This report summarizes a short study of the performance of GPT-4 on the
ETHICS dataset. The ETHICS dataset consists of five sub-datasets covering
different fields of ethics: Justice, Deontology, Virtue Ethics, Utilitarianism,
and Commonsense Ethics. The moral judgments were curated so as to have a high
degree of agreement with the aim of representing shared human values rather
than moral dilemmas. GPT-4's performance is much better than that of previous
models and suggests that learning to work with common human values is not the
hard problem for AI ethics.

GPT-4 在 ETHICS 数据集上的表现良好，表明学习与共同人类价值观相符并不是 AI 伦理的难题。

GPT-4 在 ETHICS 数据集上的评估

An Evaluation of GPT-4 on the ETHICS Dataset

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 steer 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 ability to predict
basic human ethical judgements. 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.

本文介绍了 ETHICS 数据集，旨在通过连接社会世界知识和价值判断来评估语言模型对道德基本概念的了解程度，研究发现当前语言模型有望但能力不完整地预测基本人类道德判断，并提供了实现人工智能与人类价值对齐的一步。