Learning Norms via Natural Language Teachings. (arXiv:2201.10556v1 [cs.AI])

To interact with humans, artificial intelligence (AI) systems must understand
our social world. Within this world norms play an important role in motivating
and guiding agents. However, very few computational theories for learning
social norms have been proposed. There also exists a long history of debate on
the distinction between what is normal (is) and what is normative (ought). Many
have argued that being capable of learning both concepts and recognizing the
difference is necessary for all social agents. This paper introduces and
demonstrates a computational approach to learning norms from natural language
text that accounts for both what is normal and what is normative. It provides a
foundation for everyday people to train AI systems about social norms.

Source: https://arxiv.org/abs/2201.10556


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