HAI Policy Briefs
February 2021
AI-Enabled Depression Prediction Using Social Media
Natural language processing for mental health monitoring is an emerging use of AI poised to disrupt the landscape of the health care industry. As the profusion of social media platforms allows for the population to share their thoughts and feelings with the world, users’ posts and reactions extend the scope of medical screening methods for psychological disorders such as depression. Users are already being marketed with sophistication based on these behaviors — why not leverage these technologies for public health?
Key Takeaways
➜ AI-enabled depression prediction is capable of matching the accuracy of traditional screening surveys but can be delivered to whole (consenting) populations.
➜ By examining social media language, our model can make a significant impact in recognizing the most widespread mental illnesses in the world.
➜ Policymakers and regulators must establish clearer guidelines about access to data, understand the consequences of using algorithms to change social media posts into protected health information, and consider how depression detection can be combined with digital treatments in a modern system of care.
Authors
Johannes C. Eichstaedt - Stanford University