Next Steps for AI Welfare Research

Now that more researchers are starting to take AI welfare seriously, the field faces the question of what comes next. This talk identifies three broad priorities: developing empirical methods for studying evidence of consciousness, sentience, and agency in AI systems; tracking expert and public attitudes as AI systems become more advanced and widespread; and designing governance frameworks that can address AI welfare alongside AI safety. In each area, progress requires conceptual, scientific, ethical, and political clarity: markers for welfare-relevant capacities, evidence-sensitive probability estimates, longitudinal studies of social attitudes, and policy models for rights, personhood, citizenship, and integrated safety-welfare governance. The talk will survey emerging work in these areas and suggest promising directions for building AI welfare research into a rigorous, multidisciplinary, and policy-relevant field.