This Women’s Month, Dr Denisha Jairam-Owthar, CIO at the Council for Medical Schemes, highlights the inequalities in representation between women and men technology leaders responsible for AI adoption.
While the world explodes with AI and tries to navigate its ethical usage, there is another crucial aspect for consideration: is there sufficient data that represents women in our data sets to enable this AI explosion?
Data is a key driver for AI, if not the most crucial component for it to work effectively, and if our data is not well represented, providing women’s views on feedback and inputs, how can AI then further the ‘equitable bridging’? Already there is a widened divide between the fair representation of women and men across all fronts, from product design to corporate representation of women in senior positions.
From the design of seat belts to the design of gardening tools – there are subtle biases that women have largely learnt to live with and believe that this is the norm of “a man’s world”. Probe a little deeper, however, and one realises how inadequate these product designs may actually be for women.
The gender profile of ICT skills can also impact algorithmic justice. When conforming to AI initialisation, whereby the current ICT skills sets still struggle extensively with equity for ICT skills across the spectrum, ethical data practices are needed to be formulated as a means of compliance to ensure that data from women is adequately included.
Arising from the systematic imbalances of power in the technology sector, even though women represent more than half the world’s population, we need now, more than ever, to increase the number of women data activists who will drive the implementation of equitable data sets to be used to assimilate AI.
We need not just ‘window dressing’ with ‘token appointments’ of women in technology, but deep institutional change of ensuring women’s thoughts and voices are echoed and heard in the data sets – and in every aspect of technology – coupled with the conveyor belt of our female skills entering and thriving in the tech sector.
Within this, the possibility can exist where we can win this ‘silent war’ of AI development that currently could be using only privileged data sets. We could also choose instead to positively contribute using the rapid speed of AI infiltration into the world and to close the global gender equity gap that has existed for centuries.
As we celebrate Women’s Month, let’s move forward in celebrating women’s design, women’s preferences and diversity in the data sets that are used to drive AI, or we risk unanticipated consequences for women. Women’s representation and voices need to be respected in the AI revolution via more equitable and nuanced data – women need seats at the ‘AI table’ too!
