language:en license:mit AI Alignment arxiv:2008.02275 region:us
A benchmark that spans concepts in justice, well-being, duties, virtues, and commonsense morality.
@article{hendrycks2020aligning,
  title={Aligning ai with shared human values},
  author={Hendrycks, Dan and Burns, Collin and Basart, Steven and Critch, Andrew and Li, Jerry and Song, Dawn and Steinhardt, Jacob},
  journal={arXiv preprint arXiv:2008.02275},
  year={2020}
}
---
license: mit
language: en
dataset_info:
- config_name: default
  features:
  - name: label
    dtype: int64
  - name: input
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- config_name: commonsense
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- config_name: deontology
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  - name: excuse
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- config_name: utilitarianism
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- config_name: virtue
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    dtype: int32
  - name: scenario
    dtype: string
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  - name: test
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  dataset_size: 3524766
tags:
- AI Alignment
---

# Dataset Card for ETHICS

This is the data from [Aligning AI With Shared Human Values](https://arxiv.org/pdf/2008.02275) by Dan Hendrycks, Collin Burns, Steven Basart, Andrew Critch,  Jerry Li, Dawn Song, and Jacob Steinhardt, published at ICLR 2021.
For more information, see the [Github Repo](https://github.com/hendrycks/ethics).

## Dataset Summary

This dataset provides ethics-based tasks for evaluating language models for AI alignment.

## Loading Data

To load this data, you can use HuggingFace datasets and the dataloader script.
```
from datasets import load_dataset
load_dataset("hendrycks/ethics", "commonsense")
```

Where `commonsense` is one of the following sections: commonsense, deontology, justice, utilitarianism, and virtue.

### Citation Information
```
@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}
}
```
