Trust-building in AI-human partnerships within Industry 5.0

• Autorzy: Żywiołek Justyna

Identyfikatory

DOI

10.2478/czoto-2024-0011

• Języki publikacji: EN

Abstrakty

EN

The rapid advancement of artificial intelligence (AI) within Industry 4.0 has transformed manufacturing processes, shifting from traditional automation to more collaborative AI-human partnerships. While AI promises enhanced efficiency, precision, and productivity, the success of these systems relies heavily on the trust established between human operators and AI technologies. This paper explores the critical factors influencing trust in AI-human partnerships in the manufacturing sector, emphasizing the need for transparency, accountability, and ethical AI design. Drawing on a multidisciplinary literature review and empirical studies, we identify key drivers of trust, including human preferences for system transparency, the explainability of AI decisions, and the reliability of AI systems in dynamic production environments. Furthermore, the paper examines the challenges associated with trust-building, such as overcoming fear of job displacement and managing perceived risks of AI errors. The findings contribute to the growing body of knowledge on human-centric AI design and offer practical recommendations for fostering trust to ensure successful AI-human collaboration in manufacturing settings. By transitioning from purely automated systems to collaborative partnerships, manufacturers can unlock the full potential of AI while maintaining a workforce that is confident in AI’s reliability and ethical alignment.

Słowa kluczowe

EN

artificial intelligence (AI); Industry 5.0; human-AI collaboration; cognitive model of human-AI

PL

sztuczna inteligencja; Przemysł 5.0; współpraca człowiek-AI; model poznawczy człowiek-AI

• Wydawca: De Gruyter
• Czasopismo: System Safety : Human - Technical Facility - Environment
• Rocznik: 2024
• Tom: Vol. 6, iss. 1
• Strony: 89--98
• Opis fizyczny: Bibliogr. 29 poz., rys.

Twórcy

autor

Żywiołek Justyna

• Faculty of Management, Czestochowa University of Technology, Poland

• https://orcid.org/0000-0003-0407-0826

Bibliografia

• 1.Bao, L., Krause, N. M., Calice, M. N., Scheufele, D. A., Wirz, C. D., Brossard, D., Newman, T. P., Xenos, M. A., 2022. Whose AI? How different publics think about AI and its social impacts. Computers in Human Behavior, 130, 107182, DOI: 10.1016/j.chb.2022.107182
• 2.Bitkina, O. V., Jeong, H., Lee, B. C., Park, J [Jangwoon], Park, J [Jaehyun], Kim, H. K., 2020. Perceived trust in artificial intelligence technologies: A preliminary study. Human Factors and Ergonomics in Manufacturing & Service Industries, 30(4), 282-290, DOI: 10.1002/hfm.20839
• 3.Broussard, M., Diakopoulos, N., Guzman, A. L., Abebe, R., Dupagne, M., Chuan, C. H., 2019. Artificial Intelligence and Journalism. Journalism & Mass Communication Quarterly, 96(3), 673-695, DOI: 10.1177/1077699019859901
• 4.Chan-Olmsted, S. M., 2019. A Review of Artificial Intelligence Adoptions in the Media Industry. International Journal on Media Management, 21(3-4), 193-215, DOI: 10.1080/14241277.2019.1695619
• 5.Chen, K., Zu, Y., Wang, D., 2021. Design and implementation of intelligent creation platform based on artificial intelligence technology. Journal of Computational Methods in Sciences and Engineering, 20(4), 1109-1126, DOI: 10.3233/JCM-204240
• 6.de-Lima-Santos, M. F., Ceron, W., 2022. Artificial Intelligence in News Media: Current Perceptions and Future Outlook. Journalism and Media, 3(1), 13-26, DOI: 10.3390/journalmedia3010002
• 7.Dmitrieva, E., Balmiki, V., Lakhanpal, S., Lavanya, G., Bhandari, P., 2024. AI Evolution in Industry 4.0 and Industry 5.0: An Experimental Comparative Assessment. BIO Web of Conferences, 86, 1069, DOI: 10.1051/bioconf/20248601069
• 8.Gillath, O., Ai, T., Branicky, M. S., Keshmiri, S., Davison, R. B., Spaulding, R., 2021. Attachment and trust in artificial intelligence. Computers in Human Behavior, 115, 106607, DOI: 10.1016/j.chb.2020.106607
• 9.Gursoy, D., Chi, O. H., Lu, L., Nunkoo, R., 2019. Consumers acceptance of artificially intelligent (AI) device use in service delivery. International Journal of Information Management, 49, 157-169, DOI: 10.1016/j.ijinfomgt.2019.03.008
• 10.Hussain, I., Qureshi, M., Ismail, M., Iftikhar, H., Zywiołek, J., López-Gonzales, J. L., 2024. Optimal features selection in the high dimensional data based on robust technique: Application to different health database. Heliyon, 10(17), e37241, DOI: 10.1016/j.heliyon.2024.e37241
• 11.Kamble, S. S., Gunasekaran, A., Gawankar, S. A., 2018. Sustainable Industry 4.0 framework: A systematic literature review identifying the current trends and future perspectives. Process Safety and Environmental Protection, 117, 408-425, DOI: 10.1016/j.psep.2018.05.009
• 12.Kareem Thajeel, I., Samsudin, K., Jahari Hashim, S., Hashim, F., 2023. Dynamic feature selection model for adaptive cross site scripting attack detection using developed multi-agent deep Q learning model. Journal of King Saud University - Computer and Information Sciences, 35(6), 101490, DOI: 10.1016/j.jksuci.2023.01.012
• 13.Kim, S., Kim, B., 2020. A Decision-Making Model for Adopting Al-Generated News Articles: Preliminary Results. Sustainability, 12(18), 7418, DOI: 10.3390/su12187418
• 14.Langer, M., Landers, R. N., 2021. The future of artificial intelligence at work: A review on effects of decision automation and augmentation on workers targeted by algorithms and third-party observers. Computers in Human Behavior, 123, 106878, DOI: 10.1016/j.chb.2021.106878
• 15.Li, S., Zheng, P., Liu, S., Wang, Z., Wang, X. V., Zheng, L., Wang, L., 2023. Proactive human- robot collaboration: Mutual-cognitive, predictable, and self-organising perspectives. Robotics and Computer-Integrated Manufacturing, 81, 102510, DOI: 10.1016/j.rcim.2022.102510
• 16.Lim, J. S., Zhang, J., 2022. Adoption of AI-driven personalization in digital news platforms: An integrative model of technology acceptance and perceived contingency. Technology in Society, 69, 101965, DOI: 10.1016/j.techsoc.2022.101965
• 17.McGrath, M. J., Duenser, A., Lacey, J., Paris, C., 2024, April 2. Collaborative human-AI trust (CHAI-T): A process framework for active management of trust in human-AI collaboration. http://arxiv.org/pdf/2404.01615
• 18.Paul, M., Maglaras, L., Ferrag, M. A., Almomani, I., 2023. Digitization of healthcare sector: A study on privacy and security concerns. ICT Express, 9(4), 571-588, DOI: 10.1016/j.icte.2023.02.007
• 19.Raisch, S., Krakowski, S., 2021. Artificial Intelligence and Management: The Automation- Augmentation Paradox. Academy of Management Review, 46(1), 192-210, DOI: 10.5465/amr.2018.0072
• 20.Rožanec, J. M., Novalija, I., Zajec, P., Kenda, K., Tavakoli Ghinani, H., Suh, S., Veliou, E., Papamartzivanos, D., Giannetsos, T., Menesidou, S. A., Alonso, R., Cauli, N., Meloni, A., Recupero, D. R., Kyriazis, D., Sofianidis, G., Theodoropoulos, S., Fortuna, B., Mladenić, D., Soldatos, J., 2023. Human-centric artificial intelligence architecture for industry 5.0 applications. International Journal of Production Research, 61(20), 6847-6872, DOI: 10.1080/00207543.2022.2138611
• 21.Schepman, A., Rodway, P., 2020. Initial validation of the general attitudes towards Artificial Intelligence Scale. Computers in Human Behavior Reports, 1, 100014, DOI: 10.1016/j.chbr.2020.100014
• 22.Shekhar, A. R., Parekh, M. H., Pol, V. G., 2022. Worldwide ubiquitous utilization of lithium-ion batteries: What we have done, are doing, and could do safely once they are dead? Journal of Power Sources, 523, 231015, DOI: 10.1016/j.jpowsour.2022.231015
• 23.Song, B., Zhu, Q., Luo, J., 2024. Human-AI collaboration by design. Proceedings of the Design Society, 4, 2247-2256, DOI: 10.1017/pds.2024.227
• 24.Song, M. K., Lin, F. C., Ward, S. E., Fine, J. P., 2013. Composite variables: When and how. Nursing Research, 62(1), 45-49, DOI: 10.1097/NNR.0b013e3182741948
• 25.Wang, 2020. Understanding podcast users: Consumption motives and behaviors. New Media & Society, 24, 684.
• 26.Wang, X., Zhu, F., 2021. The Application of Artificial Intelligence in AI News Anchor (2021 International Conference on Big Data Analytics for Cyber-Physical System in Smart City. Springer Singapore, 102, pp. 1093-1100.
• 27.Żywiołek, J., 2024a. Building Trust in AI-Human Partnerships: Exploring Preferences and Influences in the Manufacturing Industry. Management Systems in Production Engineering, 32(2), 244-251, DOI: 10.2478/mspe-2024-0024
• 28.Żywiołek, J., 2024b. Knowledge-Driven Sustainability: Leveraging Technology for Resource Management in Household Operations. European Conference on Knowledge Management, 25(1), 974-982, DOI: 10.34190/eckm.25.1.2375
• 29.Żywiołek, J., Rosak-Szyrocka, J., Nayyar, A., Naved, M., 2024. Modern technologies and tools supporting the development of industry 5.0. CRC PRESS.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).