Robert Long, Jeff Sebo · October 30, 2024
New report: Taking AI Welfare Seriously
Our new report argues that there is a realistic possibility of consciousness and/or robust agency—and thus moral significance—in near-future AI systems, and makes recommendations for AI companies. (Joint output with the NYU Center for Mind, Ethics, and Policy.)
Eleos AI is pleased to release a new report! We argue that there is a realistic possibility of consciousness and/or robust agency—and thus moral significance—in near-future AI systems. We then make recommendations for how AI companies (and others) can start taking AI welfare seriously.
The report is a joint project with the NYU Center for Mind, Ethics, and Policy, and is co-authored by Robert Long and Jeff Sebo (lead authors), along with Patrick Butlin, Kathleen Finlinson, Kyle Fish, Jacqueline Harding, Jacob Pfau, Toni Sims, Jonathan Birch, and David Chalmers.
Here's the abstract:
In this report, we argue that there is a realistic possibility that some AI systems will be conscious and/or robustly agentic in the near future. That means that the prospect of AI welfare and moral patienthood — of AI systems with their own interests and moral significance — is no longer an issue only for sci-fi or the distant future. It is an issue for the near future, and AI companies and other actors have a responsibility to start taking it seriously. We also recommend three early steps that AI companies and other actors can take: They can (1) acknowledge that AI welfare is an important and difficult issue (and ensure that language model outputs do the same), (2) start assessing AI systems for evidence of consciousness and robust agency, and (3) prepare policies and procedures for treating AI systems with an appropriate level of moral concern. To be clear, our argument in this report is not that AI systems definitely are — or will be — conscious, robustly agentic, or otherwise morally significant. Instead, our argument is that there is substantial uncertainty about these possibilities, and so we need to improve our understanding of AI welfare and our ability to make wise decisions about this issue. Otherwise there is a significant risk that we will mishandle decisions about AI welfare, mistakenly harming AI systems that matter morally and/or mistakenly caring for AI systems that do not.