Dr. Jacob Thebault-Spieker earned both a BA and PhD in Computer Science from the University of Minnesota. His research interests focus on bias, social computing, crowd work, and the shared economy. Dr. Thebault-Spieker’s work will be an important accelerator for the iSchool’s relationships in the new School of Computer, Data & Information Sciences.
Educational/professional background:
I’m a computer scientist by training, and I’ve been in academia my entire career.
What is your area of focus?
My research focuses on how, why, and in which contexts biases do or do not occur in large-scale online social platforms. I also build and experiment with mitigation approaches. In the past, I have studied biases in systems like Uber and Wikipedia, and more recently my work has focused on political biases in content moderation.
What main issue do you address or problem do you seek to solve in your work?
Biases and disparities in computational systems often stem from the human labor that underpins these systems or the data they’re built on. At its core, my research is focused on ameliorating these biases and similar weaknesses in computational systems and data.
What is one thing you hope students who take a class with you will come away with?
Many problems, and solutions, are inherently sociotechnical. That is, there is an interplay between individual, social, and technical facets of a given problem, which is important in thinking about solutions.
What attracted you to UW-Madison?
First, I love the Midwest! I’m also very excited to be part of the UW-Madison iSchool, and learn from colleagues and students who have perspectives focused on serving the public and social issues.
Do you feel your work relates to the Wisconsin Idea? If so, please describe how.
I think it does. Broadly, I think of my research as working towards ‘technological pluralism’ by ensuring that technology serves all people well. Some of my research has explicitly focused on the urban-rural divide in systems, and has both identified weaknesses for rural communities and put forward ideas about how to compensate for these weaknesses.
Technology and people often work together to create global encyclopedias like Wikipedia, to make it easy to call a ride in Uber, or even to help make sure that political misinformation doesn’t spread on sites like Facebook. My work tries to make sure that this effort doesn’t advantage some people over others.