AI has encompassed every single part of the world today. We can find it in nooks and corners across the globe, from harvesting crops in agricultural sectors to disease mapping in high-tech medical corporations. It has become such a vital component of the way the world functions that at this point of evolution, life without AI seems next to impossible.
Recently, I read about the high-profile, artificial intelligence driven, celebrated AI-powered BMW factory in Germany. The automobile factory consists of contemporary software and equipment that allows for the quick and efficient analysis of auto parts and components and delivers detailed descriptions for fluctuations found in the device from its standard specifications. Through the incorporation of AI into their production process, the factory has been able to eliminate pseudo defects, increase efficiency in production and achieve the highest quality of cars when leaving the factory.
Similarly, AI has contributed to numerous ground-breaking transformations to businesses in relation to data-driven predictions, smarter healthcare, increased endurance of manufactured products, improvements in customer support and several more. As AI continues to advance fields in production and research, its industry has inherently expanded by a tremendous scale. However, despite the surging demand for AI, a talent pool that could help businesses achieve their AI ambitions has remained largely untapped – women.
I recently read a report by the World Economic Forum which stated that women (and the non-binary) make up only 26% of data and AI positions in the workforce. Shockingly, a paper published by Stanford University supported this number. After analysing the stats of numerous Tenure-Track Faculties at Computer Science departments of top universities, an astonishing figure of 16.1% contributed to the entire make-up of women in CS.
Was I baffled? Indeed.
Do I think women and the non-binary were baffled? Indeed.
So, what is driving this sustained gender gap in AI, and how can we address it?
In my opinion, fiction reinforces these stereotypes. The popular media tends to reiterate this image of the “boy genius” or “wonder kid”. TV shows such as “Big Bang Theory” to movies like “The Matrix” and “Iron Man” are rife with portrayals of male tech titans.
It seems that the superstars of the Internet and AI age are all men in the popular imagination. Fictional male tech roles are often portrayed as “adorable jerks” and socially awkward nerds.
This stereotype is so strong that when investors or business clients encounter the rare “non-male” tech founder, they would blurt out their disbelief, and when students encounter “non-male” AI researchers whose articles they have read before, it results in bewildered looks when having discovered their gender.
Creating a gender-equal world of AI requires serious work in the AI research community to recruit and promote more female talent. We need to find technical solutions for fair and responsible AI. Investors need to support and provide equal opportunities to every gender identity. We also need to create more images of artificial intelligence and robots in the media without gender stereotypes.