Date: March 5-6, 2025 (Wednesday, Thursday) Organizer: AIH Lab Desire homuncularism – Agency, ethical standing, and skin in the game Prof Steve Petersen, Niagara University AI Zombies: Global Workspace Theory and Resource-Rational Analysis Prof Justin Tiehen, University of Puget Sound It probably doesn’t matter whether software can be made sentient Dr Andreas Mogensen, University of Oxford […]
AI Consciousness and Well-Being Read More »
Date: February 7, 2025 (Friday) Speaker: Ms Ninell Oldenburg, University of Copenhagen Chair: Dr Frank Hong, The University of Hong Kong Abstract: While most technical and philosophical research on LLMs tries to find a translation from human functions to computational principles, understanding the flip side — how computational principles translate into natural ones — is often overlooked.
Date: February 21, 2025 (Friday) Speaker: Dr Leonard Dung, Ruhr-University Bochum Chair: Dr Frank Hong, The University of Hong Kong Abstract: Does consciousness require biology or can systems made out of other materials be conscious? I develop an argument for the view that it is (nomologically) possible that some non-biological creatures are conscious, including conventional, silicon-based AI
Future science and artificial consciousness Read More »
Date: February 28, 2025 (Friday) Speaker: Prof Jeffrey Howard, University College London Chair: Dr Frank Hong, The University of Hong Kong Abstract: Social media platforms’ AI systems learn from user data to predict what content will keep users engaged. This content is subsequently amplified, increasing its visibility. Over the past years, many critics have claimed that
The Ethics of Amplification Read More »
Date: January 17, 2025 (Friday) Time: 13:00 – 18:00 Organizers: AIH Lab and Hong Kong Ethics Lab Prof Seth Lazar, Australian National University Agent Advocates: Some Questions and Issues Prof Nikolaj Jang Lee Linding Pedersen, Yonsei University AI Personhood: A Cost-sensitive Analysis Dr Yiwen Zhan, Beijing Normal University Steering Towards Utopia: The Importance of the Medium Term in AI
The Philosophy of AI: Themes from Seth Lazar Read More »
Date: February 14, 2025 (Friday) Organizers: AIH Lab, Programme on Artificial Intelligence and the Law and Hong Kong Ethics Lab A Matter of Principle? AI alignment as the Fair Treatment of Claims (co-authored with Geoffrey Keeling) Iason Gabriel, Staff Research Scientist, Google Deepmind Evaluating AI Agents for Dangerous (Cognitive) Capabilities Geoffrey Keeling, Senior Research Scientist, Google The Fair Treatment of
The Philosophy of AI: Themes from Iason Gabriel Read More »
Date: November 22, 2024 (Friday) Speaker: Ms Sarah Jeong, Journalist Chair: Dr Frank Hong, The University of Hong Kong Abstract: Generative AI is now a ubiquitous feature of consumer electronics, incorporated even into smartphone photography. As photographs and other forms of media become trivially easy to doctor, the social consensus around what documentary evidence is
What Was a Photograph? Read More »
Date: December 4, 2024 (Wednesday) Speaker: Dr Henry Shevlin, University of Cambridge Chair: Dr Frank Hong, The University of Hong Kong Organizers: AIH Lab and IDEAS-IDS Abstract: Recent rapid progress in artificial intelligence has prompted renewed interest in the possibility of consciousness in artificial systems. This talk argues that this question forces us to confront troubling methodological challenges
AI and the future of consciousness science Read More »
Date: December 7, 2024 (Saturday) Speaker: Dr Karina Vold, University of Toronto Chair: Dr Frank Hong, The University of Hong Kong Organizers: AIH Lab and IDEAS-IDS Abstract: Artificial intelligence (AI) systems are increasingly able to outperform humans at specific tasks, such as beating world champions at Go and solving 50-year-old grand challenges in biology. I argue that humans can
Epistemic opportunities: AI Systems as Cognitive Scaffolding Read More »
Date: March 26-27, 2025 (Wednesday, Thursday) Organizer: AI & Humanity Lab Recurrence, Rational Choice, and the Simulation Hypothesis Dr Frank Hong, The University of Hong Kong What’s hidden inside predictively successful deep learning models?Prof Darrell Rowbottom, Lingnan University Counterfactual Explanations in AI: A Tension between ‘Causality’ and ‘Plausibility’ Prof Jiji Zhang, The Chinese University of Hong
Philosophy of AI in Asia Workshop Read More »