Taking AI Welfare Seriously with Jeff Sebo
In this interview Jeff Sebo discusses the ethical implications of artificial intelligence and why we must take the possibility of AI sentience seriously now. He explores challenges in measuring moral significance, the risks of dismissing AI as mere tools, and strategies to mitigate suffering in artificial systems. Drawing on themes from the paper ‘Taking AI Welfare Seriously’ and his up and coming book ‘The Moral Circle’, Sebo examines how to detect markers of sentience in AI systems, and what to do about it. We explore ethical considerations through the lens of population ethics, AI governance (especially important in an AI arms race), and discuss indirect approaches detecting sentience, as well as AI aiding in human welfare. This rigorous conversation probes the foundations of consciousness, moral relevance, and the future of ethical AI design.
‘Taking AI Welfare Seriously’ Paper
Link: https://arxiv.org/html/2411.00986v1
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.
