The writer is a research contracts manager and a business founder. She is writing in a personal capacity
At 7:55am, I step on to the train into London, joining my fellow commuters, phones in hand, screens aglow.
During the 25-minute journey, thanks to artificial intelligence (AI), I can learn how to calculate the present value of a hypothetical annuity using a new formula, followed by a reverse calculation to determine its future value. I can better prepare for complicated test questions like these, ahead of an upcoming business school entrance test. Applying to an MBA programme is part of a plan to improve my chances of securing a leadership role at a top research and innovation organisation.
An ethical revolution and the fight against bias
While more women than ever are part of the workforce worldwide, they remain under-represented in leadership roles. In the UK, for instance, women occupy more than a third of board positions in FTSE 350 companies but gender parity in senior management remains elusive.
Why is this? According to management consultancy McKinsey, a “broken rung” is hampering women’s progress from entry-level positions to junior management, which is where important leadership skills are honed — such as planning and strategy. Contributing factors include inflexible working, the burden of domestic tasks, microaggressions, and entrenched gender bias.
This matters because research shows that, when it comes to women progressing to top positions, AI can reinforce underlying biases that we actively try to identify and counteract in society.
One study last year found that language-based generative AI risked perpetuating gender biases in leadership. When researchers asked AI to provide examples of leaders, good and bad, women were more likely to be presented as “bad leaders”. Bad male leaders were tyrannical and power-hungry despots, whereas bad female leaders were much more often deemed plain incompetent.
This will not surprise anyone who has experienced the double standard of male competence being assumed and that of female competence needing to be demonstrated. According to studies, such as Potential and the Gender Promotion Gap (2022) by three US academics, men are often promoted on showing promise, but women are routinely expected to have at least one breakthrough first.
This is relevant because these harmful patterns will only be amplified as more and more online content is created by generative AI.
And, yet, there are grounds for expecting AI to help eradicate bias — and, therefore, help women to have a fair shot at securing and thriving in more senior roles.
To start with, AI-led processes in hiring and assessment could mean less discrimination for those aspiring to leadership positions. Critics may fear this will dehumanise the process, but it is the human aspect where processes have gone consistently wrong.
That puts the onus on Big Tech to prioritise ethics in AI — applying multiple and diverse perspectives to gain the highest benefits — alongside design and development. Otherwise, AI will eventually face its own crisis of legitimacy, in the same way every patriarchal model now does. Sceptics should consider that the inclusion of women in positions of power and influence only started to improve around the middle of the last century, thanks again to widely available new technology — think of the washing machine, the freezer and, later, the microwave.
As a research professional, I find it heartening to see just how much ethics is a central concern for Big Tech. I have yet to come across a conference, paper or podcast on AI where unbiased algorithms trained on increased representation are not seen as top contenders to eradicating bias. That is despite arguments against this view, such as Hilke Schellmann’s recent book, The Algorithm.
A common question is: whom do the algorithms underlying generative AI fail? It is almost impossible to capture the infinity of human identities, so Big Tech supporting women — as the lowest common denominator of most under-represented groups — to take the lead on the ethics and the technical development of AI would be a key first step.
Better skills and less productivity inequality
Studies have shown that AI increases the productivity of lower-skilled roles more than that of higher-skilled colleagues by disseminating knowledge and best practice from expert workers to novices — thus closing the gap.
As women predominate in administrative and clerical positions, they therefore stand to benefit disproportionately from the digital transformation. AI can take over menial tasks, freeing up time for improving skills, for working on their own vision or for strategic planning, networking and mentoring — all key activities identified by McKinsey’s report as missing in the broken rung.
This opportunity extends beyond junior management. It can apply across the whole workforce, as Athina Kanioura, chief strategy and transformation officer at PepsiCo, outlined nearly two years ago. The food and drink company’s Digital Academy was set up to help employees improve their digital skills, including the use of AI to improve their work. Its warehouse operatives can use predictive maintenance, for example. Retail assistants can attain unprecedented levels of consumer insights for their stores.
And, of course, this year I started using AI, myself, to help prepare for the Graduate Management Admission Test — the entrance requirement for some MBA programmes.
In conclusion, then, AI brings hope for women to gain greater representation in senior management — both by fighting gender bias via mass-scaled AI and by using it to develop their leadership skillsets.
Technology sector efforts that enable women to take the lead on mass-scaling AI are so much more than an ethical imperative. They will be a strategic advantage for business in general, by protecting its long-term legitimacy — the kind of legitimacy that can come only from representation — and ultimately for society as a whole.
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