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Tuesday, 3 December 2024 - 5.30pm
Location: 
Fitzwilliam College, The Auditorium

Speaker: Neil Lawrence (DeepMind Professor of Machine Learning, Senior AI Fellow at The Alan Turing Institute and Visiting Professor of Machine Learning at the University of Sheffield)

Despite its transformative potential, artificial intelligence risks following a well-worn path where technological innovation fails to address society’s most pressing problems. The UK’s experience with major IT projects shows this disconnect: from the Horizon scandal’s wrongful prosecutions to the £10 billion failure of the NHS Lorenzo project. These weren’t only technical failures but a failure to bridge between needs and the provided solution, a failure to match supply and demand.

This misalignment persists in AI development: in 2017, the Royal Society’s Machine Learning Working group conducted research with Ipsos MORI to explore citizens’ aspirations for AI. It showed strong desire for AI to tackle challenges in health, education, security, and social care, while showing explicit disinterest in AI-generated art. Yet seven years later, while AI has made remarkable progress in emulating human creative tasks, the demand in these other areas remains unfulfilled.

This talk examines this persistent gap through a lens that’s inspired by innovation economics. We argue that traditional market mechanisms have failed to map macro-level interventions to the micro-level societal needs. We’ll explore why conventional approaches to technology deployment continue to fall short and propose radical changes needed to ensure that AI truly serves citizens, science, and society.

Neil Lawrence is the DeepMind Professor of Machine Learning at the University of Cambridge and a Senior AI Fellow at the Alan Turing Institute. A leading voice on the real-world impact of artificial intelligence, Neil brings over 25 years of experience in machine learning research and deployment to his insightful talks.

As a former Director of Machine Learning at Amazon, Neil offers a unique perspective on the practical challenges of implementing AI in large-scale industrial systems. His work spans from the cutting edge of AI research to its applications in developing nations, giving him a global view of AI’s potential and pitfalls.

For more details and booking, see the POLIS website.

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