University of Cambridge > Talks.cam > Machine Learning Reading Group @ CUED > Challenges of Regulating Increasingly Complicated Human-AI Collaborative Systems

Challenges of Regulating Increasingly Complicated Human-AI Collaborative Systems

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AI systems increasingly permeate many aspects of our lives, from the passport scanners at Heathrow, and recommendation engines modulating what we consume. AI systems hold promise to radically transform our productivity, wellbeing, and what we know about the world around us; however, they can also cause harm. As aptly said in Spiderman: “with great power there must also come great responsibility.” One of the key approaches in regulatory efforts designed to ensure safe use of AI is the concept of human oversight and human-the-loop. But are these measures always effective in reducing risk of harms? We start by assessing simple algorithmic decision systems and progress to rapidly emerging challenges raised around the regulation of refurbished “generative” AI.

We focus in particular on questions of regulating these systems in the context of human-AI collaboration, but highlight how such questions are increasingly intertwined from broader regulatory calls around AI safety and “AGI”. We’ll touch on a range of different efforts – from the EU AI Act to Biden’s new Executive Order, to the recent Hollywood AI strikes. We hope to leave ample time for discussion with the CBL Community and Friends of CBL about what these regulatory efforts may mean in our own day-to-day research and beyond – looking forward to discussing with you all!

This talk is part of the Machine Learning Reading Group @ CUED series.

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