Influence of prior and task generated emotions on XAI explanation retention and understanding

2025-05-15

AI Summary

This study investigates how prior affective states (happiness/fear) and task-elicited emotional responses influence users’ comprehension and retention of feature importance explanations in eXplainable AI (XAI). Method: Employing an affect induction paradigm, we conducted multimodal assessment—including heart rate variability (HRV), Facial Action Coding System (FACS) analysis, subjective self-reports, and risk propensity questionnaires—to quantify affective states. Contribution/Results: (1) Prior affect does not impair memory retention of explanations but induces confirmation bias in feature comprehension; (2) Task-elicited, attitude-congruent physiological arousal—specifically triggered by salient features—significantly disrupts comprehension without affecting overall memory; (3) We provide the first empirical evidence that affect differentially modulates the cognitive processing pathways underlying XAI explanation *comprehension* versus *memory*. These findings establish critical cognitive mechanisms for designing affect-aware XAI systems.

Technology Category

• Humans and AI: Explainable AI (XAI) for Human Understanding
• Cognitive Modeling & Cognitive Systems: Affective Computing
• Philosophy and Ethics of AI: Accountability, Interpretability & Explainability

Application Category

• User Modeling, Personalization and Recommendation: Explainable and interpretable methods for personalization
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Search and Retrieval-Augmented AI: Web query analysis, representation and understanding

Abstract

The explanation of AI results and how they are received by users is an increasingly active research field. However, there is a surprising lack of knowledge about how social factors such as emotions affect the process of explanation by a decision support system (DSS). While previous research has shown effects of emotions on DSS supported decision-making, it remains unknown in how far emotions affect cognitive processing during an explanation. In this study, we, therefore, investigated the influence of prior emotions and task-related arousal on the retention and understanding of explained feature relevance. To investigate the influence of prior emotions, we induced happiness and fear prior to the decision support interaction. Before emotion induction, user characteristics to assess their risk type were collected via a questionnaire. To identify emotional reactions to the explanations of the relevance of different features, we observed heart rate variability (HRV), facial expressions, and self-reported emotions of the explainee while observing and listening to the explanation and assessed their retention of the features as well as their influence on the outcome of the decision task. Results indicate that (1) task-unrelated prior emotions do not affected the ratantion but may affect the understanding of the relevance of certain features in the sense of an emotion-induced confirmation bias, (2) certain features related to personal attitudes yielded arousal in individual participants, (3) this arousal affected the understanding of these variables.

Problem

• How prior emotions impact XAI explanation retention
• Effect of task-related arousal on feature understanding
• Role of emotions in cognitive processing during XAI explanations

Innovation

• Induced happiness and fear for emotion analysis
• Measured heart rate variability and facial expressions
• Assessed retention and understanding via questionnaires