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Human-centered AI for industry 5.0 (HUMAI5.0) : design framework and case studies

Mario Passalacqua, Garrick Cabour, Robert Pellerin, Pierre-Majorique Léger and Philippe Doyon-Poulin

Book Section (2024)

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Integrating artificial intelligence (AI) in the workplace has created many challenges and opportunities for human work. Increased human–automation collaboration is expected on physical or cognitive tasks. Several disciplines have echoed the fact that these new technologies automate part of the work steps in collaboration with human operators rather than replacing entire professions, such as Information Technologies (Seeber et al., 2020), economics (Frey & Osborne, 2017), work psychology (Parker & Grote, 2022) and human factors & ergonomics (Mueller et al., 2021). The area of Industry 4.0 (I4.0) is at the forefront of the digitalization of human work wherein AI plays a central role. I4.0 intends to increase production system capabilities in terms of productivity, repeatability, flexibility, real-time monitoring, and process standardization (Zheng et al., 2021). This is done by integrating a set of digital, robotic, and automated technologies into production (Kadir et al., 2019) and combining different digital solutions together (Zheng et al., 2021). The latest technological advances in I4.0 have increased the capabilities of machines in performing complex, cognitive tasks (Xiong et al., 2022). However, the development of I4.0 technologies follows a technocentric approach (Sony & Naik, 2020). Focusing on technology development first (Carayannis et al., 2022). Bibliometric analyses quantified the technocentric directions of I4.0. A recent literature review noted that out of a sample of 4885 studies with a search strategy that included the terms Industry 4.0 and Human Factors, 4849 studies focused on technical factors and 36 on human factors (Passalacqua et al., 2022). This top-down approach often neglects the contextual factors that govern work systems and their potential integration into situated operational practices (Loup-Escande, 2022).

Uncontrolled Keywords

computer science; engineering & technology

Subjects: 2800 Artificial intelligence > 2800 Artificial intelligence (Computer vision, see 2603)
Department: Department of Mathematics and Industrial Engineering
PolyPublie URL: https://publications.polymtl.ca/57479/
Publisher: CRC Press
DOI: 10.1201/9781003320791-27
Official URL: https://doi.org/10.1201/9781003320791-27
Date Deposited: 28 Feb 2024 14:05
Last Modified: 09 Jul 2024 00:24
Cite in APA 7: Passalacqua, M., Cabour, G., Pellerin, R., Léger, P.-M., & Doyon-Poulin, P. (2024). Human-centered AI for industry 5.0 (HUMAI5.0) : design framework and case studies. In Human-centered AI : a multidisciplinary perspective for policy-makers, auditors and users (260-274). https://doi.org/10.1201/9781003320791-27


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