Explainable artificial intelligence has received limited attention in construction despite its growing importance in various other industrial sectors. In this paper, we provide a narrative review of XAI to raise awareness about its potential in construction. Our review develops a taxonomy of the XAI literature comprising its precepts and approaches. Opportunities for future XAI research focusing on stakeholder desiderata and data and information fusion are identified and discussed. We hope the opportunities we suggest stimulate new lines of inquiry to help alleviate the scepticism and hesitancy toward AI adoption and integration in construction.
@article{arxiv.2211.06579,
title = {Explainable Artificial Intelligence: Precepts, Methods, and Opportunities for Research in Construction},
author = {Peter ED Love and Weili Fang and Jane Matthews and Stuart Porter and Hanbin Luo and Lieyun Ding},
journal= {arXiv preprint arXiv:2211.06579},
year = {2025}
}
Comments
56 pages, 3 figures. arXiv admin note: text overlap with arXiv:1910.10045 by other authors