See What I Mean? CUE: A Cognitive Model of Understanding Explanations
Tobias Labarta, Nhi Hoang, Katharina Weitz, Wojciech Samek, Sebastian Lapuschkin, Leander Weber

TL;DR
This paper introduces CUE, a cognitive model linking explanation features to human understanding processes, and provides empirical evidence on how explanation design impacts users, especially those with visual impairments.
Contribution
It presents a formal cognitive model of explanation understanding, defines human-centered explanation properties, and offers empirical insights into accessible XAI design.
Findings
Visual impairments affect confidence and effort in understanding explanations.
Color maps designed for accessibility may not improve, and can worsen, understanding.
Altering explanation legibility influences interpretability and comprehension.
Abstract
As machine learning systems increasingly inform critical decisions, the need for human-understandable explanations grows. Current evaluations of Explainable AI (XAI) often prioritize technical fidelity over cognitive accessibility which critically affects users, in particular those with visual impairments. We propose CUE, a model for Cognitive Understanding of Explanations, linking explanation properties to cognitive sub-processes: legibility (perception), readability (comprehension), and interpretability (interpretation). In a study (N=455) testing heatmaps with varying colormaps (BWR, Cividis, Coolwarm), we found comparable task performance but lower confidence/effort for visually impaired users. Unlike expected, these gaps were not mitigated and sometimes worsened by accessibility-focused color maps like Cividis. These results challenge assumptions about perceptual optimization and…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsTopic Modeling · Explainable Artificial Intelligence (XAI) · Semantic Web and Ontologies
