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Women in Data Science and AI
Using research to inform policy measures aimed at increasing equity in the data science and AI fields
Introduction
The Women in Data Science and AI theme sits within the Public Policy Programme at The Alan Turing Institute. We work alongside policy makers and industry stakeholders, offering actionable insights and recommendations to tackle the multifaceted ethical, economic and governance-related issues stemming from inequalities in AI.
Aims
The fields of AI and data science have grown exponentially as the world is increasingly being built around automated systems and 'smart' machines. Yet the people whose work underpins this are far from representative of the society these systems are meant to serve.
As AI becomes ubiquitous in everyday life, the drive for diversity and inclusion in technology is of pressing concern. In particular, the persistent under-representation of women and marginalised groups in data science and AI, including gender data gaps, leads to the encoding and amplification of bias in technical products and algorithmic systems, creating harmful feedback loops.
It is crucial that we get ahead of this now, before flawed technologies become irreversibly integrated into the fabric of society. We address these complex challenges through a three-tiered approach:
- Mapping the participation of women in data science and AI in the UK, and globally. Women make up half the UK population, but only 22% of AI and data professionals and 18% of users across the largest online global data science platforms. Our aim is to increase the number of women in these fields.
- Investigating diversity and inclusion in online and physical workplace cultures. We explore the ‘chilly’ organisational cultures of tech companies and institutions that result in persistent structural divergence in women’s and men’s career trajectories.
- Exploring how the gender gap shapes scientific knowledge and technological innovation. The lack of diversity in the AI ecosystem results in harmful feedback loops of social bias being built into machine learning systems. We promote responsible, gender inclusive AI design.
A demonstration of gender bias when translating Hungarian to English on Google Translate
A hiring algorithm developed by Amazon was found to discriminate against female applicants
The Apple Card's algorithm was accused of being a 'sexist program' in 2019
An independent audit found that Facebook was withholding certain job ads from women because of their gender
Scientists found music recommendation algorithms had a biased feedback loop
According to a 2020 BBC Investigation, women with darker skin are more than twice as likely to be told their photos fails UK passport rules
Recent Publications
Wajcman, J., Young, E., and Kampmann, D. (2024). Rebalancing Innovation: Women, AI and Venture Capital in the UK Second Report. The Alan Turing Institute.
Wajcman, J., Young, E., and De Miguel Velazquez, J. (2023). Rebalancing Innovation: Women, AI and Venture Capital in the UK. The Alan Turing Institute.
Young, E,, Wajcman, J. and Sprejer, L. (2023) Mind the gender gap: inequalities in the emergent professions of artificial intelligence (AI) and datascience. New Technology, Work and Employment, 38, pp. 391–414. https://doi.org/10.1111/ntwe.12278414
Wajcman, Judy and Young, Erin. (2023) ‘Feminism Confronts AI: The Gender Relations of Digitalisation’, in Feminist AI: critical perspectives on data, algorithms and intelligent machines, J. Browne, S. Cave, E. Drage, and K. McInerny (eds.), Oxford University Press, pp. 47-64.
Current work
Rebalancing Innovation: Women, AI and Venture Capital
Venture capital (VC) spurs technological innovation and diversity within investment firms results in better performance. Yet in the UK, women comprise only 20% of investment roles in the VC labour force, and most VC investments in AI start-ups in 2022 (77%) were in companies without any women founders.
Building upon PitchBook’s data, our new project explores gender (dis)parity in AI-focused VC investment, investigating how the lack of diversity in both the VC and start-up ecosystem shapes AI and the innovation landscape. We found that female-founded AI companies earn 6 times less capital than their male-founded counterparts. To learn more about this, read our reports and press release.
Diversity in the Tech Industry
In collaboration with Diversio, an AI-based diversity, equity and inclusion (DEI) platform, this research explores behavioural and structural inclusion challenges faced by women in technology companies.
We are using Diversio’s database and employee public review websites’ data to analyse, and therefore tackle, diversity and inclusion pain points (e.g., pay gap, leadership diversity) within the technology industry across Canada, United States and the United Kingdom.
Research toolkit
Diversity Dashboard
We developed a tool, the ‘Diversity Dashboard’, to offer insights into gender inclusion within online tech workplaces. The Dashboard was designed for use by technology companies, running internally on top of GitHub and Slack, to measure and highlight in real-time potential differences between the treatment of men and women.
To find out more about the tool please watch the demo video below and read the information sheet.
LinkedIn scraper
We developed a new and innovative tool for scraping LinkedIn's profiles to access information regarding individual’s job, skills and educational backgrounds in the data and AI fields. For more information, please reach out via our contact form.
About the Hub
The Women in Data Science and AI’s Hub is a digital platform for women and marginalised groups interested in joining, or already involved in, the data science and AI community. Through our curation of relevant organisations, networks, guides, and educational resources, we aim to encourage increased participation and advance gender diversity within the data science and AI industry.
Turing-related content
Technology and inequality in the era of pandemic: data, power and unrest
Considering technology and inequality in the era of a pandemic
New UN commissioned report offers policy recommendations to address digital gender divide
A new paper offers key policy recommendations for using technology to advance gender equality
Researcher spotlight: Erin Young
As co-lead of the Turing’s Women in Data Science and AI project, Research Fellow Erin Young’s vital research maps the gendered career trajectories in data science and AI
The Alan Turing Institute: Social Data Science | CogX 2020
Judy Wajcman, Cosmina Dorobantu and Erin Young discuss the Turing's public policy programme work
AI UK 2022: Judy Wajcman in conversation with Dame Stephanie Shirley
Watch a fascinating conversation between Dame Stephanie Shirley and Judy Wajcman, hosted at the Turing's flagship event, AI UK
Media, press and other articles
Female-founded AI startups win just 2% of funding deals in UK
Female founders miss out on AI funds
Diversity in AI will take more than scholarships
AI Gender Bias is No Glitch in the System – UN Report
AI, bro? No! How do we stop AI being the next tech 'bro' domain?
Facebook accused of discrimination after mechanic and pilot jobs targeted at men
Organisers
Professor Judy Wajcman
Principal Investigator for Women in Data Science and AIResearchers and collaborators
Dr David Kampmann
Affiliated Research AssociatePast researchers
Laila Sprejer
Social Data Scientist
Valery Otieno
Research Assistant, Women in Data Science and AI
Julia De Miguel Velazquez
Research Assistant, Women in Data Science and AI