Towards Machine Ethics with Language Models
We show how to assess a language model’s knowledge of basic concepts of morality. We introduce the ETHICS dataset, a new benchmark that spans concepts in justice, well-being, duties, virtues, and commonsense moral judgments. Models predict widespread moral judgments about diverse written scenarios. This requires connecting physical and social world knowledge to value judgements, a capability that may later serve as a general regularizer of behavior in open-ended settings. We find that language models have low but nontrivial performance. With the ETHICS dataset, we enable meaningful progress on value learning to be made today, providing a steppingstone toward AI that is aligned with human values.
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