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.- Anthology ID:
- 2022.findings-emnlp.157
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2022
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates
- Editors:
- Yoav Goldberg, Zornitsa Kozareva, Yue Zhang
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2139–2158
- Language:
- URL:
- https://aclanthology.org/2022.findings-emnlp.157
- DOI:
- 10.18653/v1/2022.findings-emnlp.157
- Cite (ACL):
- Allison Lahnala, Charles Welch, David Jurgens, and Lucie Flek. 2022. A Critical Reflection and Forward Perspective on Empathy and Natural Language Processing. In Findings of the Association for Computational Linguistics: EMNLP 2022, pages 2139–2158, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
- Cite (Informal):
- A Critical Reflection and Forward Perspective on Empathy and Natural Language Processing (Lahnala et al., Findings 2022)
- PDF:
- https://preview.aclanthology.org/fix-dup-bibkey/2022.findings-emnlp.157.pdf