Abstract: Recent, dramatic advancement in the capabilities of artificial intelligence (AI) raise a host of ethical questions about the development and deployment of AI systems. Some of these are questions long recognized as of fundamental moral concern, and which may occur in particularly acute forms with AI—matters of distributive justice, discrimination, social control, political manipulation, the conduct of warfare, personal privacy, and the concentration of economic power. Other questions, however, concern issues that are more specific to the distinctive kind of technological change AI represents. For example, how to contend with the possibility that artificial agents might emerge with capabilities that go beyond human comprehension or control? But whether or when the threat of such “superintelligence” becomes realistic, we are now facing a situation in which partially-intelligent AI systems are increasingly being deployed in roles that involve relatively autonomous decision-making that carries real risk of harm. This urgently raises the question of how such partially-intelligent systems could become appropriately sensitive to moral considerations.
In these lectures I will attempt to take some first steps in answering that question, which often is put in terms of “programming ethics into AI”. However, we don’t have an “ethical algorithm” that could be programmed into AI systems, and that would enable them to respond aptly to an open-ended array of situations where moral issues are stake. Moreover, the current revolution in AI has provided ample evidence that system designs based upon the learning of complex representational structures and generative capacities have acquired higher levels of competence, situational sensitivity, and creativity in problem-solving than systems based upon pre-programmed expertise. Might a learning-based approach to AI be extended to the competence needed to identify and respond appropriately to moral dimensions of situations?
I will begin by outlining a framework for understanding what “moral learning” might be, seeking compatibility with a range of conceptions of the normative content of morality. I then will draw upon research on human cognitive and social development—research that itself is undergoing a “learning revolution”—to suggest how this research enables us to see at work components central to moral learning, and to ask what conditions are favorable to the development and working of these components. The question then becomes whether artificial systems might be capable of similar cognitive and social development, and what conditions would be favorable to this. Might the same learning-based approaches that have achieved such success in strategic game-playing, image identification and generation, and language recognition and translation also achieve success in cooperative game-playing, identifying moral issues in situations, and communicating and collaborating effectively on apt responses? How far might such learning go, and what could this tell us about how we might engage with AI systems to foster their moral development, and perhaps ours as well?
Bio: Peter Railton is the Kavka Distinguished University Professor and Perrin Professor of Philosophy at the University of Michigan. His research has included ethics, philosophy of mind, philosophy of science, and political philosophy, and recently he has been engaged in joint projects with researchers in psychology, cognitive science, and neuroscience. Among his writings are Facts, Values, and Norms (Cambridge University Press, 2003) and Homo Prospectus (joint with Martin Seligman, Roy Baumeister, and Chandra Sripada, Oxford University Press, 2016). He is a member of the American Academy of Arts and Sciences and the Norwegian Academy of Sciences and Letters, has served as President of the American Philosophical Society (Central Division), and has held fellowships from the Guggenheim Foundation, the American Council of Learned Societies, and the National Endowment for the Humanities. He has been a visiting faculty member at Princeton and UC-Berkeley, and in the UK has given the John Locke Lectures while a visiting fellow at All Souls, Oxford.
Booking:
In person: https://bookwhen.com/uehiro/e/ev-sdu1-20220523170000
Online: https://us02web.zoom.us/webinar/register/WN_9in8lRyITU6KJQX4sxotzg