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***** This event will be held on Friday at 8 am AWST Aug 28th due to an American guest. No Thursday night this week *****

How good are current machine learning models at morality? Can they extrapolate? Where are the weak points?

Our guest speaker, Daniel Hendrycks will talk and answer questions about the paper he is co-author on: "Aligning AI With Shared Human Values" (https://arxiv.org/abs/2008.02275, https://github.com/hendrycks/ethics).

In the paper they introduce an ethics datasets and test GPT-3 and other models on it. Finding out how well models do at different kinds of morality. It's a small but important step towards aligning AI with human values, and the findings and dataset are very interesting.

Abstract:
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 morality. Models predict widespread moral judgments about diverse text scenarios. This requires connecting physical and social world knowledge to value judgements, a capability that may enable us to filter out needlessly inflammatory chatbot outputs or eventually regularize open-ended reinforcement learning agents. With the ETHICS dataset, we find that current language models have a promising but incomplete understanding of basic ethical knowledge. Our work shows that progress can be made on machine ethics today, and it provides a steppingstone toward AI that is aligned with human values.

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