To shine a much-deserved and long-overdue spotlight on women researchers and others focused on AI, TechCrunch is launching an interview series highlighting notable women who have contributed to the AI revolution. As the AI boom continues, we'll be publishing several articles throughout the year, shining a spotlight on important research that often goes unrecognized. Find the other profiles here.
Readers, if you come across any names that you think we've missed and should be on the list, please email me and I'll try to add them. Some important people to know are:
Eileen Solaiman, Global Policy Head, HuggingFace Eva Meidel, Member of the European Parliament and EU AI Law Advisor Lee Tiedrich, AI Expert at the Global AI Partnership Rashida Richardson, Senior Counsel at Mastercard focusing on AI and privacy Crystal Kaufman, Research Fellow at the Institute for Decentralized AI Amba Kak, Developing policy recommendations to address AI concerns Miranda Bogen, Creating solutions to help govern AI Mutare Nkonde's non-profit works to reduce AI bias Karine Perset, Helping governments understand AI Francine Bennett, Using Data Science to Make AI More Accountable Sarah Kreps, Professor of Political Science at Cornell University Sandra Wachter, Professor of Data Ethics at the University of Oxford Clare Leibowitz, AI and media integrity expert at PAI Heidi Kraaf, Director of Safety Engineering at Trail of Bits Tara Kurofsky, CEO and Founder of Technovation Katherine Breslin, Founder and Director of Kingfisher LabsRachel Coldicutt, Georgia Congressman Darshun Kendrick, Founder of Careful Industries, Brookings Institution Fellow Chinasa T. Okoro, AI Now Institute Managing Director Sarah Myers West, Equal AI CEO Miriam Fogel, and White House Director of Science and Technology Policy Arati Prabhakar.
The gender gap in AI
In a New York Times article late last year, The Gray Lady analyzed how the current AI boom came about, citing familiar figures like Sam Altman, Elon Musk, and Larry Page. The journalism was not about what was covered, but about what was left uncovered: women.
The Times' list features 12 men, most of whom are leaders of AI or technology companies, many of whom have no training or education, formal or informal, in AI.
Contrary to what The New York Times speculated, the AI boom didn't start with Musk sitting next to Page in a Bay Area mansion — long before that, academics, regulators, ethicists, and enthusiasts were working tirelessly in relative obscurity to build the foundations of today's AI and generative AI systems.
Elaine Rich, a former University of Texas at Austin computer scientist and now retired, published one of the first textbooks on AI in 1983 and later became director of a corporate AI lab in 1988. Harvard professor Cynthia Dwork made waves in the areas of AI fairness, differential privacy, and distributed computing decades ago. And Cynthia Breazeale, a roboticist and professor at MIT and co-founder of robotics startup Jibo, worked on Kismet, one of the earliest “social robots,” in the late 1990s and early 2000s.
Despite the many ways in which women have advanced AI technology, they make up a small percentage of the global AI workforce: Just 16% of tenured faculty with an AI focus are women, according to a 2021 Stanford University study. In another study published the same year by the World Economic Forum, co-authors found that just 26% of analytics- and AI-related roles are held by women.
The even worse news is that the gender gap in AI is widening, not narrowing.
Nesta, the UK's innovation agency for social good, concluded in a 2019 analysis that the percentage of AI academic papers with at least one female co-author has not improved since the 1990s. As of 2019, only 13.8% of AI research papers on Arxiv.org, a repository of preprint scientific papers, had women as author or co-authors, a number that has been steadily declining over the past decade.
Reasons for the disparity
The reasons for this disparity are many, but a Deloitte survey of women in AI highlights some of the more salient (and obvious) reasons, including perceptions from male colleagues and discrimination for not fitting into the male-dominated mold that has entrenched in the AI industry.
It starts in college: 78% of women responding to a Deloitte survey said they didn't have the opportunity to take part in an AI or machine learning internship during their undergraduate years. More than half (58%) said they left at least one employer because they were treated differently than men and women, and 73% considered leaving the tech industry altogether because of pay disparities and difficulties in career advancement.
The lack of women is having a negative impact on the AI field.
Nesta's analysis found that women are more likely than men to consider the social, ethical and political implications of AI work, which is unsurprising given that women live in a world where they are marginalized because of their gender, where products on the market are designed for men, and where women with children are often expected to balance work with their role as primary caregivers.
With any luck, TechCrunch's small contribution — a series highlighting women in AI — will help steer things in the right direction, but it's clear there's still a lot of work to be done.
Our women have many suggestions for those who want to grow and advance the AI field for the better. But the common thread throughout is strong leadership, commitment, and leading by example. Organizations can make a difference by instituting policies (hiring, education, etc.) that favor women already in the AI industry and those looking to enter the industry. And decision-makers in positions of power can use their power to drive a more diverse and supportive workplace for women.
Change doesn't happen overnight, but every revolution starts with small steps.