Explainable Artificial Intelligence: Precepts, Methods, and Opportunities for Research in Construction
dc.contributor.author | Love, Peter | |
dc.contributor.author | Fang, Weili | |
dc.contributor.author | Matthews, Jane | |
dc.contributor.author | Porter, Stuart | |
dc.contributor.author | Luo, Hanbin | |
dc.contributor.author | Ding, Lieyun | |
dc.date.accessioned | 2022-11-24T07:09:10Z | |
dc.date.available | 2022-11-24T07:09:10Z | |
dc.identifier.citation | Love, P.E.D. and Fang, W. and Matthews, J. and Porter, S. and Luo, H. and Ding, L. Explainable Artificial Intelligence: Precepts, Methods, and Opportunities for Research in Construction. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/89696 | |
dc.description.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. | |
dc.subject | cs.AI | |
dc.subject | cs.AI | |
dc.subject | H.0; H.4; J.0 | |
dc.title | Explainable Artificial Intelligence: Precepts, Methods, and Opportunities for Research in Construction | |
dc.type | Journal Article | |
dc.date.updated | 2022-11-24T07:09:08Z | |
curtin.department | School of Civil and Mechanical Engineering | |
curtin.accessStatus | Fulltext not available | |
curtin.faculty | Faculty of Science and Engineering | |
curtin.contributor.orcid | Love, Peter [0000-0002-3239-1304] | |
curtin.contributor.researcherid | Love, Peter [D-7418-2017] | |
curtin.contributor.scopusauthorid | Love, Peter [7101960035] |