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Strategic Determinism: the Limitations of Governments in Shaping AI Development

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 […]

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Platform Tyranny, Rule of Law, and Virtual Community

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

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Two Models of General Artificial Intelligence

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

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Continuity, Realism, and the Objects of Philosophical Inquiry (co-authored with Tristram McPherson)

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

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What happens when you simulate an algorithm?

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,

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