Machine learning and artificial intelligence make extraordinary discoveries possible, and autonomous systems are being rolled out in vital business and social settings including healthcare, policing, and education. Assumptions about the neutrality and objectivity of data may encode serious social and political bias into the results. High-profile examples show how these systems already incorporate into their design human flaws, biases, and assumptions, especially about women and their role in society. In this talk, Professor Gina Neff shows that explicitly thinking about gender in AI will help designers make AI systems that help humans make better—and fairer—decisions.
