To give AI-focused women scholars and professionals their overdue recognition, we’re launching a series of interviews spotlighting outstanding women who’ve contributed significantly to the AI revolution. Throughout the year, as the AI boom continues, we’ll highlight key yet often unrecognized work. Read more profiles here.
If you know of someone we’ve missed and should be on the list, please email me, and I’ll strive to include them. Here are some key individuals you should be aware of:
- Irene Solaiman, head of global policy at Hugging Face
- Eva Maydell, member of the European Parliament and EU AI Act adviser
- Lee Tiedrich, AI expert at the Global Partnership on AI
- Rashida Richardson, senior counsel at Mastercard focusing on AI and privacy
- Krystal Kauffman, research fellow at the Distributed AI Research Institute
- Amba Kak, creator of policy recommendations to address AI concerns
- Miranda Bogen, developer of solutions to help govern AI
- Mutale Nkonde, working through her nonprofit to reduce AI bias
- Karine Perset, aiding governments in understanding AI
- Francine Bennett, using data science to make AI more responsible
- Sarah Kreps, professor of government at Cornell
- Sandra Wachter, professor of data ethics at Oxford
- Claire Leibowicz, AI and media integrity expert at PAI
- Heidy Khlaaf, safety engineering director at Trail of Bits
- Tara Chklovski, CEO and founder of Technovation
- Catherine Breslin, founder and director of Kingfisher Labs
- Rachel Coldicutt, founder of Careful Industries
- Rep. Dar’shun Kendrick, member of the Georgia House of Representatives
- Chinasa T. Okolo, fellow at the Brookings Institution
- Sarah Myers West, managing director at the AI Now Institute
- Miriam Vogel, CEO of EqualAI
- Arati Prabhakar, director of the White House Office of Science and Technology Policy
The gender gap in AI
In a New York Times article late last year, it showcased how the AI boom began, mentioning well-known figures like Sam Altman, Elon Musk, and Larry Page. The article went viral, not for its content but for what it overlooked: women.
The Times’ list featured 12 men, mostly leaders of AI or tech companies, many without any formal or informal training in AI.
Contrary to the Times’ implication, the AI wave didn’t begin with Musk sitting next to Page in a Bay Area mansion. It started long before, with academicians, regulators, ethicists, and enthusiasts working diligently and often unnoticed to lay the groundwork for today’s AI and generative AI systems.
Elaine Rich, a retired computer scientist from the University of Texas at Austin, authored one of the first AI textbooks in 1983 and later directed a corporate AI lab in 1988. Harvard professor Cynthia Dwork made significant contributions decades ago in AI fairness, differential privacy, and distributed computing. Cynthia Breazeal, a roboticist and MIT professor, co-founded the robotics startup Jibo and developed one of the first “social robots,” Kismet, in the late ’90s and early 2000s.
Despite their many contributions, women constitute only a small fraction of the global AI workforce. According to a 2021 Stanford study, just 16% of tenure-track faculty focusing on AI are women. Another study published the same year by the World Economic Forum found that women hold only 26% of analytics-related and AI positions.
In bad news, the gender gap in AI is not closing but widening.
Nesta, the UK’s innovation agency for social good, conducted a 2019 analysis that found the proportion of AI academic papers co-authored by at least one woman hadn’t improved since the 1990s. As of 2019, only 13.8% of AI research papers on Arxiv.org, a repository for preprint scientific papers, were authored or co-authored by women, with the numbers declining over the past decade.
Reasons for disparity
The disparity can be attributed to many factors. A Deloitte survey of women in AI highlights some prominent reasons, such as judgment from male peers and discrimination for not fitting established male-dominated AI molds.
It begins in college: 78% of women in the Deloitte survey said they didn’t have the chance to intern in AI or machine learning during their undergraduate studies. Over half (58%) left at least one employer due to differing treatment of men and women, while 73% considered leaving the tech industry altogether because of unequal pay and limited career advancement opportunities.
The scarcity of women is detrimental to the AI field.
Nesta’s analysis discovered that women are more likely than men to consider societal, ethical, and political implications in their AI work — not surprising, given that women live in a world where they face gender-based belittlement, market products are designed for men, and women with children often balance work with being primary caregivers.
Hopefully, our initiative — a series on accomplished women in AI — will help make progress. However, there’s still much work to be done.
The women we profile offer many suggestions to improve and advance the AI field. A common theme is strong mentorship, commitment, and leading by example. Organizations can drive change by implementing policies — in hiring, education, or other areas — that uplift women in, or aspiring to join, the AI industry. Those in power can use their influence to create more diverse and supportive workplaces for women.
Change won’t come overnight. But every revolution starts with a small step.
