Women Making a Difference in AI
In the midst of the AI revolution, it is crucial to recognize the remarkable women who have made significant contributions to the field. To shed light on their achievements, TechCrunch is launching a series of interviews that will highlight the work of these talented individuals. As the AI boom continues, TechCrunch aims to bring attention to the women who have often gone unrecognized in this field.
The Gender Gap in AI
Last year, The New York Times published an article about the current boom in AI, featuring the usual suspects such as Sam Altman, Elon Musk, and Larry Page. However, what caught people’s attention was not who was mentioned but rather who was missing from the list: women. The Times’ list consisted of 12 men, most of whom were leaders in AI or tech companies. Surprisingly, many of them had no formal education or training in AI.
Contrary to the Times’ suggestion, the AI craze did not start with these men. It began long before, with academics, regulators, ethicists, and hobbyists working tirelessly behind the scenes to lay the groundwork for the AI systems we have today. Women like Elaine Rich, a retired computer scientist and author of one of the first AI textbooks, and Harvard professor Cynthia Dwork, who made significant contributions to AI fairness and privacy, have played pivotal roles in shaping the field. Cynthia Breazeal, a roboticist and MIT professor, developed one of the earliest “social robots” back in the late ’90s.
Despite these accomplishments, women still make up a small fraction of the global AI workforce. According to a 2021 Stanford study, only 16% of tenure-track faculty focused on AI are women. Another study by the World Economic Forum found that women hold just 26% of analytics-related and AI positions. What’s even more concerning is that the gender gap in AI is widening rather than narrowing.
Reasons for Disparity
Numerous factors contribute to this gender gap. A Deloitte survey of women in AI highlights some of the more prominent reasons, including judgment from male peers and discrimination for not fitting into established male-dominated molds in AI. The survey revealed that 78% of women did not have the opportunity to intern in AI or machine learning during their undergraduate studies. Over half of the respondents (58%) said they left at least one employer due to unequal treatment between men and women, while 73% considered leaving the tech industry altogether because of unequal pay and limited career advancement opportunities.
The Impact of the Gender Gap
The lack of women in AI is detrimental to the field. Nesta, the UK’s innovation agency, conducted an analysis in 2019 that showed no improvement in the proportion of AI academic papers co-authored by women since the 1990s. Only 13.8% of AI research papers on Arxiv.org were authored or co-authored by women in 2019, with the numbers steadily declining over the past decade. This disparity is a missed opportunity as women bring unique perspectives and considerations to the development of AI, particularly in terms of societal, ethical, and political implications.
Moving Forward
TechCrunch’s series on accomplished women in AI aims to contribute to the efforts to bridge this gender gap. While it may be a small step, it is an important one. The women profiled in this series offer valuable suggestions for those looking to grow and evolve the AI field. One common theme that emerges is the importance of strong mentorship, commitment, and leading by example. Organizations can drive change by implementing policies that elevate women already in the AI industry or those looking to enter it. Decision-makers in positions of power can use their influence to create more diverse and supportive workplaces for women.
Conclusion
The AI revolution should not overshadow the contributions of women who have played instrumental roles in shaping the field. TechCrunch’s series on remarkable women in AI aims to give these individuals the recognition they deserve. However, it is clear that there is still much work to be done to address the gender gap in AI. By taking small steps and implementing changes at various levels within the industry, we can move towards a more inclusive and diverse AI community.