Today we’re joined by Stevie Chancellor, an Assistant Professor in the Department of Computer Science and Engineering at the University of Minnesota.
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In our conversation with Stevie, we explore her work at the intersection of human-centered computing, machine learning, and high-risk mental illness behaviors. We discuss how her background in HCC helps shapes her perspective, how machine learning helps with understanding severity levels of mental illness, and some recent work where convolutional graph neural networks are applied to identify and discover new kinds of behaviors for people who struggle with opioid use disorder.
We also explore the role of computational linguistics and NLP in her research, issues in using social media data being used as a data source, and finally, how people who are interested in an introduction to human-centered computing can get started.
Connect with Stevie!
- Paper: Methods in predictive techniques for mental health status on social media: a critical review
- Paper: A Taxonomy of Ethical Tensions in Inferring Mental Health States from Social Media
- Paper: Quantifying and Predicting Mental Illness Severity in Online Pro-Eating Disorder Communities
- A Future of Work for the Invisible Workers in A.I. with Saiph Savage – #447
- Is Linguistics Missing from NLP Research? w/ Emily M. Bender – #376
- Can Language Models Be Too Big? w/ Emily Bender and Margaret Mitchell – #467
- ACM FAccT Conference