Abstract
The emergence of new prestigious professions in data science and artificial intelligence (AI) provide a rare opportunity to explore the gendered dynamics of technical careers as they are being formed.
In this paper, Erin Young and Judy Wajcman of the Women in Data Science and AI programme contribute to the literature on gender inequality in digital work by curating and analysing a unique cross-country data set. They use innovative data science methodology to investigate the nature of work and skills in these under-researched fields. Their research finds persistent disparities in jobs, qualifications, seniority, industry, attrition and even self-confidence in these fields. They identify structural inequality in data and AI, with career trajectories of professionals differentiated by gender, reflecting the broader history of computing. Their work is original in illuminating gendering processes within elite high-tech jobs as they are being configured.
Paying attention to these nascent fields is crucial if we are to ensure that women take their rightful place at forefront of technological innovation.
Turing affiliated authors
