHEAD Connect Course Series. The course brings together subject matter experts from across mental health, psychiatry, artificial intelligence, and related disciplines to explore both the opportunities and challenges associated with the growing role of AI in mental health.

Across four expert-led modules, participants will examine AI and mental health from multiple perspectives, including its implications for vulnerable populations and the relationship between AI and lived experiences of mental health and madness, the importance of trauma-informed AI, and the translation of AI and data-driven approaches into psychiatric research and practice.

Rather than focusing primarily on the technical development or coding of AI systems, this course encourages participants to think critically about how AI is being used, whom it serves, where its limitations lie, and how it can be developed and implemented responsibly in mental health settings.

No coding or advanced technical experience is required. The series is designed to make emerging developments in AI and mental health accessible to researchers, clinicians, healthcare professionals, trainees, and others interested in the future of responsible and human-centered mental health innovation.

Course Structure

Module 1: AI & Mental Health: Vulnerable Populations

Presenter: Rose Yesha, PhD

This module examines the growing role of artificial intelligence in mental health through the lens of vulnerable populations. Participants will consider how AI can better recognize, understand, and respond to mental health needs while supporting responsible approaches to care.

Module 2: Beyond Safety: AI, Madness, and the Politics of Meaning

Presenter: Sascha Altman DuBrul, MSW

This module moves beyond conventional discussions of AI safety to examine how artificial intelligence interacts with human distress, lived experience, meaning-making, and relationships of care. It considers the distinction between technological pattern recognition and genuine relational accountability and explores how AI might strengthen rather than replace human networks of support.

Module 3: Building AI to Carry Consequence: The Case for Trauma-Informed AI Across Systems of Care

Presenter: Jimi Ige, MPA

This module examines how trauma-informed principles can be embedded into artificial intelligence used across healthcare, education, and social services. It considers what it means to build AI systems that recognize the real-world consequences of their outputs and seeks approaches that reduce harm while supporting compassionate and responsible care.

Module 4: AI in Psychiatry and Learning Health Systems: Translational Research

Presenter: Ananya Joshi, PhD

This module explores translational artificial intelligence research in psychiatry and learning health systems. Participants will consider how AI and data-driven approaches can help move knowledge from research into practice while supporting continuous learning and improvement within healthcare systems.

Intended Audience

This course is open to anyone interested in the intersection of artificial intelligence and mental health. It is particularly relevant for:

  • Mental health professionals and clinicians

  • Physicians, psychologists, psychiatrists, counselors, and social workers

  • Healthcare and public health professionals

  • Researchers and research staff

  • Data scientists and informatics professionals

  • AI and machine learning professionals working in healthcare

  • Students, fellows, residents, and other trainees

  • Individuals involved in digital health, behavioral health, and health technology

  • Community members and others interested in the ethical and responsible application of AI to mental health

Participants do not need previous experience in artificial intelligence, machine learning, or computer programming.

Learning Objectives

This course is intended to provide participants with a foundational and interdisciplinary understanding of the evolving relationship between artificial intelligence and mental health, while encouraging critical consideration of the opportunities, limitations, and responsibilities associated with these technologies.

  1. Understand AI in Mental Health: Describe emerging applications of artificial intelligence and related technologies within mental health research, clinical care, and behavioral health.

  2. Examine Vulnerable Populations: Identify opportunities, limitations, and potential risks associated with the use of AI among vulnerable populations.

  3. Critically Evaluate AI and Mental Health: Examine how AI technologies interact with complex concepts of mental health, lived experience, diagnosis, identity, and differing understandings of psychological distress.

  4. Understand Translational Psychiatry: Explore how AI, data science, and emerging computational approaches can contribute to translational psychiatry and help bridge research discoveries with clinical practice.

  5. Recognize Responsible AI Considerations: Examine issues related to trust, safety, transparency, accountability, privacy, and responsible AI implementation in mental health contexts.

  6. Consider the Future of AI and Mental Health: Evaluate emerging directions in AI-enabled mental health research and care while considering how technological innovation can remain grounded in human needs, lived experience, and responsible practice.

Instrumental Persons

We would like to recognize and express our gratitude to the individuals who contributed their expertise, leadership, and support to the development and implementation of The Future of Artificial Intelligence and Mental Health Distinguished Speaker Series.

Course Director and Presenter

Rose Yesha, PhD: Course Director, Curriculum Lead, and Presenter

Distinguished Speakers and Presenters

Sascha Altman DuBrul, MSW: Distinguished Speaker and Presenter 

Jimi Ige, MPA, PMP: Distinguished Speaker and Presenter

Ananya Joshi, PhD: Distinguished Speaker and Presenter

Course Directors

  • Nawar Shara, PhD - Course Director
  • Alexander Libin, PhD - Course Director
  • Omar Aljawfi, PhD: Course Director
  • Prabhjeet Singh, BDS, MSPH - Course Director
  • Maryam Solimany - Course Director
  • Toufeeq Syed, PhD - MPI, AIM-AHEAD Coordinating Center, Communications Hub
  • Cara Morrison - Program Manager, Communications Hub
  • Salma Baig - Research Intern
  • Emily Lam - Research Intern 

We also gratefully acknowledge the contributions and support of the AIM-AHEAD Data Science Training Core (DSTC) and AIM-AHEAD Communications Hub in supporting the development, implementation, and dissemination of this course.

Funding

The AIM-AHEAD program is funded by the National Institutes of Health (NIH). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.