Human-Centered AI for Mental Health Prediction in Social Media Data

Explore the intersection of human-centered AI and mental health prediction in social media data through this thought-provoking lecture by Dr. Stevie Chancellor from the University of Minnesota. Delve into the challenges and opportunities of using machine learning and AI to identify and intervene in potentially dangerous mental health behaviors discussed online. Examine the limitations of traditional prediction approaches and discover how human-centered machine learning can lead to more technically rigorous, ethical, and compassionate solutions. Learn about the importance of combining insights from Media Studies and Computer Science to create a more informed and context-aware technological innovation. Gain valuable insights into the speaker's research agenda, which aims to build and critically evaluate human-centered systems for high-risk health behaviors in online communities. Understand the potential impact of this work on addressing urgent issues such as disordered eating, suicide crisis, and self-injury in social media contexts.

Stanford - How Do We Make Human-Centered AI for Mental Health Prediction in Social Media Data?