About the workshop
We developed this workshop as part of our broader efforts to promote an open and inclusive community in the Allen School. Our goal is to empower students, staff, and faculty to make their daily interactions more inclusive and less biased.
This short workshop is designed to be informative and practical. We discuss why inclusion is important to our work in tech, define common concepts related to inclusion and bias, and practice making our conversations more inclusive. Participants should leave with a better understanding of why we must work collectively and proactively toward an inclusive environment, and have practical strategies for promoting inclusion in their daily interactions.
This workshop was built collaboratively: The idea and format are based on BiasBusters@Work developed at Google and refined for academic environments at CMU. We redesigned our workshop to reflect the culture and goals of the Allen School, with expert guidance from the NCWIT. Each presentation is adapted slightly to suit the specific audience.
As of June 2018, more than 200 Allen School members have participated: undergraduate and graduate students (including many TAs and student leaders), advisors, and lecturers.
Schedule or attend a workshop
Email diversity (at) cs.uw.edu to reach the facilitators of the Allen School Inclusiveness Workshop. If you work with an Allen School group that would benefit from a presentation, we're happy to talk about presenting. Ideal audience is 20-30 people.
If you work outside the Allen School and would like to see our materials or learn more about our workshop, we're happy to share resources and ideas.
Resources for instructors
- CS Teaching Tips from professor Colleen Lewis at Harvey Mudd College
- Teaching strategies for teaching students with disabilities (NCWIT)
- CMU Bias Busters site with links to research and resources
- Inclusive Teaching in CS guidelines from Stanford
- NCWIT's tips for Interrupting Bias In Academic Settings
- NCWIT article on Broadening Participation by Supporting Great Teaching, from ACM Inroads
- Overview of research and case studies on increasing retention with inclusive pedagogy
Research and texts cited in our workshop
- Philip Guo, Silent Techical Privilege
- Interview with Philip Guo about his article
- Research article on gender and self-citation across fields and over time
- Orchestrating Impartiality: The Impact of "Blind" Auditions on Female Musicians
- Want to Get a Job? Add "Mister" to Your Name.
- Are Emily and Greg More Employable than Lakisha and Jamal?
- Gender Bias in Academe: An Annotated Bibliography of Important Recent Studies
- Stereotype Threat: An overview. More than 300 peer-reviewed studies showing a range of impacts
Additional research on bias and inclusiveness in tech and academia
- Podcast on bias (good and bad) in machine learning and AI
- How Search Commitees Can See Bias in Themselves, on hiring in academia
- Amazon Scraps AI Tool Developed for Hiring Due to Bias