# Mapping Topics in 100,000 Real-life Moral Dilemmas

arXiv: https://arxiv.org/abs/2203.16762 · HTML: https://mlsanity.com/paper/2203.16762/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Mar 2022.

## Built on by (most cited first, 10 of 10)

- [Normative Evaluation of Large Language Models with Everyday Moral Dilemmas](https://mlsanity.com/paper/2501.18081/) (2025)
- [Author as Character and Narrator: Deconstructing Personal Narratives from the r/AmITheAsshole Reddit Community](https://mlsanity.com/paper/2301.08104/) (2023)
- [Beyond Human Judgment: A Bayesian Evaluation of LLMs' Moral Values Understanding](https://mlsanity.com/paper/2508.13804/) (2025)
- [The Moral Gap of Large Language Models](https://mlsanity.com/paper/2507.18523/) (2025)
- [Growth First, Care Second? Tracing the Landscape of LLM Value Preferences in Everyday Dilemmas](https://mlsanity.com/paper/2602.04456/) (2026)
- [Moral Semantics Survive Machine Translation: Cross-Lingual Evidence from Moral Foundations Corpora](https://mlsanity.com/paper/2605.22660/) (2026)
- [D2VBench: Benchmarking Large Language Models with Value Dilemmas in Daily Scenarios](https://mlsanity.com/paper/2607.19834/) (2026)
- [Moral Sparks in Social Media Narratives](https://mlsanity.com/paper/2310.19268/) (2023)
- [BenSyc: Benchmarking Conversational Sycophancy and Human Alignment in LLMs for Bengali Contexts](https://mlsanity.com/paper/2606.10061/) (2026)
- [Follow the Norm: Accounting for Fine-Tuning and Prompt Effects on Model Rationales](https://mlsanity.com/paper/2608.13250/) (2026)

## Abstract (arXiv)

Moral dilemmas play an important role in theorizing both about ethical norms and moral psychology. Yet thought experiments borrowed from the philosophical literature often lack the nuances and complexity of real life. We leverage 100,000 threads -- the largest collection to date -- from Reddit's r/AmItheAsshole to examine the features of everyday moral dilemmas. Combining topic modeling with evaluation from both expert and crowd-sourced workers, we discover 47 finer-grained, meaningful topics and group them into five meta-categories. We show that most dilemmas combine at least two topics, such as family and money. We also observe that the pattern of topic co-occurrence carries interesting information about the structure of everyday moral concerns: for example, the generation of moral dilemmas from nominally neutral topics, and interaction effects in which final verdicts do not line up with the moral concerns in the original stories in any simple way. Our analysis demonstrates the utility of a fine-grained data-driven approach to online moral dilemmas, and provides a valuable resource for researchers aiming to explore the intersection of practical and theoretical ethics.