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Date: November 1, 2024 (Friday) Speaker: Michael Frank, Founder and CEO, Seldon Strategies and 2430 Fellow, 2430 Group Chair: Dr Frank Hong, The University of Hong Kong Abstract: In the artificial intelligence era, national governments are going to great lengths to support their domestic AI ecosystems. But how much can governments actually achieve? In this talk, titled “Strategic

Date: November 8, 2024 (Friday) Speaker: Dr Sean Donahue, Australian National University  Chair: Dr Frank Hong, The University of Hong Kong Abstract: Political philosophers have long been concerned with how to avoid state tyranny, the condition of governments having arbitrary power over citizens. A standard response is that avoiding tyranny requires making power holders conform to

Date: October 28, 2024 (Monday) Speaker: Prof Carlos Montemayor , San Francisco State University Chair: Dr Frank Hong, The University of Hong Kong Abstract: The two prevailing paradigms of artificial intelligence, based on symbolic systems and neural networks, need further refinements in order to qualify as general artificial intelligence. I will argue that the best way to

Date: September 17, 2024 (Tuesday) Speaker: Prof David Plunkett , Dartmouth College Chair: Dr Frank Hong, The University of Hong Kong Abstract: Consider the following three familiar philosophical issues: the nature of consciousness; what distributive justice requires; and what constitutes knowledge. These issues – as well as countless others throughout many subareas of philosophy – are

Date: September 20, 2024 (Friday) Speaker: Dr Adam Bales, University of Oxford Chair: Dr Frank Hong, The University of Hong Kong Abstract: At some future point, AI systems could come to deserve moral consideration, in much the way that humans do now. It will be tempting to design these systems as willing servants, who vacuum, shop,

Date: October 17, 2024 (Thursday) Speaker: Dr Alice Wong, Chapman University  Chair: Dr Frank Hong, The University of Hong Kong Abstract: This talk explores the philosophical implications of simulating algorithms, particularly in the context of artificial intelligence and its relationship to biological cognition. I begin with a brief examination of the nature of simulating (implemented) algorithms,