Data Science Wire

Agreement Is Not Alignment: Divergent Moral Grounds in Human and LLM Ethical Judgments

arXiv cs.AI1mo4 min read

arXiv:2608.12368v1 Announce Type: new Abstract: Agreement with human judgments is a common proxy for evaluating the alignment of large language models (LLMs). Yet agreement in final labels does not show that human annotators and models rely on the same moral grounds. Two agents may reach the same judgment while appealing to different principles, contextual assumptions, or interpretations of the situation. We test this distinction using a curated 500-item ETHICS-derived benchmark spanning five domains of moral judgment, with new human annotator and LLM annotations of both final labels and suppo

Read the full story at arXiv cs.AI

More in AI