How Women in AI are Creating an Impact

To shine a light on the incredible contributions of women in the world of artificial intelligence, TechCrunch is launching a series of interviews featuring the remarkable women driving the AI revolution. As the AI boom continues, it is vital that we recognize and celebrate the work of these often overlooked individuals. Learn more about these inspiring women here.

If there are any names we have missed that you feel should be included, please email us and we will do our best to feature them. Here are just a few of the many incredible women in AI that you should know:

The Gender Gap in AI

In a recent article, the New York Times discussed the current AI boom, highlighting some of the key players such as Sam Altman, Elon Musk, and Larry Page. However, the article went viral for what it failed to mention – women.

The Times’ list featured 12 men, most of whom are leaders in the AI and tech industries. Many of these individuals have little to no formal education or training in AI.

Contrary to the Times’ suggestion, the AI craze did not begin with Musk and Page sitting together at a mansion in the Bay Area. It actually started decades ago, thanks to the tireless work of academics, regulators, ethicists, and hobbyists. These individuals laid the foundations for the AI and GenAI systems we have today, often in relative obscurity.

Elaine Rich, a retired computer scientist from the University of Texas at Austin, published one of the first textbooks on AI in 1983 and later became a director at a corporate AI lab in 1988. Harvard professor Cynthia Dwork has been making waves in AI fairness, differential privacy, and distributed computing for decades. And Cynthia Breazeal, a roboticist and professor at MIT, co-founded Jibo – a robotics startup – and helped develop one of the earliest “social robots,” Kismet, in the late 1990s and early 2000s.

Despite the significant contributions of women in AI, they make up only a small fraction of the global AI workforce. According to a 2021 Stanford study, just 16% of tenure-track faculty in AI are women. Another study from the World Economic Forum found that women hold only 26% of positions related to analytics and AI.

Even more concerning, the gender gap in AI is actually widening, not narrowing.

In a 2019 analysis, the U.K.’s innovation agency Nesta found that the proportion of AI research papers co-authored by women has not improved since the 1990s. As of 2019, only 13.8% of AI research papers on Arxiv.org, a repository for scientific papers, were authored or co-authored by women. This number has steadily decreased over the last decade.

Reasons for Disparity

There are numerous reasons for this disparity. A survey by Deloitte revealed some of the more prominent and obvious ones, including judgment from male peers and discrimination for not fitting into the male-dominated mold in AI.

This disparity starts in college – 78% of women surveyed by Deloitte did not have the opportunity to intern in AI or machine learning during their undergraduate studies. More than half (58%) left at least one employer due to unequal treatment between men and women, and 73% considered leaving the tech industry altogether due to unequal pay and limited opportunities for career advancement.

The lack of women in AI is detrimental to the field as a whole. Nesta’s analysis found that women are more likely than men to consider the societal, ethical, and political implications of AI in their work. This is not surprising considering the challenges that women face in a world where they are often belittled based on their gender, products are designed primarily for men, and women with children struggle to balance work and family responsibilities.

TechCrunch’s series featuring accomplished women in AI is a small effort to help move the needle in the right direction. But there is still much work to be done.

Driving Change

The women we have profiled have shared valuable insights for those looking to improve and evolve the field of AI. One recurring theme is the importance of strong mentorship, commitment, and leading by example.

Organizations can make a difference by implementing policies that promote the hiring and education of women in the AI industry. And those in positions of power can use their influence to push for more diverse and supportive workplaces for women.

Change will not happen overnight, but every revolution begins with a small step.