CSTPR Noontime Seminar

Machine Learning, Social Learning and the Governance of Self-Driving Cars
by Jack Stilgoe
Department of Science and Technology Studies, University College London
Abstract: Self-driving cars, a quintessentially ‘smart’ technology, are not born smart. In the algorithms that control their movements and the connections they make with their surroundings, they are learning as they emerge, in organised and haphazard ways. As well as a test of the powers of machine learning, they are an important test case for social learning in the technology governance. In this talk, I reframe responsible innovation as social experiment, with the key question being ‘who learns what?’ Focussing on the successes and failures of social learning around a much-publicised crash in 2016, I argue that trajectories and rhetorics of machine learning in transport pose a substantial governance challenge. ‘Self-driving’ or ‘autonomous’ cars are misnamed. As with other technologies, they are shaped by assumptions about social needs, solvable problems and economic opportunities. Governing self-driving cars in the public interest means challenging this discourse of autonomy and appreciating the ways in which self-driving cars will be entangled in their environments. I will conclude with some options for governance that should enable greater social learning.
Bio: Jack Stilgoe is senior lecturer at the department of Science and Technology Studies, University College London. His teaching and research interests are in science and innovation policy and the governance of emerging technologies. Among other publications, he is the author of Experiment Earth: Responsible Innovation in Geoengineering (Routledge 2015).