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Where are the Women? Mapping the Gender Job Gap in AI


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Young women using computers.

A report from The Alan Turing Institute shows the extent of gender disparities in careers, education, jobs, seniority, status, and skills in the artificial intelligence and data science fields.

Credit: Mike Ngo Photography/Flickr

A decade ago, Harvard Business Review named data scientists as "the sexiest job of the 21st century." Since then hiring in the fields of artificial intelligence and data science has exploded as the world is increasingly being built around smart machines and automated systems. 

Yet the people whose work underpins that vision are far from representative of the society those systems are meant to serve.

Only 22% of data and AI professionals in the UK are women, and this drops to a mere 8% of researchers who contribute to the pre-eminent machine learning conferences.

This is not only a fundamental issue of economic equality, but also about how the world is designed and for whom. Mounting evidence (e.g. Buolamwini and Gebru, 2018; West, Whittaker and Chew, 2019) suggests that the under-representation of women and marginalised groups in AI results in a feedback loop whereby bias gets built into and amplified by machine learning systems. 

Addressing the gender job gap in AI is the first step to ensuring that our technology works for all of society.

From The Alan Turing Institute
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