As AI continues to evolve and become more embedded in the workplace and in institutions of higher learning, a gender gap persists, according to recent surveys.
“Businesses lose approximately 50% of women at each stage of the career ladder from entry-level to senior leadership roles,” said Radhika Punshi, Organizational Psychologist, Co-Founder and Managing Director at Mercer Talent Enterprise. Mercer is a global management consulting firm.
“Women’s representation in the labor force took a hit during the pandemic, and the adoption of AI in jobs where women are over-represented could exacerbate this trend,” Ms. Punshi said. “This threatens a double whammy that could leave significant gaps in the representation of women at all levels. As we accelerate towards the age of AI, it is becoming increasingly evident that we must address risks around gender bias and inclusion. Businesses will need to work hard to shift mindsets and behaviors to drive cultural change, so women, under-represented and minority groups aren’t left behind in this rapidly evolving digital world.”
Women More Likely to Face Discrimination
In the recent article “Are Women Right To Be Wary Of AI?,” published on the company’s website, and co-written by Ms. Punshi and Kate Bravery, a partner and the Global Advisory Solutions & Insights Leader at Mercer, the gender gap and its effect are explained. “The painful truth is that, if women aren’t co-pilots of the current AI revolution, they may be left in the dust, faced with technology that presents a whole series of new barriers for them to overcome. Crucially, female representation in the development of AI still has a long way to go. Women still only make up just 26% of the industry, and, even when they get their foot in the door, they’re more likely to face discrimination and are 65% more likely to be made redundant than men.”
Women hold more of the jobs in sectors that are expected to be most impacted by AI, in terms of disrupting or eliminating jobs, according to the Mercer report. Those sectors include administration, healthcare, education and social services. The World Economic Forum predicts there will be 26 million fewer jobs in administration, cashiers, payroll clerks and secretaries by 2027. And there is a ripple effect to such a dramatic shift, in terms of the pension equity gap, which is already at 40%.
That gender gap can be closed quicker through more mentorship of women in the field, addressing AI bias, and a focus on the career field in high school to lead to more women pursuing AI-related majors in college, experts say.
According to Women In Tech, a web-based UK company dedicated to women currently working in the tech industry, or seeking employment in tech, based on the rate of progress of women in tech from 2006 to 2023, it will take more than 100 years to achieve global gender equity. “In 2021, the AI market size was valued at $93.5 billion and was predicted to expand at a growth rate of 38% between 2022 and 2030. Due to the huge demand for technologies like smart homes, digital assistants and self-driving vehicles, AI is believed by many to be the future of the way we live. With this demand comes the need for a highly skilled and dedicated workforce. However, currently, only 22% of AI employees globally are female, leaving a gender and skills gap which is all too common in tech sectors.”
According to a recent study by the Alan Turing Institute, titled “Where are the women, Mapping the gender gap in AI,” between 15-20% of computer science degrees are earned by women, in the U.S. and Western Europe, down from nearly 40% in the 1980’s. “Our research, based on a unique dataset of AI professionals, indicates that data science and AI careers in the UK and globally are heavily gendered. There is persistent structural inequality in these fields associated with extensive disparities in skills, status, pay, seniority, industry, attrition rates, educational background and even self-confidence levels. This gender job gap needs rectifying so that women can fully participate in the AI workforce, including in powerful leadership roles in the design and development of AI.”