MAS.772 AI for Mental Health


Christine Daniloff, MIT

Christine Daniloff, MIT

Rosalind W. Picard, Professor of Media Arts and Sciences
default units = 9; up to 12 units may be arranged with extra work for graduate students
Wednesdays 10-12
mostly on zoom
View on Canvas

This course will NOT be taught in 2024

Advances in AI provide us the opportunity to transform support systems for mental health and well-being, making them more accurate, more effective, and more accessible. With intelligent interfaces we can empower individuals with the knowledge and the tools to lead healthier and happier lives, for example helping them to stay resilient when confronted with stress and uncertainty, and perhaps prevent the onset or escalation of a mental illness. Moreover, with sensors and machine learning we can seek to understand and objectively measure changes in mental health, supporting individuals and clinicians with condition management, as well as contributing to new scientific advances.

This interdisciplinary, project-based course will overview the growing field of digital mental health. We will overview evidence-based behaviors that can influence changes in mood, sleep, social interaction, etc. Furthermore, we will survey digital mental health systems and how they support and enhance these techniques, e.g., through chatbots, gamification, personalization algorithms and just-in-time interventions, machine learning for symptom identification and severity prediction, etc. Students will work in teams to each propose and carry out a project as part of learning to conduct research on AI-related technology to improve human mental health and wellbeing.

Please check the (regularly updating) syllabus on the public website at:

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