Addressing formal and informal barriers to women's participation in AI
My research is centred around the gap between men and women in AI as an element of wider, systemic gender inequality, which occurs throughout various fields in social, political and economic spheres. Tying the gender gap in AI to a three-tier genesis: The historical erasure and exclusion of women from the ICT industry narrowing the sphere of tech solutions, The hierarchy in social positioning that skews favourably towards men and allows them to dictate the status quo in AI companies and projects and the entrenched bias in data, in workplaces and in AI applications which contributes to the ‘leaky pipeline’ effect that sees fewer women participating in and climbing up the ranks of AI companies and projects, the research seeks to identify solutions to these harms.
Strengthening current discourse on improving the AI workforce that approaches equality as greater than equality by the numbers by including studies of power structures and gender imbalances within existing workforces. Providing insight into implicit bias within organizational cultures cue to different social, political and economic contexts and the ramifications that hold for the output of AI companies.