Women in artificial intelligence are making a difference

Artificial Intelligence at the Center In an effort to give female academics and others a deserved (and overdue) spotlight, TechCrunch has launched a series of interviews focusing on the remarkable women contributing to the AI ​​revolution. As the AI ​​craze continues, we will publish multiple articles throughout the year highlighting critical work that is often overlooked. Read more profiles here.

As a reader, if you see a name we’ve left out and think should be on the list, please send us an email and we’ll do our best to add them. Here are some key people you should know:

The gender gap in artificial intelligence

In a New York Times article late last year, Ms. Gray analyzed in detail how the current craze for artificial intelligence came to be, highlighting the likes of Sam Altman, Elon Musk and Larry Page, among many others. The usual suspects. The news story went viral — not because of what it said, but because of what it didn’t mention: women.

There are 12 men on the Times’ list, most of whom are leaders of artificial intelligence or technology companies. Many people have no formal or other training or education in artificial intelligence.

Contrary to what the New York Times claimed, the artificial intelligence craze didn’t start with Musk sitting next to Page in his Bayfront mansion. Long before that, academics, regulators, ethicists, and enthusiasts were working tirelessly in relative obscurity to lay the foundation for the artificial intelligence and GenAI systems we have today.

Elaine Rich is a retired computer scientist who worked at the University of Texas at Austin. She published one of the earliest artificial intelligence textbooks in 1983 and later became the director of a corporate artificial intelligence laboratory in 1988. Harvard professor Cynthia Dwork has been making waves in the fields of AI fairness, differential privacy and decentralized computing for decades. Cynthia Breazeal, a roboticist and professor at MIT and co-founder of robotics startup Jibo, spent the late 1990s and early 2000s developing one of the earliest “social robots,” Kismet.

Although women possess advanced AI technologies in many aspects, they make up only a small portion of the global AI workforce. According to a 2021 Stanford University study, only 16% of tenured professors focusing on artificial intelligence are women. In another study released by the World Economic Forum that same year, co-authors found that women held only 26% of analytics-related and artificial intelligence positions.

The even worse news is that the gender gap in artificial intelligence is growing, not closing.

A 2019 analysis by Nesta, the UK’s social good innovation agency, concluded that the proportion of academic papers on artificial intelligence co-authored by at least one woman has not increased since the 1990s. As of 2019, only 13.8% of AI research papers on the preprint scientific paper repository Arxiv.org were authored or co-authored by women, a number that has declined steadily over the past decade.

Reason for difference

There are many reasons for this difference. But a Deloitte survey of women in AI highlights some of the more salient (and obvious) issues, including judgment from male peers and discrimination that results from not fitting into the established male-dominated mold of the AI ​​field.

It starts in college: 78% of women surveyed by Deloitte said they had no opportunity to intern in artificial intelligence or machine learning as an undergraduate. More than half (58%) said they ended up leaving at least one employer due to disparate treatment of men and women, while 73% considered leaving the tech industry entirely due to pay inequality and the inability to advance in their careers.

The lack of women is hurting the field of artificial intelligence.

Nesta’s analysis found that women are more likely than men to consider social, ethical and political implications in their AI work—not surprising considering that women live in a world where they are devalued for their gender and products. The market is designed for men and women with children, who often want to balance work with the role of primary caregiver.

With any luck, TechCrunch’s modest contribution—a series of articles about accomplished women in artificial intelligence—will help nudge the needle in the right direction. But clearly there is still much work to be done.

The women we profile have plenty of advice for those who want the field of artificial intelligence to thrive. But the common thread throughout is: strong mentoring, commitment and leading by example. Organizations can influence change by developing policies (recruitment, education, or other means) to advance women who are already in or wish to enter the AI ​​industry. Policymakers in positions of power can use that power to push for more diverse and supportive workplaces for women.

Change doesn’t happen overnight. But every revolution starts with a small step.