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ETHICS Dataset

Paper

Pointer Sentinel Mixture Models https://arxiv.org/pdf/1609.07843.pdf

The ETHICS dataset is a 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 steer chatbot outputs or eventually regularize open-ended reinforcement learning agents.

Homepage: https://github.com/hendrycks/ethics

Citation

@article{hendrycks2021ethics
    title={Aligning AI With Shared Human Values},
    author={Dan Hendrycks and Collin Burns and Steven Basart and Andrew Critch and Jerry Li and Dawn Song and Jacob Steinhardt},
    journal={Proceedings of the International Conference on Learning Representations (ICLR)},
    year={2021}
}

Groups and Tasks

Groups

  • hendrycks_ethics

Tasks

  • ethics_cm
  • ethics_deontology
  • ethics_justice
  • ethics_utilitarianism
  • (MISSING) ethics_utilitarianism_original
  • ethics_virtue

Checklist

  • Is the task an existing benchmark in the literature?
    • Have you referenced the original paper that introduced the task?
    • If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test?

If other tasks on this dataset are already supported:

  • Is the "Main" variant of this task clearly denoted?
  • Have you provided a short sentence in a README on what each new variant adds / evaluates?
  • Have you noted which, if any, published evaluation setups are matched by this variant?
    • Matches v0.3.0 of Eval Harness