What are you currently working on?

I co-lead the Women in Data Science and AI project within the Public Policy programme at the Turing, and most recently we’ve been working on a policy paper which is being released to coincide with International Women’s Day. The report presents the results of our social data science research into mapping gendered career trajectories - in other words, the gender gap - in the fields of data science and AI.

Recently, I’ve also been giving a number of talks about how data and algorithmic biases, alongside imbalances in the AI sector, result in a feedback loop which shapes and amplifies biases in AI and machine learning systems. It is crucial that we get ahead of this now, before these flawed technologies become irreversibly integrated into the fabric of society.

Most surprising thing to come out of this research?

Firstly, it’s the striking scarcity of quality, disaggregated, intersectional demographic data available about the global AI and data science labour force. Responsibly collecting this is a crucial first step in interrogating and tackling these issues. We were also surprised to find the extent and impact of men’s dominance in AI and data science, especially in technical and leadership roles.

Our findings reveal persistent structural inequality in these fields, associated with disparities between women and men in skills, status, seniority, jobs and attrition rates. Especially alarming is that only 8% of UK researchers who contribute to the pre-eminent machine learning conferences are women. In other words: the world is being increasingly shaped by decision-making machines, but the people whose work underpins that vision are far from representative of the society these systems are meant to serve.

What do you hope is the impact of your work?

I hope for better recognition of the inequities in the global data science and AI workforce. The lack of this is currently a major stumbling block for the opportunities of women and marginalised groups in the broader technology industry. It’s not only an ethical issue of social and economic justice, but also crucially holds back innovation. Our policy paper highlights the need for effective policy responses if society as a whole is to reap the benefits of technological advances in AI.

I also hope that we can re-write the narrative; by this I mean heightening awareness of the gendered history of computing in order to avoid its replication in AI and data science. Finally, our Women in Data Science and AI Hub, including our list of resources, aims to help women build successful data and AI careers, and raise awareness of creating fair and equitable AI.

What has been the highlight of your career so far?

There have been a few but honestly getting to work with my amazing team in the Public Policy programme at the Turing has been fantastic. Also, being accepted to Cambridge for my undergraduate degree - albeit at the very start of my career - truly changed my life, so I’d have to add that too.

Who would you invite to your dream dinner party?

It’s a very, very long list, but to name a few:

  • Marcus Aurelius
  • Beyoncé
  • Fred Astaire
  • Harriet Tubman
  • Robin Williams
  • Dave Chappelle
  • Emmeline Pankhurst
  • Dolly Parton
  • The Buddha
  • Alan Turing
  • Michelle Obama
  • Stephen Fry
  • Katherine Johnson
  • Nye Bevan
  • A lot of dogs
  • And I’m so grateful to be able to say my own family and friends!

And finally, when not working what can you be found doing?

I love working out (yoga, boxing, running, HIIT), dancing (I used to be a ballerina), and - in normal times - dinner parties with friends, and exploring the world. I’ve also picked up some new plant-based cooking skills in lockdown!