How can software professionals systematically assess whether their software supports diverse users? And if they find problems, how can they fix them? Our team's prior research revealed software's failures to support different genders' user experiences equitably, and then produced the GenderMag method to address this problem, which is now in use around the world. Today we present our research toward a new method, SocioeconomicMag, to help improve software's equitability across socioeconomically diverse users. SocioeconomicMag is just emerging, and we are actively looking for field collaborators to try it out in the field.
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, 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).