Gender imbalance is commonly seen in the tech and finance industries, with women making up just 21% of the tech workforce. Research by Grant Thornton revealed that just 19.1% of CEOs in tech are women, compared to 25.8% globally in mid-market firms.
This is being exacerbated by the rise of AI automating many female-dominated roles, perpetuating bias against women, and women falling behind in AI adoption rates. Strategies to tackle the change AI is bringing to the workplace, with a focus on the effects on women, are required.
The future of AI and women in the workplace
A report by the City of London revealed that over the next decade, 119,000 clerical roles in tech, finance, and professional services are at risk. This is especially worrying as female clerical workers make up 10% of the financial sector workforce, and 68% of clerical occupations overall. Displacing these jobs could cost up to £752m ($1.02bn) in severance payments, proving to be expensive for the sector.
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Lower AI adoption rates shown by women are likely to have effects in the workplace. There is estimated to be a gap of 25% in women’s uptake of AI against their male counterparts. From November 2022 to May 2024, women made up only 42% of the 200 million average monthly users of ChatGPT’s website and only 27% of ChatGPT app downloads.
Lower adoption rates will likely present barriers to professional development, due to the integration within the workplace and requirements in AI literacy. Hesitancy to use these tools will not only create additional challenges for women’s professional development but could also affect businesses’ productivity. Fewer women using these tools will also create less feedback from women, which is especially important when AI tools are often still in early rollout or developmental phases in the workplace.
The inherent bias of AI
AI bias has been shown in areas ranging from healthcare to recruitment, as well as in generative AI. Images created using generative AI commonly depict men as doctors and women as nurses, as well as CEOs as men. Researchers at LSE, funded by the National Institute for Health and Care Research, found that Google’s Gemma AI model downplayed female symptoms of physical and mental issues in comparison to men when used to generate and summarise case notes.
In 2018, Amazon discontinued developing an AI software as a recruiting tool due to the tool favouring male CVs. These kinds of bias are highly detrimental to women, not only reflecting current societal bias but also enforcing it.
To overcome these problems, companies should invest in reskilling and upskilling female workers and ensure that their staff is educated on how AI works and the technology’s potential for bias. Meanwhile, tech companies must improve the training data that algorithms learn from and ensure that there is female representation in development teams.
Above all, governments must enforce strong legislation regarding the use of AI in healthcare and recruitment, to make companies liable for the bias associated with it.
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