Wednesday, July 28 at 10:45 AM-12:00 PM

This workshop originates from a student-led, grassroots effort at the Carnegie Melon University Computer Science Department to instate a mandatory course for first-year PhD students focused on improving the climate and making academia more just. The course covers topics including implicit bias, equity, privilege, microaggressions, systemic inequality, bias in technology, and allyship. We secured approval to run a pilot course in Spring 2021 for all first-year PhD students. After positive feedback from pilot attendees, we are now developing a semester-long version of the course. In this workshop, participants will learn (1) the results of this pilot (via course evaluation data), within a broader discussion of the viability of mandating anti-bias learning in an academic setting; (2) how we developed and evaluated the curriculum; (3) how to utilize our open-source curriculum materials to replicate our efforts; and (4) the strategies we have used to overcome challenges such as securing approval for this initiative in our department, engaging students with different interests and backgrounds, fostering participation in a mandatory setting, ensuring that in-class discussions remain safe spaces that spark critical thinking, and, importantly, developing and running the course in a way that lifts up marginalized voices without putting added burden on marginalized groups. Finally, we discuss our upcoming work on collecting more data and extending this initiative to other departments and universities.

Presenters

Bailey Flanigan

Bailey Flanigan is a PhD student in Computer Science at Carnegie Mellon University. In her research, she aims to improve the efficacy and fairness of methods for collective participation in democratic decision-making (e.g., citizens’ assemblies). She is broadly interested in structural inequalities in the culture of academia, and over the past year she has been leading a team of several graduate students in the development of the mandatory anti-bias course being presented at the workshop.

Sara McAllister

Sara McAllister is a PhD student in Computer Science at Carnegie Mellon University. Her research focuses on designing storage, caching, and memory systems that are efficient at scale and leverage future hardware interfaces. She is also interested in ensuring computer science and academia in general is accessible to and inclusive of all people and toward this goal, she is a co-creator of the mandatory anti-bias education course for PhD students being presented at this workshop.

Catalina Vajiac

Catalina Vajiac is a PhD student in Computer Science at Carnegie Mellon University. Her research focuses on developing algorithms and interfaces for fighting human sex trafficking online through the analysis of online escort websites and social media. Outside of research, she directs her efforts toward making academia more inclusive, and is a co-creator of the mandatory anti-bias course for PhD students being presented at the workshop.