To focus on AI Women academics and others who deserved—and overdue—time in the spotlight, TechCrunch is launching a series of interviews focusing on notable women who have contributed to the AI revolution. We’ll be publishing several pieces throughout the year as the AI boom continues, highlighting essential work that often goes unrecognized. Read more profiles here.
As a reader, if you see a name we missed and think should be on the list, please email us and we’ll try to add it. Here are some key people to know:
The gender gap in artificial intelligence
In a New York Times newspaper piece Late last year, The Gray Lady broke down how the current boom in artificial intelligence was made — singling out many of the usual suspects like Sam Altman, Elon Musk and Larry Page. The journalism went viral – not for what it reported, but for what it failed to report: women.
The Times list included 12 men — most of whom were leaders of artificial intelligence or technology companies. Many had no training or education, formal or otherwise, in artificial intelligence.
Contrary to what the Times suggests, the AI craze didn’t start with Musk sitting next to Page in a mansion on the Bay. It started long before that, with academics, regulators, ethicists and hobbyists working tirelessly in relative obscurity to build the foundations for the AI and GenAI 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 artificial intelligence in 1983 and later became director of a corporate artificial intelligence lab in 1988. Harvard professor Cynthia Dwork made the waves decades ago in the fields of artificial intelligence fairness, differential privacy and distributed computing. And Cynthia Breazeal, a roboticist and professor at MIT and co-founder of the robotics startup Jibo, worked to develop one of the first “social robots,” Kismet, in the late 90s and early 2000s.
Despite the many ways in which women have advanced AI technology, they make up a small part of the global AI workforce. According to a 2021 Stanford studyjust 16% of AI-focused faculty are women. In a separate study released the same year by the World Economic Forum, the authors find that women hold only 26% of positions related to analytics and artificial intelligence.
In worse news, the gender gap in AI is widening — not closing.
Nesta, the UK’s innovation agency for social good, conducted 2019 analysis which concluded that the percentage of academic AI papers authored by at least one woman had not improved since the 1990s. As of 2019, just 13.8% of AI research papers on Arxiv.org, a repository for preprinted scientific papers papers, were authored or co-authored by women, with numbers steadily declining over the previous decade.
Reasons for inequality
The reasons for inequality are many. But a Deloitte survey on women in artificial intelligence highlights some of the more prominent (and obvious), including male peer judgment and discrimination as a result of not fitting into established male-dominated molds in AI.
It starts in college: 78% of women surveyed by Deloitte said they didn’t have an opportunity to practice in artificial intelligence or machine learning while an undergraduate. More than half (58%) said they ended up leaving at least one employer because of how men and women were treated differently, while 73% considered leaving the tech industry altogether because of unequal pay and an inability to advance their careers.
A lack of women hurts 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 on artificial intelligence – which is not surprising given that women live in a world where they are undervalued based on their gender. The market is designed for men, and women with children are often expected to balance work with their role as primary caregivers.
With any luck, TechCrunch’s humble contribution—a series about successful women in AI—will help move the needle in the right direction. But there is clearly a lot of work to be done.
Our women designers share many suggestions for those who wish to grow and evolve the field of artificial intelligence for the better. But there is a common thread: strong leadership, commitment and leading by example. Organizations can affect change by enacting policies—hiring, training, or otherwise—that elevate women already in or looking to break into 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.
