Addressing identity mismatch challenges

Right now, the technological challenge we are most likely to face in the labour market is ‘frictional’ technological unemployment – where there is plenty of work available, but not enough people are able to do it. This lecture explores the phenomenon and its main causes – that people might lack the right skills for the work, not live in the place where the work is created, or have an identity that is at odds with the nature of the work.

This lecture was recorded by Professor Daniel Susskind on the 24th of February 2026 at Barnard’s Inn Hall, London

Dr Daniel Susskind is a writer and economist. He explores the impact of technology, and particularly AI, on work and society. He is a Research Professor at King’s College London, a Senior Research Associate at the Institute for Ethics in AI at Oxford University, a Digital Fellow at the Stanford Digital Economy Lab, and an Associate Member of the Economics Department at Oxford University. 
 
His new book, Growth: A Reckoning (2024), was chosen by President Obama as one of his ‘Favourite Books of 2024’ and was a runner-up for the Financial Times Business Book of the Year 2024. He is also the author of A World Without Work (2020), described by The New York Times as "required reading for any potential presidential candidate thinking about the economy of the future” and a runner-up for the Financial Times Business Book of the Year 2020, and co-author of the best-selling book, The Future of the Professions (2015). His TED Talk, on the future of work, has been viewed more than 1.6 million times. He is currently working on his next book, What Should Our Children Do? How to Flourish in the Age of AI. 
 
Previously he worked in various roles in the British Government – in the Prime Minister’s Strategy Unit, in the Policy Unit in 10 Downing Street, and in the Cabinet Office. He was a Kennedy Scholar at Harvard University

The transcript of the lecture is available from the Gresham College website: https://www.gresham.ac.uk/watch-now/out-reach

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