Quantifying bias: A Data-Driven Approach to Workplace Gender Equality
AI affects almost every aspect of our daily lives, yet there is a troubling underrepresentation of women in this sector. As technology reflects the worldview of its developers, AI systems are being coded with social biases. Alongside gender-biased AI, there are significant economic and governance-related issues associated with the exclusion of women from AI careers. This talk explores how the gendered nature of technical culture and workplace defaults are key factors in women’s underrepresentation in tech. It introduces the current data-driven research at the Turing to monitor these ‘chilly’ workplace environments and motivate evidence-based policy towards achieving gender equality.
Anna FitzMaurice is a postdoctoral research fellow on The Alan Turing Institute’s Women in Data Science and AI project. Her research at the Turing sits at the intersection of technology and society, taking a data-driven approach to investigating the systematic exclusion of women from tech, and the impact this is having on the development of AI. As well as industry experience in data science, she holds a PhD from Princeton University in Atmospheric and Oceanic Sciences, with a focus on modelling ice-ocean interactions under future climate change scenarios, and an MMath in Mathematics (first class) from the University of Oxford.