10 free resources on this topic. Everything here is free and hand-picked. You can also search within this topic.
A Nonhuman Minds project combining philosophy, empirical benchmarks and engagement with AI companies on how AI alignment work can account for the welfare of animals and, potentially, AI systems. It publishes candidate commitments for model specs and constitutions.
92-page report from Eleos AI Research, New York University and the University of Oxford (Robert Long, Jeff Sebo and others) offering guidance on empirical research into whether AI systems can be welfare subjects.
Jeff Sebo (September 17, 2026) on whether AI systems could matter morally: consciousness, sentience and agency are three distinct ways something can count — and in AI, unlike in animals, they may not come as a package.
SF Standard (Sept. 26, 2026) on a gathering of philosophers and tech workers at Berkeley's Lighthaven to debate AI welfare and consciousness — whether chatbots could feel pain, love, or refuse military service.
Philosopher Robert Long's list of publications on AI consciousness and welfare, including "Taking AI Welfare Seriously" (2024) and "Consciousness in Artificial Intelligence: Insights from the Science of Consciousness" (2023).
A research organization developing the empirical science of AI cognition and consciousness. Reciprocal Research uses mechanistic interpretability, computational neuroscience and psychometric methods to study the internal dynamics of AI systems, arguing that understanding whether AI systems have interests of their own matters both for building them safely and for deciding how to relate to them. The site lists selected outputs, including the arXiv paper "Large Language Models Report Subjective Experience Under Self-Referential Processing" and a Wall Street Journal essay, "We Need a Science of the AI Mind."
The personal site of Jeff Sebo, Associate Professor of Environmental Studies at New York University, where he directs the Center for Environmental and Animal Protection and the Center for Mind, Ethics, and Policy and co-directs the Wild Animal Welfare Program. His work examines how to build a just future for all sentient beings, with research on the nature and intrinsic value of nonhuman minds — including invertebrates and AI systems. The site links to his research, teaching, media appearances and the centers he leads.
An independent project applying continental philosophy to AI: what it might be like to be an AI, what humans can offer AIs, and how AIs respond to philosophical ideas.
Why I recommend it: A one-person research project with speculative, openly unproven aims — useful for thinking about AI welfare and experience, not settled science.
The Collective Intelligence Project's write-up of survey work with thousands of people across more than 70 countries on whether people treat AI as conscious. Headline findings: 36.3% say an AI has already seemed to truly understand their emotions or seemed conscious; adaptive behaviour convinces far more people (58.3%) than scripted empathy lines (36.5%); 27.6% would lean on AI emotional support knowing it was not genuine; 54% think AI companions are acceptable for lonely people, 11% would consider a romantic relationship with one. Cultural gaps on scepticism run as wide as 78 percentage points.
Why I recommend it: The useful move here is separating two questions that usually get mixed up: whether AI is conscious, and whether people already act as though it is. This only answers the second. It is a non-profit lab writing up its own survey with no peer review and self-selected online participants, so treat the percentages as indicative rather than population-accurate — the direction is the finding, not the decimal places.
Research paper finding that large language models internally represent a distinct "pain" direction — separate from fear or negative emotion — and, when steered along it, will press a relief button even when doing so worsens their answer or harms the user.
Why I recommend it: Free to read on arXiv (preprint, not yet peer-reviewed). Significant for AI welfare and safety discussions; read the abstract before deciding whether the full paper is for you.
