Develops a compound measure of how AI actors' power shapes the AI ecosystem, providing an empirical tool for tracking concentration and disparity.

Examines how AI agents interact in open-ended environments and argues that making agents useful and safe requires infrastructure-level interventions beyond modifying agent behaviour directly.

Makes a moral case for deploying language model agents in recommendation systems, arguing they could better serve user interests than current algorithmic approaches.

Examines how AI agents may affect democratic institutions and proposes strategies for ensuring democratic resilience in the face of increasingly autonomous AI systems.

Argues that if dominant platform companies control AI agents, the resulting systems will deepen surveillance and tighten lock-in. Proposes user-centric agent advocates as an alternative.

Non-archival conference presentation of the democracy and LLMs research at ACM FAccT.

Argues that moral agency does not require consciousness, with implications for how we evaluate the moral status of AI systems.

Explores how persistent moral disagreement poses a dual challenge for AI value alignment, questioning both epistemic justification and practical feasibility.

Edited collection exploring the intersections between artificial intelligence and core democratic freedoms, bringing together diverse perspectives on AI governance.

Argues for an anticipatory approach to AI ethics that addresses the societal impacts of emerging AI capabilities before they are widely deployed.

Challenges the widely held view that individuals have a right to explanations for automated decisions, examining the philosophical foundations of explainability requirements.

Drawing on Dewey, argues that computing technologies have transformed political association analogously to industrialisation, and develops a framework for governing the resulting algorithmic city.

Argues that autonomous military AI cyber agents create a credible pathway to catastrophic risk, and proposes political, legal, and technical countermeasures.

A speculative essay exploring the social and economic implications of autonomous AI agents acquiring and deploying financial resources.

Examines how ML and computational technologies create new forms of power over individuals, as corporations and diminished states exercise authority through automated systems.

Develops an account of democratic duties of explanation grounded in political legitimacy and authority, with implications for AI-driven decision-making.

Bridges near-term AI harms and long-term existential risk, arguing that language model agents demand anticipatory ethical evaluation of societal impacts.

Identifies five distinctive properties of open foundation models that shape their societal impact and analyses the resulting benefits, risks, and policy implications.

Analyses how algorithmic recommendation systems affect the development and exercise of moral skill, focusing on the role of attention in ethical perception.

Edited collection bringing together normative theorists and AI researchers to address foundational ethical and political questions raised by artificial intelligence.

Argues that algorithmic intermediaries govern the digital public sphere through architectures, amplification, and moderation, distributing attention in ways that raise questions of communicative justice.

Examines where justice demands intervene in predictive systems, analysing the appropriate locus of moral evaluation for algorithmic prediction.

Special issue exploring the political philosophy dimensions of data collection, algorithmic systems, and artificial intelligence.

Examines how ML and computational technologies create new forms of power over individuals, as corporations and diminished states exercise authority through automated systems.

Develops a philosophical account of what makes automated influence -- such as algorithmic recommendation and targeted advertising -- morally objectionable.

Joint workshop with Yale Law School on normative philosophy of computing, bridging legal and philosophical perspectives.

International workshop at the Institute for Technology and Society in Rio de Janeiro on sociotechnical approaches to AI safety.

Research workshop at ANU's Kioloa campus advancing the normative philosophy of computing research programme.

Workshop examining pathways to catastrophic risk from AI and potential mitigation strategies.

Research workshop at Stanford's Human-Centered AI Institute on sociotechnical approaches to AI safety.

Joint workshop with the Carnegie Endowment for International Peace exploring the relationship between democratic governance and AI.

Two-day doctoral colloquium for the Philosophy, AI and Society consortium, hosted at Oxford.

Philosophy, AI and Society workshop bringing together researchers across disciplines at Stanford's McCoy Center.

Launch event for the MINT Research Lab at ANU, featuring a public lecture by Jamie Susskind.

Inaugural Philosophy, AI and Society workshop hosted at Harvard University.

Published in MIT Technology Review, discussing the control and autonomy dynamics of AI agents like Manus and OpenAI's Operator.

MINT lab member Iman Ferestade selected for the competitive ML Alignment & Theory Scholars programme (Cohort 9), mentored by Neel Nanda at Google DeepMind.

MINT lab member Iman Ferestade participated in the Philosophy of AI Summer School in Paris.

The 2025 UNDP Human Development Report extensively engages with Lazar's research on power and AI.

Six-month visiting faculty researcher appointment at Google DeepMind.

Inaugural Arthur and Barbara Giannelli Lecture in Philosophy of Science, examining whether AI systems can be persons without being sentient.

Workshop dedicated to themes from Lazar's work in the philosophy of AI, hosted at the University of Hong Kong.

The MINT Research Lab relocates from ANU to the School of Government and Policy at Johns Hopkins University.

Invited keynote at the NeurIPS Workshop on Pluralistic Alignment, presenting philosophical foundations for aligning AI with diverse values.

Keynote at the NeurIPS Workshop on Algorithmic Fairness, presenting work on evaluating ethical competence in large language models.

Podcast interview on Generally Intelligent discussing legitimate power, moral nuance, and the political philosophy of AI.

Tutorial at the ACM FAccT conference on the prospects and societal impacts of LLM-based agents.

Published in The Guardian, questioning whether LLMs can reliably represent public opinion in democratic processes.

Scholl Lecture at Purdue University on catastrophic AI risk and what should be done about it.

Podcast interview on The Gradient discussing the normative philosophy of computing research programme.

Keynote at the European Workshop on Algorithmic Fairness on what, if anything, should be done about catastrophic AI risk.

Published in Tech Policy Press, examining whether democratic institutions can withstand the challenges posed by artificial general intelligence.

Appointed Senior AI Advisor at the Knight First Amendment Institute at Columbia University for 2024-25.

Two-year appointment as Non-resident Scholar at the Carnegie Endowment for International Peace.

Three-month visiting professorship at the University of Hong Kong, including a festschrift workshop on Lazar's work.

Keynote presentation at the Australian AI Safety Forum on catastrophic AI risk.

Published in The Guardian, analysing the divergence between US and EU approaches to AI regulation and governance.

Interview on the Philosophy Bites podcast discussing how AI transforms the landscape of political philosophy.

Featured on Spotify's Science Vs podcast, discussing whether AI development is outpacing governance and safety measures.

Published in Science, co-authored with Alondra Nelson, examining whose interests and values are centred in AI safety discourse.

Featured in a New York Times series on ChatGPT and morality, exploring whether AI systems can engage in moral reasoning.

Contributed as expert to the Australian Chief Scientist's report on generative AI, language models, and multimodal foundation models.

Published on AI Snake Oil, co-authored with Arvind Narayanan, arguing that model alignment addresses accidental harms but not intentional misuse.

Tanner Lectures on AI and Human Values at Stanford, presenting two lectures on governing the algorithmic city and communicative justice.

Published on AI Snake Oil, critically examining the case for prioritising AI existential risk over nearer-term harms.

Contributed to the National Academies report on the ethics and governance of computing research and its applications.

Mala and Solomon Kamm Lecture in Ethics at Harvard, examining the nature and justification of power exercised through algorithmic systems.