Explainable Artificial Intelligence in Construction: The Content, Context, Process, Outcome Evaluation Framework
Explainable artificial intelligence is an emerging and evolving concept. Its impact on construction, though yet to be realised, will be profound in the foreseeable future. Still, XAI has received limited attention in construction. As a result, no evaluation frameworks have been propagated to enab...
| Main Authors: | , , , , , |
|---|---|
| Format: | Journal Article |
| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/89695 |
| _version_ | 1848765272985436160 |
|---|---|
| author | Love, Peter Matthews, Jane Fang, Weili Porter, Stuart Luo, Hanbin Ding, Lieyun |
| author_facet | Love, Peter Matthews, Jane Fang, Weili Porter, Stuart Luo, Hanbin Ding, Lieyun |
| author_sort | Love, Peter |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Explainable artificial intelligence is an emerging and evolving concept. Its
impact on construction, though yet to be realised, will be profound in the
foreseeable future. Still, XAI has received limited attention in construction.
As a result, no evaluation frameworks have been propagated to enable
construction organisations to understand the what, why, how, and when of XAI.
Our paper aims to fill this void by developing a content, context, process, and
outcome evaluation framework that can be used to justify the adoption and
effective management of XAI. After introducing and describing this novel
framework, we discuss its implications for future research. While our novel
framework is conceptual, it provides a frame of reference for construction
organisations to make headway toward realising XAI business value and benefits. |
| first_indexed | 2025-11-14T11:32:37Z |
| format | Journal Article |
| id | curtin-20.500.11937-89695 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:32:37Z |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-896952023-01-30T03:18:02Z Explainable Artificial Intelligence in Construction: The Content, Context, Process, Outcome Evaluation Framework Love, Peter Matthews, Jane Fang, Weili Porter, Stuart Luo, Hanbin Ding, Lieyun cs.AI cs.AI H.0; H.4; J.0 Explainable artificial intelligence is an emerging and evolving concept. Its impact on construction, though yet to be realised, will be profound in the foreseeable future. Still, XAI has received limited attention in construction. As a result, no evaluation frameworks have been propagated to enable construction organisations to understand the what, why, how, and when of XAI. Our paper aims to fill this void by developing a content, context, process, and outcome evaluation framework that can be used to justify the adoption and effective management of XAI. After introducing and describing this novel framework, we discuss its implications for future research. While our novel framework is conceptual, it provides a frame of reference for construction organisations to make headway toward realising XAI business value and benefits. Journal Article http://hdl.handle.net/20.500.11937/89695 restricted |
| spellingShingle | cs.AI cs.AI H.0; H.4; J.0 Love, Peter Matthews, Jane Fang, Weili Porter, Stuart Luo, Hanbin Ding, Lieyun Explainable Artificial Intelligence in Construction: The Content, Context, Process, Outcome Evaluation Framework |
| title | Explainable Artificial Intelligence in Construction: The Content,
Context, Process, Outcome Evaluation Framework |
| title_full | Explainable Artificial Intelligence in Construction: The Content,
Context, Process, Outcome Evaluation Framework |
| title_fullStr | Explainable Artificial Intelligence in Construction: The Content,
Context, Process, Outcome Evaluation Framework |
| title_full_unstemmed | Explainable Artificial Intelligence in Construction: The Content,
Context, Process, Outcome Evaluation Framework |
| title_short | Explainable Artificial Intelligence in Construction: The Content,
Context, Process, Outcome Evaluation Framework |
| title_sort | explainable artificial intelligence in construction: the content,
context, process, outcome evaluation framework |
| topic | cs.AI cs.AI H.0; H.4; J.0 |
| url | http://hdl.handle.net/20.500.11937/89695 |