Northwestern Events Calendar

Nov
23
2020

CS Colloquium - Stevie Chancellor, Northwestern University

When: Monday, November 23, 2020
12:30 PM - 1:30 PM  

Where: Online

Audience: Faculty/Staff - Student - Post Docs/Docs - Graduate Students

Contact: Pam Villalovoz   847.467.6558

Group: Department of Computer Science

Category: Academic

Description:

Live Stream link: 
https://northwestern.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=918bb170-6258-4ab5-ad4d-ac640142ecd6

Title: 
Human-Centered Machine Learning for Dangerous Mental Health Behaviors Online

Abstract
Research and industry both use machine learning to identify and intervene in physically dangerous behaviors discussed on social media, such as advocating for self-injury or violence. There is an urgent need to innovate in data-driven systems to handle the volume and risk of this content in social networks and its propagation to others in the community. However, traditional approaches to prediction have mixed success, in part because technical solutions oversimplify complex behavior and the unique interactions of dangerous communities with both individuals and platforms. The difficulties in computationally handling these circumstances threatens the applications of these techniques to pressing social problems.

In this talk, I will describe my work in human-centered machine learning, an approach that refocuses technological innovation on the needs of humans, communities, and stakeholders. I study this through dangerous mental illness behaviors in online communities, like opioid abuse, suicidal ideation, and promoting eating disorders. First, I will talk about my work in building novel and human-centered prediction systems that make robust and accurate assessments of mental illness signals across several conditions. Then, I will discuss recent research on a crucial part of machine learning pipelines - generating labels for training data and reporting standards in papers. I have found alarming gaps in construct validity and rigor that jeopardize the state-of-the-art – and I’ll discuss our current work on how we’re attempting to fix this. Together, these inform an agenda for human-centered machine learning that is scientifically and technically rich and more considerate of social contexts in data, providing a pathway for more impactful and ethical problem solving in computer science.

Biography
Dr. Stevie Chancellor is the CS + X Postdoctoral Fellow in Computer Science at Northwestern University. Her research combines approaches from human-computer interaction and machine learning to build and critically evaluate human-centered systems, focusing on high-risk health behaviors in online communities. Dr. Chancellor’s research agenda has produced 14 publications in premier venues like CHI, CSCW, and FAccT, and has received four Honorable Mention awards at CHI and CSCW. Her work has been featured in The Atlantic, Wired, Smithsonian Magazine, and Gizmodo. Dr. Chancellor recently received her doctorate in Human-Centered Computing from Georgia Tech, and she will start as an Assistant Professor in Computer Science and Engineering at the University of Minnesota in 2021.

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