CFI research into the representation of AI is transforming how the technology will be depicted in the future, including by helping the BBC to commission “less clichéd, more accurate and more representative" AI imagery.
When ‘The Whiteness of AI’ by Stephen Cave and Kanta Dihal was published in Philosophy & Technology last year, it triggered coverage in over a hundred news outlets around the world, from BBC Science Focus to the Daily Mail. Just over a year on, the work has continued to inspire responses from both the academic and media communities.
For example, inspired by the 'Whiteness of AI' paper – along with other works, such as CFI's 2018 report with The Royal Society ‘Portrayals and perceptions of AI and why they matter’ – the BBC and the nonprofit We and AI have announced they will collaborate on the project Better Images of AI, which commissions new artwork “towards better, less clichéd, more accurate and more representative images and media for AI”. Furthermore, Dr Dihal was invited to join the project as an advisor.
Meanwhile, gender and race scholar, Shelley M. Park, has published a fascinating commentary, 'More than Skin Deep: a Response to “The Whiteness of AI"' in which she makes three points: (1) the importance of gender in understanding the operation of Whiteness in AI’s construction; (2) that there are many different ways in which Whiteness is scripted, and (3) the White racial frame exceeds white casting and thus cannot be undone by more diverse and inclusive hiring (or engineering).
Stephen and Kanta were in turn invited to respond to this commentary in Philosophy & Technology. Their response paper 'Race and AI: the Diversity Dilemma' argues that Whiteness presents a dilemma for those creating or representing AI. They discuss three possible solutions: avoiding anthropomorphisation, explicitly critiquing racial role-typing, and representing powerful AI as non-White.