The AIH Lab and Hong Kong Ethics Lab co-hosted "The Philosophy of AI: Themes from Seth Lazar" workshop at HKU on January 17.
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On December 14 Seth Lazar gave a keynote talk to the NeurIPS workshop on Pluralistic Alignment.
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On December 14 Seth Lazar delivered a keynote talk on evaluating the ethical competence of LLMs to the NeurIPS Algorithmic Fairness through the Lens of Metrics and Evaluation workshop
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On December 9 Seth gave a talk entitled 'Evaluating LLM Ethical Competence' at the HKU workshop on Linguistic and Cognitive Capacities of LLMs.
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In this paper, Alan Chan, Kevin Wei, Sihao Huang, Nitarshan Rajkumar, Elija Perrier, Seth Lazar, Gillian K. Hadfield, Markus Anderljung investigate the infrastructure we need to bring about the benefits and manage the risks of AI Agents.
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On December 5, Seth Lazar presented at the Lingnan University Ethics of Artificial Intelligence Conference on rethinking how we evaluate LLM ethical competence. His talk critiqued current approaches focused on binary ethical judgments, arguing instead for evaluations that assess LLMs' capacity for substantive moral reasoning and justification.
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Seth wrote an article in Aeon to explain the suite of ethical issues being raised by AI agents built out of generative foundation models (Generative Agents). The essay explores the strengths and weaknesses of methods for aligning LLMs to human values, as well as the prospective societal impacts of Generative Agents from AI companions, to Attention Guardians, to universal intermediaries.
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This week Robert Long spoke to the lab about his newest paper with MINT lab affiliate Jacqueline Harding arguing that near-term AI systems may develop consciousness, requiring immediate attention to AI welfare considerations.
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In this seminar Emma argues that transformer architectures demonstrate that machine learning models cannot assimilate theoretical paradigms.
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On September 30-October 1 MINT co-organised a workshop convened by Imbue, a leading AI startup based in San Francisco, focused on assessing the prospective impacts of language model agents on society through the lens of classical liberalism.
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In this seminar Jen Semler presents her work examining why delegating moral decisions to AI systems is problematic, even when these systems can make reliable judgements.
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In this paper, Seth Lazar, Luke Thorburn, Tian Jin, and Luca Belli propose using language model agents as an alternative approach to content recommendation, suggesting that these agents could better respect user privacy and autonomy while effectively matching content to users' preferences.
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