Peter Railton on Moral Learning and Metaethics in AI Systems

From a young age, humans are capable of developing moral competency and autonomy through experience. We begin life by constructing sophisticated moral representations of the world that allow for us to successfully navigate our way through complex social situations with sensitivity to morally relevant information and variables. This capacity for moral learning allows us to solve open-ended problems with other persons who may hold complex beliefs and preferences. As AI systems become increasingly autonomous and active in social situations involving human and non-human agents, AI moral competency via the capacity for moral learning will become more and more critical. On this episode of the AI Alignment Podcast, Peter Railton joins us to discuss the potential role of moral learning and moral epistemology in AI systems, as well as his views on metaethics.

Topics discussed in this episode include:

-Moral epistemology
-The potential relevance of metaethics to AI alignment
-The importance of moral learning in AI systems
-Peter Railton’s, Derek Parfit’s, and Peter Singer’s metaethical views

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0:00 Intro
3:05 Does metaethics matter for AI alignment?
22:49 Long-reflection considerations
26:05 Moral learning in humans
35:07 The need for moral learning in artificial intelligence
53:57 Peter Railton’s views on metaethics and his discussions with Derek Parfit
1:38:50 The need for engagement between philosophers and the AI alignment community
1:40:37 Where to find Peter’s work

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