On the Importance and Evaluation of Narrativity in Natural Language AI Explanations
Explainable AI (XAI) aims to make the behaviour of machine learning models interpretable, yet many explanation methods remain difficult to understand. The integration of Natural Language Generation into XAI aims to deliver explanations in textual form, making them more accessible to practitioners. Current approaches, however, largely yield static lists of feature importances. Although such explanations indicate what influences the prediction, they do not explain why the prediction occurs. In this study, we draw on insights from social sciences and linguistics, and argue that XAI explanations should be presented in the form of narratives. Narrative explanations support human understanding ...
| Authors | Mateusz Cedro, David Martens |
|---|---|
| Primary category | cs.CL |
| Published | 20 April 2026 |
| Last updated at source | 20 April 2026 |
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