To give female academics and others working on AI their deserved—and long overdue—time within the highlight, TechCrunch is launching an interview series with notable women who’ve contributed to the AI revolution. As the AI boom continues, we'll be publishing several posts all year long highlighting necessary work that always goes unnoticed. Find more profiles here.
If you as a reader see a reputation we missed that you’re thinking that must be on the list, please email me and I’ll try so as to add it. Here are some necessary people you need to know:
- Irene Solaiman, Head of Global Policy at Hugging Face
- Eva Maydell, Member of the European Parliament and Advisor to the EU AI Act
- Lee Tiedrich, AI expert on the Global Partnership on AI
- Rashida Richardson, Senior Counsel at Mastercard specializing in AI and data protection
- Krystal Kauffman, research associate on the Distributed AI Research Institute
- Amba Kak makes policy recommendations to handle AI problems
- Miranda Bogen develops solutions for controlling AI
- Mutale Nkonde's nonprofit is working to make AI less biased
- Karine Perset helps governments understand AI
- Francine Bennett uses data science to make AI more responsible
- Sarah Kreps, Professor of Government at Cornell
- Sandra Wachter, Professor of Data Ethics at Oxford
- Claire Leibowicz, AI and media integrity expert at PAI
- Heidy Khlaaf, Head of Security Technology at Trail of Bits
- Tara Chklovski, CEO and Founder of Technovation
- Catherine Breslin, Founder and Director of Kingfisher Labs
- Rachel Coldicutt, Founder of Careful Industries
- Representative Dar'shun Kendrick, Member of the Georgia House of Representatives
- Chinasa T. Okolo, Fellow on the Brookings Institution
- Sarah Myers West, Executive Director of the AI Now Institute
- Miriam Vogel, CEO of EqualAI
- Arati Prabhakar, Director of the White House Office of Science and Technology Policy
The gender gap in AI
In a New York Times Piece Late last yr, the Gray Lady analyzed how the present boom in artificial intelligence got here about—highlighting lots of the usual suspects, like Sam Altman, Elon Musk, and Larry Page. The article went viral—not due to what was reported, but due to what was not mentioned: women.
The Times' list included 12 men, most of them executives of AI or technology firms, a lot of whom had no training or education in AI, formal or otherwise.
Contrary to what the Times suggests, the AI hype didn't start with Musk sitting next to Page in a Bayfront mansion. It began much earlier, when academics, regulators, ethicists and amateur experts worked tirelessly and in relative obscurity to put the groundwork for the AI and generative AI systems now we have today.
Elaine Rich, a retired computer scientist formerly of the University of Texas at Austin, published certainly one of the primary textbooks on AI in 1983 and have become head of a company AI lab in 1988. Harvard professor Cynthia Dwork made waves in AI fairness, differential privacy, and distributed computing a long time ago. And Cynthia Breazeal, a roboticist and professor at MIT and co-founder of robotics startup Jibo, worked within the late Nineties and early 2000s to develop certainly one of the primary “social robots,” Kismet.
Although women have advanced AI technology in some ways, they represent only a tiny portion of the worldwide AI workforce. According to a 2021 Stanford University study, studyOnly 16% of tenured professors specializing in AI are female. In a separate study The co-authors present in a study published by the World Economic Forum the identical yr that only 26% of analytics and AI positions are held by women.
The worse news is that the gender gap in AI is widening – not narrowing.
Nesta, the UK’s innovation agency for social good, conducted an evaluation from 2019 It found that the proportion of AI-related scientific papers co-authored by at the least one woman has not improved for the reason that Nineties. In 2019, only 13.8% of AI research papers on Arxiv.org, a repository of scientific preprints, were authored or co-authored by women, with the number steadily declining over the past decade.
Reasons for inequality
The reasons for this inequality are manifold. Deloitte survey on women in AI highlights among the most glaring (and obvious), including judgement by male colleagues and discrimination based on not fitting into established, male-dominated molds in AI.
It starts in college: 78% of girls who responded to the Deloitte survey said they didn't have the chance to intern in AI or machine learning while in college. Over half (58%) said they left at the least one employer due to differences in treatment between men and girls. 73% considered leaving the tech industry altogether attributable to unequal pay and an absence of opportunities for advancement.
The lack of girls is damaging the AI field.
Nesta's evaluation found that girls are more likely than men to contemplate societal, ethical and political implications when working on AI. This is just not surprising considering that girls live in a world where they’re denigrated due to their gender, the products in the marketplace are designed for men, and girls with children are sometimes expected to balance their work with their role as primary caregivers.
With any luck, TechCrunch's modest contribution – a series on successful women in AI – will help move things in the suitable direction. But there may be clearly still a whole lot of work to be done.
The women we profile offer many suggestions for those trying to grow and evolve the AI field for the higher. But one common thread runs through all of them: strong mentorship, engagement, and role modeling. Companies can create change by enacting policies—in hiring, training, or otherwise—that promote women already within the AI industry or who need to enter it. And decision-makers in positions of power can use that power to push for more diverse and supportive workplaces for girls.
Changes don't occur overnight. But every revolution begins with a small step.
