rtificial Intelligence has immense potential to positively transform the world but it has a gender–diversity problem. Empowering women in AI is not just a moral imperative but a strategic necessity. By upskilling women and increasing their representation in AI leadership, we can create a more inclusive, innovative, and productive future.
Women represent roughly 47% of the UK and U.S. labor force. Yet they make up just 16% of the tenure–track faculty focused on AI globally and only 26% of data and AI positions in the workforce. The lack of gender diversity in AI research has far–reaching consequences.
Why does the lack of gender diversity matter?
AI failures disproportionately impact women and those from marginalized backgrounds. It perpetuates existing biases and reinforces societal inequalities. For example, Amazon’s AI–driven recruitment system was found to discriminate against women for technical jobs. Beyond missed opportunities, this imbalance impedes progress on economic, cultural and technological fronts.
- Economic Impact: Diverse teams drive innovation and economic prosperity. When capable women are excluded from AI, we miss out on fresh perspectives, novel ideas, and potential breakthroughs. McKinsey research shows that companies whose workforces consist of more than 30% women outperformed the least gender–diverse companies with above–average profitability.
- Cultural Implications: Society is shaped by norms and behaviors. The under–representation of women in AI perpetuates harmful stereotypes, creating a self–fulfilling prophecy and limiting the diversity of voices shaping our future. This has a negative impact on equality and belonging in the workplace. Equitable gender representation is a must if we want to change the narrative around who can participate in and lead technological innovation.
- Technological progress: AI systems that are predominantly designed and trained by men could lead to suboptimal solutions that disadvantage women consumers. For example, studies have shown that some facial recognition systems have lower accuracy for women and ethnic minorities than for white men. We can’t afford to ignore the perspectives of half the population in future design and development of AI.
Barriers for gender balance in AI
Some of the root causes of underrepresentation of women in AI are insufficient role models, unequal access to educational opportunities, stereotypes, biases in hiring, and hostile tech culture. A lack of education and clarity on the range of roles and industries in which one can work with AI has contributed to keeping women out of the field. Once women overcome the first hurdle of getting into AI, they often face another challenge: staying. Fifty seven percent of women said that they left their employer due to discrimination.
Actions to foster gender diversity in AI
I am inspired by Maria Klawe’s leadership at Harvey Mudd College where she increased the ratio of women in computer science from 10% to 40% in 5 years. This involved culture change, rigorous tracking, and course correction to increase interest and belonging in computer science. Concerted efforts by educational institutions, employers, policy makers, and individuals will be required to attract and retain women in AI.
Based on Women in AI research I conducted while at Nesta and my experience of launching digital skills training in the UK (Ada National College for Digital Skills and 01Founders), I recommend:
- Showcase female AI trailblazers: Encourage and inspire more girls and young women to pursue and excel in AI by providing them with positive role models, mentors, and guidance. For example, you could join STEM Ambassadors, Girls Who Code or Founders4Schools to inspire the next generation of AI leaders.
- Change the perception of AI: Create public dialog about new ways of talking about AI and thinking about its impact e.g. AI for Good Global Summit. Highlight not just the engineering and technical roles but also opportunities in product management, customer experience, AI ethics, data science, and beyond.
- Celebrate impact of women: Celebrate and amplify the achievements of women in AI by recognizing and rewarding their excellence and impact. For example, Women in AI Awards, Women in Machine Learning, Women in Data, among others.
- Provide training opportunities: Promote a culture of continuous learning and provide women with professional development opportunities to unlock their potential. Some examples include Teens in AI, AI4Good Lab, and Women in Data Science.
- Build an inclusive culture: Create a respectful, inclusive, and supportive environment for women by improving access to opportunities for learning, networking, and leadership.
- Be an ally: Collaborate and partner with other women in AI, by building and joining communities and organizations (e.g. Tech Talent Charter, National Center for Women and Information Technology) that share the mission of promoting gender balance in AI.
Empowering women in AI isn’t just about fairness, it’s about unlocking untapped potential. By taking these actions, we can create a more diverse, inclusive, and vibrant AI community that builds a better future, fuels innovation and drives economic prosperity for all.
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How we can empower women to drive innovation in AI
Photo by ThisisEngineering RAEng on Unsplash
March 8, 2024
Fixing AI’s gender–diversity problem is both a moral imperative and a strategic one. By upskilling women and increasing their representation in AI leadership, we can create a more inclusive, innovative, and productive future, writes Joysy John.
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rtificial Intelligence has immense potential to positively transform the world but it has a gender–diversity problem. Empowering women in AI is not just a moral imperative but a strategic necessity. By upskilling women and increasing their representation in AI leadership, we can create a more inclusive, innovative, and productive future.
Women represent roughly 47% of the UK and U.S. labor force. Yet they make up just 16% of the tenure–track faculty focused on AI globally and only 26% of data and AI positions in the workforce. The lack of gender diversity in AI research has far–reaching consequences.
Why does the lack of gender diversity matter?
AI failures disproportionately impact women and those from marginalized backgrounds. It perpetuates existing biases and reinforces societal inequalities. For example, Amazon’s AI–driven recruitment system was found to discriminate against women for technical jobs. Beyond missed opportunities, this imbalance impedes progress on economic, cultural and technological fronts.
- Economic Impact: Diverse teams drive innovation and economic prosperity. When capable women are excluded from AI, we miss out on fresh perspectives, novel ideas, and potential breakthroughs. McKinsey research shows that companies whose workforces consist of more than 30% women outperformed the least gender–diverse companies with above–average profitability.
- Cultural Implications: Society is shaped by norms and behaviors. The under–representation of women in AI perpetuates harmful stereotypes, creating a self–fulfilling prophecy and limiting the diversity of voices shaping our future. This has a negative impact on equality and belonging in the workplace. Equitable gender representation is a must if we want to change the narrative around who can participate in and lead technological innovation.
- Technological progress: AI systems that are predominantly designed and trained by men could lead to suboptimal solutions that disadvantage women consumers. For example, studies have shown that some facial recognition systems have lower accuracy for women and ethnic minorities than for white men. We can’t afford to ignore the perspectives of half the population in future design and development of AI.
Barriers for gender balance in AI
Some of the root causes of underrepresentation of women in AI are insufficient role models, unequal access to educational opportunities, stereotypes, biases in hiring, and hostile tech culture. A lack of education and clarity on the range of roles and industries in which one can work with AI has contributed to keeping women out of the field. Once women overcome the first hurdle of getting into AI, they often face another challenge: staying. Fifty seven percent of women said that they left their employer due to discrimination.
Actions to foster gender diversity in AI
I am inspired by Maria Klawe’s leadership at Harvey Mudd College where she increased the ratio of women in computer science from 10% to 40% in 5 years. This involved culture change, rigorous tracking, and course correction to increase interest and belonging in computer science. Concerted efforts by educational institutions, employers, policy makers, and individuals will be required to attract and retain women in AI.
Based on Women in AI research I conducted while at Nesta and my experience of launching digital skills training in the UK (Ada National College for Digital Skills and 01Founders), I recommend:
- Showcase female AI trailblazers: Encourage and inspire more girls and young women to pursue and excel in AI by providing them with positive role models, mentors, and guidance. For example, you could join STEM Ambassadors, Girls Who Code or Founders4Schools to inspire the next generation of AI leaders.
- Change the perception of AI: Create public dialog about new ways of talking about AI and thinking about its impact e.g. AI for Good Global Summit. Highlight not just the engineering and technical roles but also opportunities in product management, customer experience, AI ethics, data science, and beyond.
- Celebrate impact of women: Celebrate and amplify the achievements of women in AI by recognizing and rewarding their excellence and impact. For example, Women in AI Awards, Women in Machine Learning, Women in Data, among others.
- Provide training opportunities: Promote a culture of continuous learning and provide women with professional development opportunities to unlock their potential. Some examples include Teens in AI, AI4Good Lab, and Women in Data Science.
- Build an inclusive culture: Create a respectful, inclusive, and supportive environment for women by improving access to opportunities for learning, networking, and leadership.
- Be an ally: Collaborate and partner with other women in AI, by building and joining communities and organizations (e.g. Tech Talent Charter, National Center for Women and Information Technology) that share the mission of promoting gender balance in AI.
Empowering women in AI isn’t just about fairness, it’s about unlocking untapped potential. By taking these actions, we can create a more diverse, inclusive, and vibrant AI community that builds a better future, fuels innovation and drives economic prosperity for all.
