Harnessing AI to Reshape Gender Norms in the Workforce

By Alexandra Whittington and Graham Norris

Regardless of the hype, the long-term trend of artificial intelligence gaining an increasingly prominent role in our lives continues, and we need to stay alert to its impact on society. As AI becomes more integral to productivity and work, it is crucial that we approach its development and integration with intentionality, particularly when it comes to gender.

AI is not a neutral technology; it is shaped by the data it is trained on and the biases of those who develop it. If we are not vigilant, AI could reinforce existing gender stereotypes and further marginalize already underrepresented groups. Alternatively, if we approach AI with a gender-conscious lens, we can leverage its capabilities to break down barriers and create a more inclusive and equitable society.

Unfortunately, there are already numerous examples of AI reinforcing traditional gender disparities. The default voice of personal assistants like Alexa and Siri has usually been female, perpetuating the notion that women make great assistants. Both Apple’s Siri and Microsoft’s now discontinued Cortana were both named after females, one real and one fictitious.???

Similarly, generative AI models trained on internet data have been known to produce hypersexualized and objectified images of women, reflecting the pervasive gender bias present in much of the training data. This not only perpetuates harmful stereotypes but also contributes to the normalization of the objectification of women.

Moreover, many AI systems have been found to exhibit male bias, performing better on tasks related to stereotypically male professions or displaying gender-biased language. For instance, some machine translation models have been shown to associate certain occupations, like nurses and teachers, more strongly with female pronouns, while others, like engineers and scientists, are more closely linked to male pronouns.

These examples illustrate how AI, if not developed and deployed with care, can reinforce and amplify existing gender disparities, potentially undoing progress toward gender equality and hindering the full realization of AI's potential benefits.

The cost of failure would be substantial. When certain groups are marginalized or face barriers to entry and advancement, it not only limits their individual opportunities but also deprives society of their potential contributions. This, in turn, hampers innovation, creativity, and overall productivity.

Furthermore, gender bias in AI systems themselves can lead to suboptimal decision-making and resource allocation, further compounding the issue. For example, if an AI-powered hiring system exhibits gender bias, it may overlook qualified candidates, resulting in a less diverse and capable workforce.

There are already examples of how we can leverage the capabilities of AI to enable economic empowerment and break down gender stereotypes across various professions.

For example, with AI-powered personalized learning platforms and virtual tutors, the role of a teacher is being redefined, away from just lecturing to a "guide on the side" who facilitates learning experiences. This reduces the emphasis on nurturing that has traditionally been seen as a female role. It could also increase the pay and status of teachers, bringing them into line with other professions.?

But not all work is paid, and unpaid work is disproportionately undertaken by women. According to the International Labor Organization, women spend 2.5 times more time on unpaid care and domestic work than men. As robots become more dexterous and benefit from machine learning, they are starting to take on more of the tasks that only humans were capable of and women were expected to do.?

And in fashion, generative AI is democratizing creativity and may have the effect of making design less stereotypically feminine. With AI tools that can generate unique designs and patterns, the fashion industry could become more accessible to individuals of all genders, breaking down the notion that fashion is solely a female pursuit.

But how about male-dominated professions?

Automated farming and synthetic biology are emerging as new frontiers where women could be frontrunners. Traditionally, agriculture has been viewed as a physically demanding and labor-intensive occupation, which has contributed to the underrepresentation of women in the field. AI-powered precision agriculture involves the use of advanced sensors, drones, and data analytics to optimize crop yields, reduce waste, and increase efficiency. This approach requires skills in areas such as computer science, data analysis, and engineering, which are not inherently gender-biased. Similarly, synthetic biology, which involves the design and engineering of biological systems for various applications, including agricultural purposes, is a rapidly growing field that relies heavily on scientific knowledge and technological expertise rather than brawn.??

In the trades, the transition to clean energy will ensure the uninterrupted use of AI going forward, and its rise necessitates a large gender-blind workforce in electrical plumbing and similar roles. AI-powered tools and automation in these fields could make them more accessible to individuals of all genders, breaking down the traditional association of trades with masculinity.

And as AI permeates the business world, it could create a higher expectation of relational skills from CEOs and other executive roles. With AI handling much of the analytical and data-driven decision-making, the role of a CEO may shift towards leading with empathy, emotional intelligence, and strong communication skills – traits often associated with feminine leadership styles.

Ultimately, AI presents us with an opportunity to challenge long-standing gender norms and pave the way for a future where opportunities are not limited by outdated stereotypes, but rather by an individual's talents and ambitions. It is our responsibility to embrace this opportunity and shape AI in a way that empowers all genders, to the benefit of everyone.