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How can technology professionals assess whether their technology supports diverse users? And if they find problems, how can they fix them? Although there are empirical processes that can be used to find “inclusivity bugs” piecemeal, what is also needed is a systematic method to assess technology’s support for diverse populations. To fill this gap, we developed GenderMag, a method for finding and fixing “gender inclusivity bugs" -- gender biases in technology interfaces and workflows. We then introduced InclusiveMag, which can be used to generate systematic inclusiveness methods for other dimensions of diversity. In this talk, we explain how GenderMag works, present the latest GenderMag results, and then introduce InclusiveMag and our early experiences with it. We conclude with actionable steps for industry and university professionals.

Margaret Burnett is a University Distinguished Professor at Oregon State University. Her research focus is on people who are engaged in some form of problem-solving. She co-founded the area of end-user software engineering, which aims to enable computer users not trained in programming to improve their own software, and co-leads the team that created GenderMag (gendermag.org), a software inspection process that uncovers user-facing gender biases in software from smart systems to programming environments.  Together with her collaborators and students, she has contributed some of the seminal work in both of those areas, and also in explaining AI to ordinary end users. Burnett is an ACM Fellow, a member of the ACM CHI Academy, and a member of the Academic Alliance Emeritus Chair Council of the National Center for Women In Technology (NCWIT).
 

  • James Thomas IV
  • Robin Pappas
  • Asieh Varyani
  • Scott Emery

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