A Critical Reflection and Forward Perspective on Empathy and Natural Language Processing

TL;DR

This paper critically reviews empathy research in NLP, highlighting definitional ambiguities and overemphasis on emotional empathy, and advocates for clearer conceptualization and operationalization to advance the field.

Contribution

It offers a comprehensive critique of current empathy research in NLP and proposes a structured framework for better conceptualization and operationalization of empathy components.

Findings

Current empathy definitions are often absent or vague.

Research overemphasizes emotional empathy, neglecting cognitive aspects.

Clarifying empathy concepts can enhance NLP applications in clinical and educational fields.

Abstract

We review the state of research on empathy in natural language processing and identify the following issues: (1) empathy definitions are absent or abstract, which (2) leads to low construct validity and reproducibility. Moreover, (3) emotional empathy is overemphasized, skewing our focus to a narrow subset of simplified tasks. We believe these issues hinder research progress and argue that current directions will benefit from a clear conceptualization that includes operationalizing cognitive empathy components. Our main objectives are to provide insight and guidance on empathy conceptualization for NLP research objectives and to encourage researchers to pursue the overlooked opportunities in this area, highly relevant, e.g., for clinical and educational sectors.