Please fill out this form BEFORE 1pm on the first day of class if you're interested in taking the course. Course size will be limited and you must fill this out to be considered for the class (credit or listener).
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.
Room & Time:
Classes will meet in person, subject to the latest Covid-19 guidance from MIT
E14 or E15 (75 Amherst Street; Cambridge, MA) All classes will now be held in E14-633
Wednesdays, 10am-noon, February 2 - May 4, 2022
Credits:
This is a graduate-level 9 hour course, with 2 hours/week in class and 7 hours/week of homework/project work.
By special request, we are usually allowed to increase the credit hours to 12 by adding additional weekly research article readings and/or project work. If you want this, please request it the first week.
There is no final exam.
Contact:
To reach the course staff please email:
Professor Picard: picard (at) media (dot) mit (dot) edu
Rob Lewis (TA): roblewis (at) media (dot) mit (dot) edu
Context on Mental Health:
Excerpted from the WHO website. Read more here.
The prevalence and impact of mental health:
“Mental health conditions are increasing worldwide ... with a 13% rise in mental health conditions and substance use disorders in the last decade (to 2017). Mental health conditions now cause 1 in 5 years lived with disability. Around 20% of the world’s children and adolescents have a mental health condition, with suicide the second leading cause of death among 15-29-year-olds. Approximately one in five people in post-conflict settings have a mental health condition.
Mental health conditions can have a substantial effect on all areas of life, such as school or work performance, relationships with family and friends and ability to participate in the community. Two of the most common mental health conditions, depression and anxiety, cost the global economy US$ 1 trillion each year.”
Call to action: how can we design technology to address these needs?
“Many mental health conditions can be effectively treated at relatively low cost, yet the gap between people needing care and those with access to care remains substantial. Effective treatment coverage remains extremely low.
Increased investment is required on all fronts: for mental health awareness to increase understanding and reduce stigma; for efforts to increase access to quality mental health care and effective treatments; and for research to identify new treatments and improve existing treatments for all mental disorders.”