Intersectional perspectives in digitalisation of science and society
About this video
Prof Schiebinger explains the efforts to remove and prevent gender and other types of bias in research and innovation by closing gaps in understanding how sex and gender influence results and differentiate outcomes of studies for women and men, often with worse impact for women. She focuses her talk on the Gendered Innovation project, which shows through evidence how methods of sex/gender analysis improve quality and impact of research. The focus of the talk is AI, including face recognition, robotics, and health technology with specific examples of gender, race, and stereotype biases embedded in the design of and the outputs from relevant applications.