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To give focus on artificial intelligence From academic women and others who have a well-deserved — and overdue — time in the spotlight, TechCrunch is launching a series of interviews focusing on the remarkable women who have contributed to the AI revolution. We will publish many articles throughout the year as AI continues to flourish, highlighting key works that often go unrecognized. Read more profiles here.
As a reader, if you see a name we’ve missed that you feel should be on the list, please email us and we will endeavor to add it. Here are some key people you should know:
The gender gap in artificial intelligence
In the New York Times piece Late last year, The Gray Lady highlighted how the current boom in artificial intelligence emerged, highlighting several of the usual suspects like Sam Altman, Elon Musk, and Larry Page. The press went viral—not because of what was published, but instead because of what it failed to mention: women.
The Times’ list included 12 men, most of whom were leaders of artificial intelligence or technology companies. Many of them have received no training or education, formal or otherwise, in the field of artificial intelligence.
Contrary to the Times’ suggestion, the AI craze didn’t start with Musk sitting next to Page in a mansion in the Gulf. It began long before that, with academics, regulators, ethicists, and hobbyists working tirelessly in relative obscurity to build the foundations of the AI and GenAI systems we have today.
Elaine Rich, a retired computer scientist who previously worked at the University of Texas at Austin, published one of the first textbooks on artificial intelligence in 1983, and later became director of the company’s AI lab in 1988. Cynthia Durk, a professor at Harvard , a buzz over decades. Previously in the areas of AI fairness, differential privacy, and distributed computing. Cynthia Breazeale, a roboticist, professor at MIT and co-founder of Jibo, a robotics startup, developed one of the earliest “social robots,” Kismet, in the late 1990s and early 2000s.
Despite the many ways women have advanced AI technology, they make up a small segment of the global AI workforce. According to Stanford 2021 Stadyonly 16% of tenure-track faculty who focus on AI are women. In a separate study Released by the World Economic Forum in the same year, the co-authors found that women held only 26% of analytics and AI-related positions.
In worse news, the gender gap in AI is widening — not narrowing.
Conducted by Nesta, the UK’s innovation agency for social good 2019 analysis It concluded that the proportion of AI-related 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, with numbers declining steadily over the previous decade.
Reasons for the disparity
The reasons for the disparity are many. but Deloitte Survey of Women in AI It highlights a few of the most notable (and obvious) issues, including judgment from male peers and discrimination as a result of not fitting into established male-dominated stereotypes in AI.
It starts in college: 78% of women who participated in the Deloitte survey said they did not have the opportunity to train in artificial intelligence or machine learning while they were college students. More than half (58%) said they ended up leaving at least one employer because of the way men and women are treated differently, while 73% considered leaving the tech industry altogether due to unequal pay and an inability to advance in their lives. Professional.
The lack of women is hurting the field of artificial intelligence.
Nesta’s analysis found that women are more likely than men to consider the social, ethical and political implications of their work in AI – which is not surprising given that women live in a world where they are undervalued based on their gender, and the products of the world. 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, a modest contribution from TechCrunch — a series about women excelling in AI — will help move the needle in the right direction. But there is clearly a lot of work to be done.
The women we meet share many suggestions for those who want to grow the field of AI for the better. But there is a common thread throughout: strong mentorship, commitment and leadership by example. Organizations can influence change by enacting policies – employment, education, or otherwise – that uplift women who are already in the AI industry or looking to break into it. Decision makers in positions of power can exercise this power to push for more diverse and supportive workplaces for women.
Change will not happen overnight. But every revolution begins with a small step.
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