Explainable Artificial Intelligence: Precepts, Methods, and Opportunities for Research in Construction

• URL: http://arxiv.org/abs/2211.06579v1
• Date: Sat, 12 Nov 2022 05:47:42 GMT
• Title: Explainable Artificial Intelligence: Precepts, Methods, and Opportunities for Research in Construction
• Authors: Peter ED Love, Weili Fang, Jane Matthews, Stuart Porter, Hanbin Luo, and Lieyun Ding
• Abstract summary: We provide a narrative review of XAI to raise awareness about its potential in construction. Opportunities for future XAI research focusing on stakeholder desiderata and data and information fusion are identified and discussed.
• Score: 1.2622634782102324
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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