Work

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

Year: 2022

Type: preprint

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.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2211.06579

Authors: Love, Peter ED, Fang, Weili, Matthews, Jane, Porter, Stuart, Luo, Hanbin, Ding, Lieyun

Institutions: Curtin University, Technische Universität Berlin, Deakin University, Huazhong University of Science and Technology

Language: English

Topic: Explainable Artificial Intelligence (XAI)

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

Funders: Alexander von Humboldt-Stiftung, National Natural Science Foundation of China