Highlighting the Remarkable Contributions of Women in AI
To give AI-focused women academics and others their well-deserved — and overdue — time in the spotlight, TechCrunch is launching a series of interviews focusing on remarkable women who’ve contributed to the AI revolution. We’ll publish 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 a name we’ve missed and feel should be on the list, please let us know and we’ll seek to add them. Here’s some key people you should know:
In a New York Times piece late last year, the Gray Lady revealed how the current boom in AI unfolded — highlighting many of the usual suspects like Sam Altman, Elon Musk and Larry Page. The journalism went viral – not for what was reported, but instead for what it failed to mention: women.
The Times’ list featured 12 men — most of them leaders of AI or tech companies. Interestingly, many had no training or education, formal or otherwise, in AI.
Despite what the Times might suggest, the fascination with AI didn’t begin with Musk and Page holding a chat in a plush Bay Area mansion. Rather, it was the result of countless hours put forth by researchers, policy makers, ethicists, and enthusiasts laboring in somewhat anonymous to lay out the groundwork for present day AI and GenAI systems.
Elaine Rich, an emeritus professor of computer science who was previously with the University of Texas at Austin, is known for composing one of the earliest academic texts on AI in 1983. She subsequently became the lead of a company’s AI lab in 1988. Cynthia Dwork, a Harvard faculty member, made considerable strides a few decades ago in AI fairness, differential privacy, and distributed computing. Additionally, Cynthia Breazeal, a MIT professor and roboticist, also the co-founder of Jibo, a robotics startup, pioneered one of the inaugural “social robots,” named Kismet, in the late 1990s and the early 2000s.
Despite the substantial advancements in AI technology by women, they represent a minute fraction of the worldwide AI workforce. A 2021 research conducted by Stanford revealed that only 16% of tenured faculty members focusing on AI are female. In another study published in the same year by the World Economic Forum, the authors noted that women occupy a mere 26% of roles related to analytics and AI.
Alarmingly, rather than closing, the gender gap in the AI field is expanding.
Nesta, the U.K.’s organisation focused on innovations for societal benefits, carried out a study in 2019 revealing that the percentage of AI academic articles featuring at least one female co-author has not improved since the 1990s. As per the 2019 records, a mere 13.8% of all AI research articles on Arxiv.org, a platform for preliminary scientific articles, had been authored or co-authored by women, showing a steady decline over the prior decade.
The disparity is resultant of numerous factors. However, a Deloitte survey focused on women in AI pointed out a few prominent and apparent reasons including bias from male colleagues, and prejudice due to non-conformance to traditional male-dominated norms in AI.
Such disparity originates in college: 78% of female respondents in the Deloitte survey indicated that they were not offered an opportunity to intern in AI or machine learning during their undergraduate studies. More than half (58%) reported having left an employer due to differential treatment of men and women, and as many as 73% contemplated leaving the tech industry entirely due to pay inequality and limitations in career advancement.
This absence of women is detrimental to the AI industry.
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