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

TL;DR

The paper investigates whether large language models can honor the right to be an exception by assessing how they attribute mental states and predict behavior. It contrasts three assessment modalities—correlational prediction, theory-based assessment, and empathy—and argues that empathy, though uniquely human, carries moral significance beyond predictive accuracy. The authors review recent ToM-related work and highlight a persistent 'empathy gap' between AI and human judgment, questioning the sufficiency of ToM-like capabilities for fair exception handling. They conclude that while LLMs may approximate some aspects of empathetic reasoning, the method of consideration matters and propose empirical and normative avenues to explore intrinsic value of empathic assessment.

Abstract

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.