Women In AI

AI is set to be a critically transformative technology over the next decade, changing how we live and work in every field. The impact of AI and Machine Learning will likely have a greater influence than advances in any other area.

Although AI is looking to transform over the next decade. We need to remember the specialists behind the scenes developing the future of AI. It is critical that diverse voices and perspectives are present at the point of inception, and that the growth of AI is unbiased, presenting both genders in the workforce. While women are under-represented across tech, AI is an area where homogeneity of mindset can have enormous, unintended consequences in misdirecting self-learning systems from the start.

Fighting stereotypes

“[The under-representation of women in AI] comes down to cultural norms and female representation in general,” says Helen Yu, Founder and CEO of Tigon Advisory Corporation. There are pervasive stereotypes that computer science is for boys – and there is a common sense that tech workplaces are hostile to women, she observes. Then there’s the challenge of workaholic tech office cultures, which all too often are incompatible with family life – the burden of which falls disproportionately on women.

Meanwhile, the phenomenon of “stereotype threat” means that a feeling of not belonging will actively worsen a candidate’s performance, notes Helen. As a consequence of these among other factors, just 18% of computer-science degrees in the US are awarded to women today.

Statistics of this kind are not the case everywhere, though. In Algeria, 41% of STEM graduates are women; while in India, women take 35% of specialist technology roles. Research has in fact suggested that countries with higher levels of gender inequality drive women to seek more direct paths to financial freedom – and hence into tech and the STEM fields.

Driving change

So what can businesses do to achieve or surpass these levels of representation? “[We need to] nurture and foster more female role models in AI,” says Helen. Establishing champions and creating support networks for women are often cited as key steps for driving change. And at the same time, organisations must stamp out toxic working practices and look to address unconscious bias at a wider level.

“Businesses first need to have a forward-looking CEO and Head of HR in place to create an embracing culture,” says Helen. “[And] many companies have [already] put in programmes for diversity and inclusion.” She also cites the need to regularly audit talent – and a specific case in a company where four of the six women at the level of VP or above quit within a five-week period. Naturally, it would be important to establish exactly what was happening in such a situation and whether the company needed to respond at the board level.

Another key change is to offer a flexible working environment. “Create an environment to allow women to integrate work with life – [doing so] will retain more female talent,” Helen comments. Werk, a company that supports flexible working practices, reported that 70% of women who had left the workplace would have embraced flexibility if it had been offered. Other research, also suggests that flexibility boosts productivity and staff retention.


Flexibility can also be a matter of mindset. For example, if a business only accepts candidates with specific degrees then it may needlessly exclude others who have the relevant skills but not the required qualifications. “Companies should not limit their recruiting process to those with engineering degrees,” says Helen. “There are many talented females, [for example,] who learned how to code without engineering degrees.” This is also a factor to consider in jobs ads – where exhaustive lists of required skills and qualifications have been shown to disproportionately deter female candidates.

Companies should be in no doubt that driving change is a long-term commitment. “Businesses should invest in STEM programmes such as Rewards and Internships that generate more interest from girls and women,” says Helen. “[And] recognition programmes, to spread the word about girls’ and women’s achievements in math and science, will create [new] role models.”


Looking ahead, there are many women pushing the field of AI forwards. Prof. Fei-Fei Li, the Co-Director of Stanford University’s Human-Centered AI Institute and the Stanford Vision and Learning Lab, who worked as Google Cloud’s Chief Scientist of AI/ML while on sabbatical; there’s Aakriti Srikanth, who won a $100,000 prize for using IBM Watson technology and went on to become IBM’s Head of AI Product Management, Acquisitions; and there’s Cyra Richardson, General Manager of AI and IoT at Microsoft.

The Women Leading in AI network, meanwhile, founded by Ivana Bartoletti, Dr Allison Gardner and Reema Patel in the UK, aims to be a global think tank for women in AI, directly tackling any shortage of diversity in the field. Going further, the organisation focuses on “the good governance of AI as a means to ensure that… [changes] will be of benefit to all people and not further embed societal prejudice in our systems.”

While more needs to be done across the field, there’s clearly a huge amount of work underway – and women who push ahead in AI may very well have a decisive impact on our technological future.