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Machine learning, social learning and self-driving cars

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Self-driving cars, a quintessentially ‘smart’ technology, are not born smart. The algorithms that control their movements are learning as the technology emerges. Self-driving cars represent a high-stakes test of the powers of machine learning, as well as a test case for social learning in technology governance. Starting with the successes and failures of social learning around a much-publicized fatal Tesla Model S crash in 2016, I argue that trajectories and rhetorics of machine learning in transport pose a substantial governance challenge. Governing these technologies in the public interest means improving social learning by constructively engaging with the contingencies of machine learning.

This talk is part of the Departmental Seminars in History and Philosophy of Science series.

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