Designing Explainable and Counterfactual-Based AI Interfaces for Operators in Process Industries

Yanqing Zhang, Leila Methnani, Emmanuel Brorsson, Elmira Zohrevandi, Andreas Darnell, Kostiantyn Kucher

2025

Abstract

Industrial applications of Artificial Intelligence (AI) can be hindered by the issues of explainability and trust from end users. Human-computer interaction and eXplainable AI (XAI) concerns become imperative in such scenarios. However, the prior evidence of applying more general principles and techniques in specialized industrial scenarios is often limited. In this case study, we focus on designing interactive interfaces of XAI solutions for operators in the pulp and paper industry. The explanation techniques supported and compared include counterfactual and feature importance explanations. We applied the user-centered design methodology, including the analysis of requirements elicited from operators during site visits and interactive interface prototype evaluation eventually conducted on site with five operators. Our results indicate that the operators preferred the combination of counterfactual and feature importance explanations. The study also provides lessons learned for researchers and practitioners.

Paper Citation

in Harvard Style

Zhang Y., Methnani L., Brorsson E., Zohrevandi E., Darnell A. and Kucher K. (2025). Designing Explainable and Counterfactual-Based AI Interfaces for Operators in Process Industries. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: IVAPP; ISBN 978-989-758-728-3, SciTePress, pages 831-842. DOI: 10.5220/0013107700003912

in Bibtex Style

@conference{ivapp25,
author={Yanqing Zhang and Leila Methnani and Emmanuel Brorsson and Elmira Zohrevandi and Andreas Darnell and Kostiantyn Kucher},
title={Designing Explainable and Counterfactual-Based AI Interfaces for Operators in Process Industries},
booktitle={Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: IVAPP},
year={2025},
pages={831-842},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013107700003912},
isbn={978-989-758-728-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: IVAPP
TI - Designing Explainable and Counterfactual-Based AI Interfaces for Operators in Process Industries
SN - 978-989-758-728-3
AU - Zhang Y.
AU - Methnani L.
AU - Brorsson E.
AU - Zohrevandi E.
AU - Darnell A.
AU - Kucher K.
PY - 2025
SP - 831
EP - 842
DO - 10.5220/0013107700003912
PB - SciTePress