Evaluation Cards for XAI Metrics
For researchers in explainable AI, this is an incremental proposal for a documentation standard to improve evaluation reporting.
The paper tackles the lack of standardization in evaluating XAI methods by proposing the XAI Evaluation Card, a documentation template for reporting evaluation metrics. It aims to reduce fragmentation and improve accountability, but no concrete results or numbers are provided.
The evaluation of explainable AI (XAI) methods is affected by a lack of standardization. Metrics are inconsistently defined, incompletely reported, and rarely validated against common baselines. In this paper, we identify transparency of evaluation reporting as a central, under-addressed problem. We propose the XAI Evaluation Card, a documentation template analogous to model cards, designed to accompany any study that introduces an XAI evaluation metric. The card covers explicit declaration of target properties, grounding levels, metric assumptions, validation evidence, gaming risks, and known failure cases. We argue that adopting this template as a community norm would reduce evaluation fragmentation, support meta-analysis, and improve accountability in XAI research.