Highlighting Women in AI: An Exploration of Kate Devlin’s Research on AI and Intimacy at King’s College
To give AI-focused women academics and others their well-deserved — and overdue — time in the spotlight, TechCrunch is launching a series of interviews focusing on remarkable women who’ve contributed to the AI revolution. We’ll publish several pieces throughout the year as the AI boom continues, highlighting key work that often goes unrecognized. Read more profiles here.
Kate Devlin is a lecturer in AI and society at King’s College London. The author of “Turned On: Science, Sex and Robots,” which examines the ethical and social implications of tech and intimacy, Devlin’s research investigates how people interact with and react to technologies — both past and future.
Devlin — who in 2016 ran the U.K.’s first sex tech hackathon — directs advocacy and engagement for the Trusted Autonomous Systems Hub, a collaborative platform to support the development of “socially beneficial” robotics and AI systems. She’s also a board member of the Open Rights Group, an organization that works to preserve digital rights and freedoms.
Briefly, how did you get your start in AI? What attracted you to the field?
My journey began in the realm of archaeology, transitioning eventually into the field of computer science where I earned a Ph.D. in 2004. Although my initial intent was to mingle these areas of study, my focus steadily inclined towards the human-computer interaction domain, including the interaction between humans and AI or robot technology and the perception of such technologies.
Most esteemed work in the AI field?
Currently, the recognition of emotional intimacy and AI as serious academic territory is what fills me with satisfaction. The proliferation of intriguing research in this area is certainly awe-inspiring. A domain once considered highly niche and far-fetched is now making waves with instances of individuals building significant relationships with chatbots, relationships that are of substantial importance to these individuals.
Strategy to tackle the obstacles of the primarily male-populated tech and, by extension, AI industry?
I don’t. We just persevere. It’s still shockingly sexist. And maybe I don’t want to “lean in”; maybe I want an environment that isn’t defined around macho qualities. I guess it’s a two-pronged thing: we need more women in visible, top positions, and we need to tackle sexism in schools and beyond. And then we need a systemic change to stop the “leaky pipeline” — we’re seeing an increase of women in AI and tech due to a rise in homeworking as it fits better with childcare which, let’s face it, still falls to us. Let’s have more flexibility until we don’t have to do the majority of that caring on our own.
What advice would you give to women seeking to enter the AI field?
You have the right to take up as much space as men.
What are some of the most pressing issues facing AI as it evolves?
Responsibility. Accountability. Presently, there’s a rising sense of apprehension surrounding technological determinism — as if we are speeding uncontrollably towards a precarious future. But it doesn’t have to be this way. We can choose to disagree. It’s fine to prioritize a different direction. Most of the challenges we’re facing aren’t necessarily novel; it’s the magnitude and proliferation of these issues that makes them particularly complex.
What are some concerns AI users need to be conscious of?
Well… late-stage capitalism.
To give a more practical answer: validate the source — where is the data originating from? How ethical are the practices of the provider? Do they have a commendable history of social responsibility? Would you trust them with the operation of your oxygen supply if you were on Mars?
What is the best way to responsibly build AI?
Regulation and conscience.
How can investors better push for responsible AI?
From a business perspective, happier customers can be achieved by demonstrating genuine care for people. It’s important to see beyond mere ethics-washing and ensure it really counts. Encourage companies to take into consideration elements such as human rights, labor, sustainability, and social impact within their AI supply chain.
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