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STICERD Econometrics Seminar Series

The Means of Prediction

Maximilian Kasy (Oxford)

Thursday 20 November 2025 14:00 - 15:30

Many of our seminars and public events this year will continue as in person or as hybrid (online and in person) events. Please check our website listings and Twitter feed @STICERD_LSE for updates.

Unless otherwise specified, in-person seminars are open to the public. Please ensure you have informed the event contact as early as possible.

Those unable to join the seminars in-person are welcome to participate via zoom if the event is hybrid.


About this event

Maximilian Kasy will present his forthcoming book, The Means of Prediction. Artificial intelligence, far from being an unstoppable force, is irrevocably shaped by human decisions—choices made to date by the ownership class that steers its development and deployment. Kasy shows that the technology of AI is ultimately not that complex. It is insidious, however, in its capacity to steer results to its owners’ wants and ends. Kasy clearly and accessibly explains the fundamental principles on which AI works, and, in doing so, reveals that the real conflict isn’t between humans and machines, but between those who control the machines and the rest of us. The Means of Prediction offers a powerful vision of the future of AI: a future not shaped by technology, but by the technology’s owners. Amid a deluge of debates about technical details, new possibilities, and social problems, Kasy cuts to the core issue: Who controls AI’s objectives, and how is this control maintained? The answer lies in what he calls “the means of prediction,” or the essential resources required for building AI systems: data, computing power, expertise, and energy. As Kasy shows, in a world already defined by inequality, one of humanity’s most consequential technologies has been and will be steered by those already in power.

STICERD Econometrics seminars are held on Thursdays in term time at 14.00-15.30, in SAL 3.05, unless specified otherwise.

Seminar organisers: Dr Yike Wang, Professor Tai Otsu, and Dr Vassilis Hajivassiliou.

For further information please contact Sadia Ali: s.ali43@lse.ac.uk.

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