Stanford - How Do We Make Human-Centered AI for Mental Health Prediction in Social Media Data?
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ML Maths Basics90%Unsupervised Learning80%Supervised Learning80%Research Methods70%AI Ethics & Policy60%
How Do We Make Human-Centered AI for Mental Health Prediction in Social Media Data?
Stevie Chancellor of University of Minnesota
November 10, 2023
Machine learning and AI are now at the forefront of technological interest in solving socially challenging problems. Specifically, there is much interest in identifying and intervening in physically dangerous mental health behaviors discussed on social media, such as promoting disordered eating, suicide crisis, or self-injury. 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.
In this talk, I will discuss the importance of human-centered machine learning as a lens to make predictions about mental health in social media more technically rigorous, ethical, and compassionate. 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. Together, these inform an agenda for human-centered machine learning that is scientifically and technically rich, more ethical, and considerate of social contexts in data.
About the speaker:
Dr. Stevie Chancellor is an Assistant Professor in the Department of Computer Science & Engineering at the University of Minnesota - Twin Cities. Her research combines approaches from HCI and ML to build and critically evaluate human-centered systems, focusing on high-risk health behaviors in online communities. Her work has been recognized with awards from CHI, CSCW, and ICWSM. Her work has been covered in international outlets, such as the United Nations ITU, The New York Times, The Washington Post, The Atlantic, and other popular press. Dr. Chancellor received her doc
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