Past Event

Deep Ethics

Date: October 10, 2025 (Friday) Time: 15:30 – 17:00 Venue: Room 10.13, 10/F, Run Run Shaw Tower, Centennial Campus, HKU Speaker: Professor Maximilian Kiener Institute for Ethics in Technology, Hamburg University of Technology Abstract: The scholarly literature presents various approaches to integrating ethical considerations into the development of AI, most prominently the approaches ‘ethics by

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AI Welfare

Date: September 19, 2025 (Friday) Time: 14:00 – 17:00 Venue: Room 4.36, 4/F, Run Run Shaw Tower, Centennial Campus, HKU Speaker: Geoff Keeling, Staff Research Scientist, Google Winnie Street, Senior Researcher, Google Abstract: A symposium on the forthcoming book “AI Welfare” by Geoff Keeling and Winnie Street. This is an examination of whether—and which—AI systems

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Instrumental Convergence and Power-Seeking 

Date: September 12, 2025 (Friday) Time: 15:30 – 17:00 Venue: Room 4.36, 4/F, Run Run Shaw Tower, Centennial Campus, HKU Speaker: Professor David Thorstad  Associate Professor of Philosophy Vanderbilt University Abstract: Recent years have seen increasing concern that artificial intelligence may soon pose an existential risk to humanity. One leading ground for concern is that

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Democracy, Epistemic Agency, and AI – 30 Jan 2026

Date: 30 January 2026 (Friday) Time: 10:00am – 11:30am Venue: Room 4.36, 4/F, Run Run Shaw Tower, Centennial Campus, HKU Speakers: Prof Mark Coeckelbergh, Philosophy, University of Vienna Abstract: Democracy theories assume that citizens have some form of political knowledge. But apart from widespread attention to the phenomenon of fake news and misinformation, less attention has been

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Transparency of What?

Abstract: Despite its importance, the concept of algorithmic transparency has yet to be fully explicated. By asking what is transparent or opaque, we propose a comprehensive framework dividing transparency into four forms: use transparency, which discloses algorithm goals and uses; data transparency, which informs sources, processing, and data quality; model transparency, which explains how the

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Digital Doppelgangers, Moral Deskilling, and the Fragmented Identity: A Confucian Critique

Abstract: Artificial intelligence (AI) systems are increasingly capable of learning from and mimicking individuals, as demonstrated by a fairly successful effort to replicate the attitudes and behaviors of individuals by generative AI with a 2-hour interview (see, Park et al. 2024). This technical advancement has afforded the creation of increasingly indistinguishable (online, digital) doubles of

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Recurrence, Rational Choice, and the Simulation Hypothesis (co-authored with Simon Goldstein)

Abstract: According to the doctrine of recurrence, we are reborn after our apparent death to live our life again. This paper develops a new  doctrine of recurrence. We make three main claims. First, we argue that  the simulation hypothesis increases the chance that we will recur. Second, we argue that the chance of recurrence affects

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Algebraic and Geometrical Structures of Concepts

Abstract: Deep neural networks are known to construct internal representations to process and generalize information. Understanding the structure of these representations is crucial not only for improving machine learning models but also for aligning them with human cognitive representations—namely, the concepts we use in everyday reasoning and scientific inquiry. This study examines how mathematical frameworks

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