This project will examine whether and how biological and artificial systems can be compared on a common welfare scale. As a CMEP-Rethink Priorities collaboration within the broader Moral Weight Project 2.0, it will assess substrate-general theories of welfare intensity, evaluate compute and related intersubstrate metrics, and map structural disanalogies that complicate comparisons between animal and artificial minds.
About the project
This project will develop an interdisciplinary framework for assessing whether and how welfare ranges can be compared across biological and artificial systems. It will constitute a section of Rethink Priorities’ broader Moral Weight Project 2.0 and will be conducted as a collaboration between the NYU Center for Mind, Ethics, and Policy and Rethink Priorities. Jeff Sebo (CMEP) and Bob Fischer (RP) will lead the research, and CMEP will provide project management.
First, the report will examine which theories of the intensity of valenced experience are substrate-general. Some theories characterize intensity functionally—for example, through attentional capture, motivational salience, or effects on decision-making—and might therefore apply to biological and artificial systems alike. Other theories depend on particular biological implementations, such as the extent of neural recruitment. We will classify candidate theories by their substrate portability and, for portable theories, identify possible artificial analogues of their indicators and assess whether those indicators can be measured.
Second, the report will assess theory-light or theory-neutral intersubstrate metrics. It will examine whether metrics related to compute, information processing, or system complexity track anything relevant to welfare range rather than merely tracking task capability. It will also analyze the functional-form problem: whether welfare range should scale concavely, linearly, or convexly with a candidate metric. Since frontier AI systems can exceed biological systems on some computational measures by large margins, assumptions about these issues and their interactions can radically affect resulting comparisons.
Third, the report will map structural disanalogies that complicate intersubstrate welfare comparisons. These include uncertainty about the relevant subject of welfare—a model, a model-persona, an instance, an instance-persona, a forward pass, or other possibilities—as well as uncertainty about whether processing speed, parallelism, psychological continuity, or other such features should affect estimates of how much welfare an entity can have at a time or over time. The report will explain how these uncertainties bear on whether and how to place biological and artificial systems on a common welfare range scale.
The resulting report will be one component of Moral Weight Project 2.0, which more broadly examines hedonic and non-hedonic welfare ranges, aggregation across theories, theory-neutral metrics, and the responsible interpretation of moral weight estimates. Our component will connect that broader framework with emerging research on AI consciousness, sentience, agency, welfare, and moral status.
Theory of change
This project advances AI safety by clarifying how we should reason about the welfare and moral status of increasingly capable AI systems under deep uncertainty. By assessing which welfare-relevant properties and metrics extend across substrates, the report will identify tools that help developers and policymakers avoid both over-allocation and under-allocation of moral concern to AI. Clear, calibrated frameworks can reduce ambiguity, improve accountability, and support more responsible development and deployment of advanced AI.
The project also advances AI welfare by developing rigorous, transparent methods for estimating and comparing the welfare of AI systems that could one day have morally significant experiences or preferences. By adapting tools from animal welfare science, the report will identify which theories of experience and which metrics can place animal and digital minds on a common scale. This supports more thoughtful engagement with the moral status of AI, again striking a balance between over-allocation and under-allocation of moral concern.
Your role
We would be excited for mentees to contribute in a variety of ways depending on their backgrounds and interests. For example, they can research particular theories, indicators, metrics, or structural disanalogies and produce background memos; contribute to draft material; comment on other sections; assist with formal modeling or technical analysis; and help with figures, tables, references, formatting, fact checking, and copyediting. We can credit them as authors or research assistants depending on their eventual roles.
Prerequisites
Required -A clear, reference-dense writing style: This report is intended to be accessible and useful to researchers, grantmakers, policymakers, and practitioners. Mentees must be able to write accessibly while maintaining conceptual rigor and careful attribution. -Comfort with interdisciplinary work: The report will integrate philosophy, cognitive science, computer science, AI research, and decision theory. Mentees must be able to engage constructively with literatures beyond their primary discipline. -Strong research skills: Researchers must be able to identify, evaluate, and synthesize sources across empirical and conceptual fields, including academic papers, technical reports, model documentation, and relevant work on animal and AI welfare.
Preferred This is a multidisciplinary project, so we welcome expressions of interest from people with a variety of backgrounds. With that said, we would be especially excited to work with: -A researcher with a background in machine learning or computer science who can assess compute, architecture, information processing, functional indicators, and other candidate intersubstrate metrics. -A researcher with a background in philosophy, cognitive science, or neuroscience who can assess theories of valence, experiential intensity, welfare range, consciousness, sentience, and agency. -A researcher with experience in quantitative modeling or decision theory who can help analyze functional forms, uncertainty, aggregation, and the sensitivity of conclusions to competing assumptions. -A generalist who can assist with literature reviews, research memos, drafting, references, visualization, formatting, or copyediting. -Preferred for all: familiarity with the Moral Weight Project or related debates about cross-species welfare comparisons. -Preferred for all: familiarity with research on animal and/or AI consciousness, sentience, agency, welfare, and/or moral status.
Location preference
The project leads are in the Eastern Time Zone in the United States, and we would be happy to welcome mentees in other time zones as well. Mentees should ideally have some recurring availability during the US working day.
Application question(s)
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Describe a time you had to synthesize research from multiple disciplines or reason across relevantly different kinds of systems or contexts. What was challenging, and how did you approach it? (~200 words)
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Which aspect of this project most interests you, what perspective would you bring, and what would you most like to learn? (~200 words)
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List your other expected commitments during the fellowship period (employment, degree programs, other fellowships) with estimated weekly hours for each. If you finished the fellowship feeling you hadn't done your best work, what would likely be the reason? (~200 words)
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Provide a link to one or more relevant writing samples and briefly explain your role in the project. (Optional; ~50 words per project)
About the mentors
I’m a researcher at New York University’ Center for Mind, Ethics, and Policy working on questions of nonhuman sentience, consciousness, and moral standing. I’m a moral psychologist by training, and I’m interested in how people form social and moral inferences about nonhumans — both biological and artificial — and how these inferences inform consumer ethics, behavior, and policy preferences.
I hold a PhD in social psychology and an MA in linguistics, and I enjoy using mixed methods approaches -- experimental designs combined with linguistic corpus analysis or qualitative discourse analysis -- to explore both the manifest and more latent pathways by which people reason about nonhumans.
Jeff Sebo is Associate Professor of Environmental Studies, Affiliated Professor of Bioethics, Medical Ethics, Philosophy, and Law, Director of the Center for Environmental and Animal Protection, Director of the Center for Mind, Ethics, and Policy, and Co-Director of the Wild Animal Welfare Program at New York University. His research focuses on animal minds, ethics, and policy; AI minds, ethics, and policy; and global health and climate ethics and policy. He is the author of The Moral Circle and Saving Animals, Saving Ourselves and co-author of Chimpanzee Rights and Food, Animals, and the Environment. He is also an advisory board member at the Jeremy Coller Centre for Animal Sentience, an advisory board member at the Insect Welfare Research Society, an advisor at Eleos AI, and a senior affiliate at the Institute for Law & AI.
Bob Fischer is a Senior Researcher at Rethink Priorities, an Associate Professor of Philosophy at Texas State University, and the Director of the Society for the Study of Ethics & Animals. He has published widely on animal ethics, applied ethics, and epistemology, and edited Weighing Animal Welfare: Comparing Well-Being Across Species (Oxford University Press, 2024).
Toni Sims
NYU Center for Mind, Ethics, and Policy
Toni is a researcher at the NYU Center for Mind, Ethics, and Policy and the NYU Center for Environmental and Animal Protection. Previously, she worked as an editor at the Center for AI Safety, a research fellow at Longview Philanthropy, and the managing editor of Social Theory and Practice. She also worked as the director of research for Animal Charity Evaluators, where she led charity evaluations and managed two grant programs.