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Regulation of AI Technologies in the Construction Industry

Author

Listed:
  • Vishnu Sivarudran Pillai

    (Chief Economist for Asia Pacific, NATIXIS, Department of Public Policy, The Hong Kong University of Science and Technology)

  • Kira Matus

    (Associate Professor for the Division of Social Science, Associate Professor for Division of Public Policy, Department of Economics & Institute for Emerging Market Studies, the Hong Kong University of Science and Technology)

Abstract

The development of Artificial Intelligence (AI) -based technologies for the construction industry, though not as advanced as in some areas, is progressing. The degree of automation in construction is anticipated to eventually lead to humanoid robots and autonomous back loaders or cranes operating at construction sites. The prospect of a highly automated construction industry is a medium-term future prospect. Hence it is imperative to proactively understand the regulatory gaps, to support policy interventions to mitigate potential risks. Regulation of futuristic technologies like AI is challenging in sectors where there is a lack of adequate tacit and applied knowledge. AI regulation is complicated by the massiveness of the construction industry, characterized by a broad spectrum of actors and activities. We propose a framework to understand the AI inclusion in the construction industry and identification of risks and regulatory gaps by considering the diverse stakeholders and their risk perception.

Suggested Citation

  • Vishnu Sivarudran Pillai & Kira Matus, 2019. "Regulation of AI Technologies in the Construction Industry," HKUST IEMS Working Paper Series 2019-65, HKUST Institute for Emerging Market Studies, revised May 2019.
    • Handle: RePEc:hku:wpaper:201965
    as

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    References listed on IDEAS

    as
    1. Aria, Massimo & Cuccurullo, Corrado, 2017. "bibliometrix: An R-tool for comprehensive science mapping analysis," Journal of Informetrics, Elsevier, vol. 11(4), pages 959-975.
    2. Juan Zhang & Qi Yu & Fashan Zheng & Chao Long & Zuxun Lu & Zhiguang Duan, 2016. "Comparing keywords plus of WOS and author keywords: A case study of patient adherence research," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(4), pages 967-972, April.
    3. You, Sangseok & Kim, Jeong-Hwan & Lee, SangHyun & Kamat, Vineet & Robert, Lionel, 2018. "Enhancing perceived safety in human–robot collaborative construction using immersive virtual environments," HEC Research Papers Series 1308, HEC Paris.
    4. Zvi Griliches, 1998. "The Search for R&D Spillovers," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 251-268, National Bureau of Economic Research, Inc.
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    More about this item

    Keywords

    Artificial Intelligence; Construction; Regulation; Risks; Risk Tolerance;
    All these keywords.

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