Aristotelian Virtue Profiling of LLMs through Ethical Dilemmas
Large Language Models (LLMs) often face ethical tradeoffs in which several responses may be defensible but express different priorities, such as fairness, honesty, courage, or restraint. We introduce VirtueMap, a framework for describing these patterns through an Aristotelian virtue-ethics lens. Instead of asking for a single correct answer, VirtueMap asks humans or LLMs to rank all five responses to each of seven general, non-lethal, non-political, and non-religious ethical dilemmas. To define the reference orderings used for scoring, we first proposed, for each dilemma and virtue, an ordering of the five responses from most to least expressive of that virtue. We then collected more than...
| Authors | Ioannis Tzachristas, John Pavlopoulos |
|---|---|
| Primary category | cs.AI |
| Published | 27 June 2026 |
| Last updated at source | 27 June 2026 |
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