This course explores bias in computing at several levels with a focus on how data and technology intersect with and have an impact on different identities in computing. It will examine how bias towards different identities (such as gender, race, ethnicity, socio-economic status, ability, and sexual identity) impacts individuals working in the computing field. It will also examine how these biases can be embedded in data, algorithms, predictive models, and physical products.
The content of this course is roughly divided into the following three parts:
- Understanding different identities and intersectionality
- Exploring the history and status quo of diversity, inclusion and equity in Computer Science (both in academic and industry)
- Exploring bias in algorithms, prediction models, and technological products
- Kelly Shaw (kshaw@cs.williams.edu)
- Shikha Singh (shikha@cs.williams.edu)