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    Explainable Artificial Intelligence in Construction: The Content, Context, Process, Outcome Evaluation Framework

    Access Status
    Fulltext not available
    Authors
    Love, Peter
    Matthews, Jane
    Fang, Weili
    Porter, Stuart
    Luo, Hanbin
    Ding, Lieyun
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Love, P.E.D. and Matthews, J. and Fang, W. and Porter, S. and Luo, H. and Ding, L. Explainable Artificial Intelligence in Construction: The Content, Context, Process, Outcome Evaluation Framework.
    Faculty
    Faculty of Science and Engineering
    School
    School of Civil and Mechanical Engineering
    URI
    http://hdl.handle.net/20.500.11937/89695
    Collection
    • Curtin Research Publications
    Abstract

    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.

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