Abstract
The current status quo of explainable AI makes use of prefabricated explanations to enable users to gain insights into an AI-based system’s underlying decision-making logic, thereby increasing users’ system understanding. In contrast, we introduce an established method from the field of generative learning called self-explanation: Rather than passively processing existing explanations, the recipient is integrated into the explanation generation process and (to different degrees) generates their own explanations. We performed an experiment to investigate the effects of such self-explanations (with various levels of contextual information) on system understanding (operationalized through explainability, transparency, predictability) and cognitive load. Our findings suggest that recipient-generated self-explanations can be effective at increasing system understanding, providing an effective alternative to the current status quo with comparable mental load.
Paper Type
Full Paper
DOI
10.62036/ISD.2026.76
Just Explain It to Yourself: On Integrating Self-Explanations into Explainable AI
The current status quo of explainable AI makes use of prefabricated explanations to enable users to gain insights into an AI-based system’s underlying decision-making logic, thereby increasing users’ system understanding. In contrast, we introduce an established method from the field of generative learning called self-explanation: Rather than passively processing existing explanations, the recipient is integrated into the explanation generation process and (to different degrees) generates their own explanations. We performed an experiment to investigate the effects of such self-explanations (with various levels of contextual information) on system understanding (operationalized through explainability, transparency, predictability) and cognitive load. Our findings suggest that recipient-generated self-explanations can be effective at increasing system understanding, providing an effective alternative to the current status quo with comparable mental load.
Recommended Citation
de Zoeten, M., Ernst, C.P.H., Staegemann, D. & Rothlauf, F.(2026). Just Explain It to Yourself: On Integrating Self-Explanations into Explainable AI. In M. Valenta, B. Mannová, R. Pergl, A. Przybylek, M. Lang, H. Linger, C. Schneider, N. Iivari, & E. Insfran (Eds.), Making ISD Sustainable: Reloaded with AI and Automation (ISD2026 Proceedings). Prague, Czech Republic: Czech Technical University in Prague. ISBN: 978-80-01-07585-2. https://doi.org/10.62036/ISD.2026.76