In 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.

In this essay Seth develops a democratic egalitarian theory of communicative justice to guide the governance of the digital public sphere.

The UK government is considering the use of Large Language Models to summarise and analyse submissions during public consultations. Seth weighs in on the considerations behind such a suggestion for the Guardian.

In a forthcoming paper in the ACM Journal on Responsible Computing Jake Stone and Brent Mittelstadt consider how we ought to legitimate automated decision making.

In a forthcoming paper in AI & Society Sean Donahue argues that while common objections to epistocracy may not apply to AI governance, epistocracy remains fundamentally flawed.

On December 9 Seth gave a talk entitled 'Evaluating LLM Ethical Competence' at the HKU workshop on Linguistic and Cognitive Capacities of LLMs.

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.

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.

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.

On 23 March 2024 Nick Schuster presented his paper “Role-Taking Skill and Online Marginalization” (co-authored by Jenny Davis) at the American Philosophical Association's 2024 Pacific Division Meeting in Portland, Oregon.

Our special issue of Philosophical Studies on Normative Theory and AI is now live. A couple more papers remain to come, but in the meantime you can find eight new papers on AI and normative theory here:

Seth Lazar and lead author Nick Schuster published a paper on algorithmic recommendation in Philosophical Studies.

On 18 September 2023 Nick Schuster presented his paper “Role-Taking Skill and Online Marginalization” (co-authored by Jenny Davis) at the University of Leeds.

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.

This week, Harriet Farlow and Tania Sadhani presented their framework for analyzing AI incident likelihood. Developed through a collaboration between Mileva Security Labs, ANU MINT Lab, and UNSW, with funding from Foresight, their work aims to bridge short and long-term AI risks through practical quantification methods.

Seth 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.

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.

In a new paper in Philosophical Studies MINT Lab affiliate David Thorstad critically examines the singularity hypothesis. Thorstad argues that this popular concept relies on insufficiently supported growth assumptions. The study explores the philosophical and policy implications of this critique, contributing to ongoing debates about the future trajectory of AI development.