Professor Stevie Chancellor at ECE Fall 2024 Colloquium

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

Machine learning and AI are now at the forefront of technological interest in solving socially challenging problems, like understanding and intervening in dangerous mental illness behaviors. There is an urgent need to innovate data-driven systems to handle the volume and risk of this content in social networks and its contagion to others in the community. However, traditional approaches to prediction have mixed success, partly because technical solutions oversimplify complex behavior for technical tractability, and these problems are uniquely human and messy. This is exacerbated by recent press indicating that technology can be harmful for well-being. 

In this talk, I will argue that we need human-centered AI as a lens to make socially complex AI tech more technically rigorous and accurate, ethical, and compassionate for the people it impacts. My approach to this problem combines my disciplinary training in Media Studies and Computer Science, drawing on social science theory for more informed technological innovation. To unpack the transformative potential of human-centered AI, we’ll look at my group’s work in mental illness and social media as a case study.