To highlight the significant contributions of women in the field of AI, TechCrunch is launching a series of interviews focusing on outstanding women who have played a crucial role in the AI revolution. This initiative aims to shine a light on their achievements that have often been overlooked. The series will feature multiple profiles throughout the year to coincide with the continuous growth of AI, showcasing pivotal work that deserves recognition. For more profiles, please visit the provided link.
If you believe there are notable individuals we have missed and should include in our list, kindly reach out via email, and we will strive to incorporate them. Here are some key figures you should be familiar with:
Addressing the Gender Disparity in AI
In a recent article by the New York Times, the publication dissected the current AI boom, highlighting prominent figures like Sam Altman, Elon Musk, and Larry Page. However, what garnered attention was not the content of the piece but rather its glaring omission of women.
The Times’ compilation featured 12 men, many of whom are leaders in AI or technology companies. Surprisingly, most lacked any formal training or education in AI.
Contrary to the Times’ narrative, the roots of the AI frenzy extend far beyond Musk and Page’s interactions in a Bay Area mansion. It traces back to the diligent efforts of academics, regulators, ethicists, and enthusiasts who toiled in the shadows, laying the groundwork for the AI and GenAI systems we rely on today.
Elaine Rich, a retired computer scientist from the University of Texas at Austin, authored one of the initial AI textbooks in 1983 and later led a corporate AI lab in 1988. Cynthia Dwork, a Harvard professor, made significant strides in AI fairness, differential privacy, and distributed computing decades ago. Additionally, Cynthia Breazeal, a roboticist and MIT professor, along with being the co-founder of Jibo, a robotics startup, played a pivotal role in developing one of the earliest “social robots,” Kismet, in the late ‘90s and early 2000s.
Despite the pivotal contributions of women to AI technology, they represent only a small fraction of the global AI workforce. According to a Stanford study in 2021, a mere 16% of tenure-track faculty specializing in AI are women. Another study from the World Economic Forum in the same year revealed that women hold only 26% of positions related to analytics and AI.
Furthermore, the gender gap in AI is widening rather than narrowing.
A 2019 analysis by Nesta, the U.K.’s innovation agency, concluded that the percentage of AI academic papers co-authored by women has stagnated since the 1990s. As of 2019, a mere 13.8% of the AI research papers on Arxiv.org had female authors or co-authors, with this figure steadily declining over the past decade.
Factors Contributing to the Disparity
Various factors contribute to this gender gap. A survey by Deloitte focusing on women in AI highlighted several prominent reasons, including biased judgments from male colleagues and discrimination stemming from not conforming to the established male-centric norms within the AI field.
The disparity begins during college, with 78% of women surveyed by Deloitte indicating they did not have the opportunity to intern in AI or machine learning during their undergraduate studies. Over half (58%) reported leaving at least one employer due to differential treatment based on gender, while 73% contemplated exiting the tech industry altogether due to unequal compensation and limited career progression opportunities.
The underrepresentation of women is detrimentally impacting the AI sector.
Nesta’s analysis revealed that women are more inclined than men to consider the societal, ethical, and political implications of their AI work. This inclination is unsurprising given the challenges women face, including gender-based belittlement, product designs predominantly tailored for men, and the expectation for women with children to balance work responsibilities with their primary caregiving role.
With the launch of TechCrunch’s series focusing on accomplished women in AI, there is hope for progress in the right direction. However, it is evident that substantial efforts lie ahead.
The women featured in our profiles offer valuable insights for those seeking to enhance and advance the AI field. A recurring theme among their suggestions is the significance of robust mentorship, unwavering commitment, and leading by example. Organizations can drive change by implementing policies that support and elevate women in the AI industry, whether already established or aspiring to enter the field. Moreover, influential decision-makers can utilize their authority to advocate for more inclusive and supportive work environments for women.
While change may not occur overnight, every transformation commences with a single step.
