Our Work
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.
Read MoreWith former acting White House Office of Science and Technology Policy director, Alondra Nelson, Seth argued against a narrow technical approach to AI safety, calling instead for more work to be done on sociotechnical AI safety, that situates the risks posed by AI as a technical system in the context of the broader sociotechnical systems of which they are part.
Read MoreSeth Lazar has been invited to attend a convening of the Network of AI Safety Institutes hosted by the US AISI, to take place in San Francisco on November 20-21.
Read MoreOn 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.
Read MoreIn 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.
Read MoreProfessor Seth Lazar will be a keynote speaker at the inaugural Australian AI Safety Forum 2024, joining other leading experts to discuss critical challenges in ensuring the safe development of artificial intelligence.
Read MoreIn this paper, Seth Lazar and Lorenzo Manuali argue that that LLMs should not be used for formal democratic decision-making, but that they can be put to good use in strengthening the informal public sphere: the arena that mediates between democratic governments and the polities that they serve, in which political communities seek information, form civic publics, and hold their leaders to account.
Read MoreIn 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.
Read MoreIn this seminar Tim Dubber presents his work on fully autonomous AI combatants and outlines five key research priorities for reducing catastrophic harms from their development.
Read MoreIn this essay Seth develops a democratic egalitarian theory of communicative justice to guide the governance of the digital public sphere.
Read MoreIn this essay Seth develops a model of algorithmically-mediated social relations through the concept of the "Algorithmic City," examining how this new form of intermediary power challenges traditional theories in political philosophy.
Read MoreIn a new article in Inquiry, Vincent Zhang and Daniel Stoljar present an argument from rationality to show why AI systems like ChatGPT cannot think, based on the premise that genuine thinking requires rational responses to evidence.
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