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.
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:
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
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.
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.
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.
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.
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.
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.