To give female academics and others focused on AI their well-deserved — and overdue — time, TechCrunch is launching a series of interviews focusing on remarkable women who have AI has contributed to the revolution. We'll be publishing several pieces throughout the year as the AI boom continues, highlighting key work that often goes unrecognized. Read more profiles here.
As a reader, if you see any names that we have missed and feel should be on the list, please email me and I will try to add them. Here are some important ones you should know:
- Irene Sulaiman, head of global policy at Hedging Face
- Eva Maydell, Member of the European Parliament and Advisor on the EU AI Act
- Lee Tiedrich, AI expert at the Global Partnership on AI
- Rashida Richardson, Senior Counsel at MasterCard focusing on AI and Privacy
- Crystal Kaufman, Research Fellow at the Distributed AI Research Institute
- Ambacock develops policy recommendations to address AI concerns.
- Miranda Bogan is developing solutions to help drive AI.
- Mutale Nkonde's nonprofit is working to make AI less biased.
- Karine Perset helps governments understand AI.
- Francine Bennett uses data science to make AI more responsive.
- Sarah Krepps, professor of government at Cornell
- Sandra Wachter, Professor of Data Ethics at Oxford
- Claire Leibowicz, AI and Media Integrity Specialist at PAI
- Heidi Khalif, Safety Engineering Director at Trail of Bits
- Tara Chklovski, CEO and Founder of Technovation
- Kathryn Breslin, founder and director of Kingfisher Labs
- Rachel Coldicutt, founder of Careful Industries
- Representative Darshawn Kendrick, a member of the Georgia House of Representatives
Gender differences in AI
In a New York Times piece late last year, Gray Lady broke down how the current boom in AI came about — highlighting many of the usual suspects like Sam Altman, Elon Musk and Larry Page. Journalism went viral — not for what was reported, but for what was not mentioned: women.
The Times list includes 12 men — most of whom are leaders of AI or tech companies. Many had no training or education, formal or otherwise, in AI.
Contrary to what the Times suggests, the AI obsession didn't start with Musk sitting next to Page in a mansion in the Bay. It began long before that, with academics, regulators, ethicists and hobbyists working tirelessly in relative obscurity to build the foundations of the AI and generative AI systems we have today.
Elaine Rich, a retired computer scientist formerly at the University of Texas at Austin, published one of the first textbooks on AI in 1983, and later became director of a corporate AI lab in 1988. Harvard professor Cynthia DeWerk pioneered decades ago in the fields of AI fairness, differential privacy and distributed computing. And Cynthia Breazeale, a roboticist and professor at MIT and co-founder of Jibo, a robotics startup, worked in the late '90s and early 2000s to develop the earliest known “social robots,” the Kismets.
Despite the many ways in which women have advanced AI tech, they make up a small portion of the global AI workforce. According to a 2021 Stanford study, only 16% of faculty focusing on AI are women. In a separate study released the same year by the World Economic Forum, co-authors found that women hold only 26 percent of analytics and AI positions.
In worse news, the gender gap in AI is widening — not narrowing.
A 2019 analysis by Nesta, the UK innovation agency for social good, concluded that the proportion of AI academic papers co-authored by at least one woman has not improved since the 1990s. As of 2019, only 13.8% of AI research papers on Arxiv.org, a repository of pre-print scientific papers, were authored or co-authored by women, a number that has been steadily decreasing over the past decade. .
Reasons for disparity
There are many reasons for the disparity. But Deloitte's survey of women in AI highlights something more salient (and obvious), including judgment from male colleagues and discrimination as a result of not fitting into male-dominated molds in AI.
It starts in college: 78% of women responding to a Deloitte survey said they didn't have the opportunity to intern in AI or machine learning when they were undergraduates. More than half (58%) said they left at least one employer because men and women were treated differently, while 73% cited unequal pay and failure to advance in their careers. Considered leaving the tech industry altogether.
A lack of women is hurting the AI field.
Nesta's analysis found that women are more likely than men to consider the social, ethical and political implications of their work on AI – which is not surprising considering women live in a world where They are humiliated on the basis of their gender, products. The market is designed for men and women with children who are often expected to balance work with their role as primary caregivers.
With any luck, TechCrunch's humble contribution—a series on successful women in AI—will help move the needle in the right direction. But clearly much work remains to be done.
The women we profile share many tips for those who want to grow and develop the AI field for the better. But a common thread runs throughout: strong leadership, commitment and leading by example. Organizations can affect change by creating policies — employment, education or otherwise — that favor women already in, or looking to enter, the AI industry. And decision makers in positions of power can use that power to push for more diverse, supportive workplaces for women.
Change will not happen overnight. But every revolution starts with a small step.