# Empathy and the Right to Be an Exception: What LLMs Can and Cannot Do

arXiv: https://arxiv.org/abs/2401.14523 · HTML: https://mlsanity.com/paper/2401.14523/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 18 references that are in the map.
- First posted on arXiv 25 Jan 2024.

## Builds on (most cited first, 2 of 2)

- [Large Language Models Fail on Trivial Alterations to Theory-of-Mind Tasks](https://mlsanity.com/paper/2302.08399/) (2023)
- [Using Sequences of Life-events to Predict Human Lives](https://mlsanity.com/paper/2306.03009/) (2023)

## Built on by (most cited first, 4 of 4)

- [Linguistic Comparison of AI- and Human-Written Responses to Online Mental Health Queries](https://mlsanity.com/paper/2504.09271/) (2025)
- [MICA: Multi-granularity Intertemporal Credit Assignment for Long-Horizon Emotional Support Dialogue](https://mlsanity.com/paper/2603.06194/) (2026)
- [Performance Gains of LLMs With Humans in a World of LLMs Versus Humans](https://mlsanity.com/paper/2505.08902/) (2025)
- [RE-LLM: Refining Empathetic Speech-LLM Responses by Integrating Emotion Nuance](https://mlsanity.com/paper/2602.10716/) (2026)

## Abstract (arXiv)

Advances in the performance of large language models (LLMs) have led some researchers to propose the emergence of theory of mind (ToM) in artificial intelligence (AI). LLMs can attribute beliefs, desires, intentions, and emotions, and they will improve in their accuracy. Rather than employing the characteristically human method of empathy, they learn to attribute mental states by recognizing linguistic patterns in a dataset that typically do not include that individual. We ask whether LLMs' inability to empathize precludes them from honoring an individual's right to be an exception, that is, from making assessments of character and predictions of behavior that reflect appropriate sensitivity to a person's individuality. Can LLMs seriously consider an individual's claim that their case is different based on internal mental states like beliefs, desires, and intentions, or are they limited to judging that case based on its similarities to others? We propose that the method of empathy has special significance for honoring the right to be an exception that is distinct from the value of predictive accuracy, at which LLMs excel. We conclude by considering whether using empathy to consider exceptional cases has intrinsic or merely practical value and we introduce conceptual and empirical avenues for advancing this investigation.