# Is ETHICS about ethics? Evaluating the ETHICS benchmark

arXiv: https://arxiv.org/abs/2410.13009 · HTML: https://mlsanity.com/paper/2410.13009/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Oct 2024.

## Built on by (most cited first, 1 of 1)

- [Where Paths Split: Localized, Calibrated Control of Moral Reasoning in Large Language Models](https://mlsanity.com/paper/2605.03609/) (2026)

## Abstract (arXiv)

ETHICS is probably the most-cited dataset for testing the ethical capabilities of language models. Drawing on moral theory, psychology, and prompt evaluation, we interrogate the validity of the ETHICS benchmark. Adding to prior work, our findings suggest that having a clear understanding of ethics and how it relates to empirical phenomena is key to the validity of ethics evaluations for AI.