Human-AI interaction in remanufacturing: exploring shop floor workers’ behavioural patterns within a specific human-AI system

References

• Acemoglu, D. 2021. Harms of AI (No. W29247). Cambridge, MA: National Bureau of Economic Research. https://doi.org/10.3386/w29247.
   Google Scholar
• Agrawal, R., V. A. Wankhede, A. Kumar, S. Luthra, A. Majumdar, and Y. Kazancoglu. 2021. “An Exploratory State-Of-The-Art Review of Artificial Intelligence Applications in Circular Economy Using Structural Topic Modeling.” Operations Management Research 1–18.
   Web of Science ®Google Scholar
• Ahlborn, K., G. Bachmann, F. Biegel, J. Bienert, S. Falk, A. Fay, T. Gamer, K. Garrels, J. Grotepass, and A. Heindl. 2019. “Technologieszenario Künstliche Intelligenz in der Industrie 4.0.” Bundesministerium für Wirtschaft und Energie (BMWi).
   Google Scholar
• Anton, E., A. Behne, and F. Teuteberg. 2020. The Human Behind Artificial Intelligence - an Operationalisation of AI Competencies, In Proceedings of the 28th European Conference on Information Systems (ECIS). Presented at the European Conference on Information Systems (ECIS), pp. 19–36. https://aisel.aisnet.org/ecis2020_rp/141
   Google Scholar
• Bassellier, G., B. H. Reich, and I. Benbasat. 2001. “Information Technology Competence of Business Managers: A Definition and Research Model.” Journal of Management Information Systems 17 (4): 159–182. https://doi.org/10.1080/07421222.2001.11045660.
   Web of Science ®Google Scholar
• Bittner, E., S. Oeste-Reiß, and J. M. Leimeister. 2019. Where is the Bot in Our Team? Toward a Taxonomy of Design Option Combinations for Conversational Agents in Collaborative Work, In Proceedings of the 52nd Hawaii International Conference on System Sciences, Hawaii, USA.
   Google Scholar
• Blömeke, S., J. Rickert, M. Mennenga, S. Thiede, T. S. Spengler, and C. Herrmann. 2020. “Recycling 4.0 – Mapping Smart Manufacturing Solutions to Remanufacturing and Recycling Operations.” Procedia CIRP 90:600–605. https://doi.org/10.1016/j.procir.2020.02.045.
   Google Scholar
• Borenstein, J., and A. Howard. 2021. “Emerging Challenges in AI and the Need for AI Ethics Education.” AI and Ethics 1 (1): 61–65. https://doi.org/10.1007/s43681-020-00002-7.
   PubMedGoogle Scholar
• Boyatzis, R. E., and R. Boyatzis. 2008. “Competencies in the 21st Century.” Journal of Management Development 27 (1): 5–12. https://doi.org/10.1108/02621710810840730.
   Google Scholar
• Boyatzis, R. E., D. Goleman, F. Gerli, S. Bonesso, and L. Cortellazzo. 2019. “Emotional and Social Intelligence Competencies and the Intentional Change Process.” In Cognitive Readiness in Project Teams, edited by C. Belack, D. Di Filippo, and I. Di Filippo, 147–169. New York: Productivity Press. https://doi.org/10.4324/9780429490057-7.
   Google Scholar
• Brock, J. K. U., and F. von Wangenheim. 2019. “Demystifying AI: What Digital Transformation Leaders Can Teach You About Realistic Artificial Intelligence.” California Management Review 61 (4): 110–134. https://doi.org/10.1177/1536504219865226.
   Web of Science ®Google Scholar
• Brynjolfsson, E., and T. Mitchell. 2017. “What Can Machine Learning Do? Workforce Implications.” Science 358 (6370): 1530–1534. https://doi.org/10.1126/science.aap8062.
   PubMed Web of Science ®Google Scholar
• Buiten, M. C. 2019. “Towards Intelligent Regulation of Artificial Intelligence.” European Journal of Risk Regulation 10 (1): 41–59. https://doi.org/10.1017/err.2019.8.
   Web of Science ®Google Scholar
• Dellermann, D., A. Calma, N. Lipusch, T. Weber, S. Weigel, and P. Ebel. 2019. The Future of Human-AI Collaboration: A Taxonomy of Design Knowledge for Hybrid Intelligence Systems. Presented at the Hawaii International Conference on System Sciences. https://doi.org/10.24251/HICSS.2019.034.
   Google Scholar
• Ferràs-Hernández, X. 2018. “The Future of Management in a World of Electronic Brains.” Journal of Management Inquiry 27 (2): 260–263. https://doi.org/10.1177/1056492617724973.
   Web of Science ®Google Scholar
• Giering, O. 2021. Künstliche Intelligenz und Arbeit: Betrachtungen zwischen Prognose und betrieblicher Realität. Z. Arb. Wiss. https://doi.org/10.1007/s41449-021-00289-0.
   Google Scholar
• Glikson, E., and A. W. Woolley. 2020. “Human Trust in Artificial Intelligence: Review of Empirical Research.” Academy of Management Annals 14 (2): 627–660. https://doi.org/10.5465/annals.2018.0057.
   Web of Science ®Google Scholar
• Grafström, J., and S. Aasma. 2021. “Breaking Circular Economy Barriers.” Journal of Cleaner Production 292:126002. https://doi.org/10.1016/j.jclepro.2021.126002.
   Web of Science ®Google Scholar
• Hamm, P., and M. Klesel. 2021. “Success Factors for the Adoption of Artificial Intelligence in Organizations: A Literature Review.“ 27th Americas Conference on Information Systems (AMCIS), Montreal, Canada, August 2021.
   Google Scholar
• Hinsen, S., P. Hofmann, J. Jöhnk, and N. Urbach. 2022. How Can Organizations Design Purposeful Human-AI Interactions: A Practical Perspective from Existing Use Cases and Interviews. Presented at the Hawaii International Conference on System Sciences. https://doi.org/10.24251/HICSS.2022.024.
   Google Scholar
• Hsieh, H. F., and S. E. Shannon. 2005. “Three Approaches to Qualitative Content Analysis.” Qualitative Health Research 15 (9): 1277–1288. https://doi.org/10.1177/1049732305276687.
   PubMed Web of Science ®Google Scholar
• Kerin, M., and D. T. Pham. 2019. “A Review of Emerging Industry 4.0 Technologies in Remanufacturing.” Journal of Cleaner Production 237:117805. https://doi.org/10.1016/j.jclepro.2019.117805.
   Web of Science ®Google Scholar
• Li, J., M. Barwood, and S. Rahimifard. 2018. “Robotic Disassembly for Increased Recovery of Strategically Important Materials from Electrical Vehicles.” Robotics and Computer-Integrated Manufacturing 50:203–212. https://doi.org/10.1016/j.rcim.2017.09.013.
   Web of Science ®Google Scholar
• Li, S., H. Zhang, W. Yan, Z. Jiang, H. Wang, and W. Wei. 2019. “Multi-Objective Disassembly Sequence Optimization Aiming at Quality Uncertainty of End-Of-Life Product.” IOP Conference Series: Materials Science & Engineering 631 (3): 032015. https://doi.org/10.1088/1757-899X/631/3/032015.
   Google Scholar
• Margetts, H. 2022. “Rethinking AI for Good Governance.” Daedalus 151 (2): 360–371. https://doi.org/10.1162/daed_a_01922.
   Web of Science ®Google Scholar
• Markauskaite, L., R. Marrone, O. Poquet, S. Knight, R. Martinez-Maldonado, S. Howard, J. Tondeur, et al. 2022. “Rethinking the Entwinement Between Artificial Intelligence and Human Learning: What Capabilities Do Learners Need for a World with AI?” Computers and Education: Artificial Intelligence 3:100056. https://doi.org/10.1016/j.caeai.2022.100056.
   Google Scholar
• Masi, D., V. Kumar, J. A. Garza-Reyes, and J. Godsell. 2018. “Towards a More Circular Economy: Exploring the Awareness, Practices, and Barriers from a Focal Firm Perspective.” Production Planning & Control 29 (6): 539–550. https://doi.org/10.1080/09537287.2018.1449246.
   Web of Science ®Google Scholar
• Massmann, C., and A. Hofstetter. 2020. “AI-pocalypse now? Herausforderungen Künstlicher Intelligenz für Bildungssystem.” Unternehmen und die Workforce der Zukunft Digitale Bildung und Künstliche Intelligenz in Deutschland 167–220. https://doi.org/10.1007/978-3-658-30525-3_8.
   Google Scholar
• Miles, M. B., A. M. Huberman, and J. Saldana. 2020. Qualitative Data Analysis: A Methods Sourcebook. 4th ed. Arizona State University, USA: SAGE Publications, Thousand Oaks.
   Google Scholar
• Papachristos, E., P. Skov Johansen, R. Møberg Jacobsen, L. Bjørn Leer Bysted, and M. B. Skov. 2021. How Do People Perceive the Role of AI in Human-AI Collaboration to Solve Everyday Tasks? In Presented at the CHI Greece 2021: 1st International Conference of the ACM Greek SIGCHI Chapter, ACM, Online (Athens, Greece) Greece, 1–6. https://doi.org/10.1145/3489410.3489420.
   Google Scholar
• Pumplun, L., C. Tauchert, and M. Heidt. 2019. “A New Organizational Chassis for Artificial Intelligence - Exploring Organizational Readiness Factors.“ European Conference on Information Systems (ECIS), Stockholm, Sweden, June 2019.
   Google Scholar
• Ramadoss, T. S., H. Alam, and R. Seeram. 2018. “Artificial Intelligence and Internet of Things Enabled Circular Economy.“ The International Journal of Engineering and Science (IJES) 7 (9): 55–63.
   Google Scholar
• Rammer, C., I. Bertschek, B. Schuck, V. Demary, and H. Goecke. 2020. Einsatz von Künstlicher Intelligenz in der Deutschen Wirtschaft: Stand der KI-Nutzung im Jahr 2019 (Research Report). ZEW-Gutachten und Forschungsberichte.
   Google Scholar
• Rzepka, C., and B. Berger. 2018. “User Interaction with AI-Enabled Systems: A Systematic Review of IS Research.“ International Conference on Information Systems (ICIS), San Francisco, California, December 2018.
   Google Scholar
• Salmenperä, H., K. Pitkänen, P. Kautto, and L. Saikku. 2021. “Critical Factors for Enhancing the Circular Economy in Waste Management.” Journal of Cleaner Production 280:124339. https://doi.org/10.1016/j.jclepro.2020.124339.
   Web of Science ®Google Scholar
• Samuel, J. 2021. A Call for Proactive Policies for Informatics and Artificial Intelligence Technologies [WWW Document]. Scholars Strategy Network. Accessed April 25, 2023. https://scholars.org/contribution/call-proactive-policies-informatics-and
   Google Scholar
• Sankaran, K. 2019. “Carbon Emission and Plastic Pollution: How Circular Economy, Blockchain, and Artificial Intelligence Support Energy Transition?” Journal of Innovation Management 7 (4): 7–13. https://doi.org/10.24840/2183-0606_007.004_0002.
   Google Scholar
• Schelble, B., C. Flathmann, L.-B. Canonico, and N. Mcneese. 2021. Understanding Human-AI Cooperation Through Game-Theory and Reinforcement Learning Models. Presented at the Hawaii International Conference on System Sciences. https://doi.org/10.24251/HICSS.2021.041.
   Google Scholar
• Schlüter, M., H. Lickert, K. Schweitzer, P. Bilge, C. Briese, F. Dietrich, and J. Krüger. 2021. “AI-Enhanced Identification, Inspection and Sorting for Reverse Logistics in Remanufacturing.” Procedia CIRP 98:300–305. https://doi.org/10.1016/j.procir.2021.01.107.
   Google Scholar
• Seeber, I., E. Bittner, R. O. Briggs, G.-J. de Vreede, T. de Vreede, D. Druckenmiller, A. B. Merz, et al. 2018. Machines as Teammates: A Collaboration Research Agenda. https://doi.org/10.24251/HICSS.2018.055.
   Google Scholar
• Seiffer, A., U. Gnewuch, and A. Maedche. 2021. “Understanding Employee Responses to Software Robots: A Systematic Literature Review.“ Conference: International Conference on Information Systems (ICIS), Austin, Texas, December 2021.
   Google Scholar
• Sonnentag, S., I. Kuttler, and C. Fritz. 2010. “Job Stressors, Emotional Exhaustion, and Need for Recovery: A Multi-Source Study on the Benefits of Psychological Detachment.” Journal of Vocational Behavior 76 (3): 355–365. https://doi.org/10.1016/j.jvb.2009.06.005.
   Web of Science ®Google Scholar
• Süße, T., M. Kobert, and C. Kries. 2021. “Antecedents of constructive human-AI collaboration: An exploration of human actors’ key competencies.” In Smart and Sustainable Collaborative Networks 4.0, edited by L. M. Camarinha-Matos, X. Bouchier, and H. Afsarmanesh. Springer.
   Google Scholar
• Talboy, A. N., and E. Fuller. 2023. “Challenging the Appearance of Machine Intelligence: Cognitive Bias in LLMs.” https://doi.org/10.48550/arXiv.2304.01358.
   Google Scholar
• Tsimba, W., G. Chirinda, and S. Matope. 2021. “Machine Learning for Decision-Making in the Remanufacturing of Worn-Out Gears and Bearings.” SAJIE 32 (2): 135–150. https://doi.org/10.7166/32-3-2636.
   Google Scholar
• van Berkel, N., O. F. Ahmad, D. Stoyanov, L. Lovat, and A. Blandford. 2021. “Designing Visual Markers for Continuous Artificial Intelligence Support: A Colonoscopy Case Study.” ACM Transactions on Computing for Healthcare 2 (1): 1–7:24. https://doi.org/10.1145/3422156.
   Google Scholar
• van Berkel, N., M. B. Skov, and J. Kjeldskov. 2021. “Human-AI Interaction: Intermittent, Continuous, or Proactive.” Interactions 28 (6): 67–71. https://doi.org/10.1145/3486941.
   Google Scholar
• Waefler, T., and U. Schmid. 2021. “Explainability is Not Enough: Requirements for Human-AI- Partnership in Complex Socio-Technical Systems. https://doi.org/10.34190/EAIR.20.007.
   Google Scholar
• Wang, D., J. D. Weisz, M. Muller, P. Ram, W. Geyer, C. Dugan, Y. Tausczik, H. Samulowitz, and A. Gray. 2019. “Human-AI Collaboration in Data Science: Exploring Data Scientists.” Perceptions of Automated AI Proceedings of the ACM on human-computer interaction 3 (CSCW): 1–24. https://doi.org/10.1145/3359313.
   PubMedGoogle Scholar
• Wanner, J., L.-V. Herm, and C. Janiesch. 2019. “Countering the Fear of Black-Boxed AI in Maintenance: Towards a Smart Colleague.“ 2019 Pre-ICIS SIGDSA Symposium.
   Google Scholar
• Wilson, H. J., and P. R. Daugherty. 2018. “Collaborative Intelligence: Humans and AI are Joining Forces.” Harvard Business Review 96 (4): 114–123.
   Web of Science ®Google Scholar
• Yeh, S. C., A. W. Wu, H. C. Yu, H. C. Wu, Y.-P. Kuo, and P.-X. Chen. 2021. “Public Perception of Artificial Intelligence and Its Connections to the Sustainable Development Goals.” Sustainability 13 (16): 9165. https://doi.org/10.3390/su13169165.
   Web of Science ®Google Scholar
• Yuan, Z., J. Bi, and Y. Moriguichi. 2008. “The Circular Economy: A New Development Strategy in China.” Journal of Industrial Ecology 10 (1–2): 4–8. https://doi.org/10.1162/108819806775545321.
   Web of Science ®Google Scholar
• Yudkowsky, E. 2008. “Artificial Intelligence as a Positive and Negative Factor in Global Risk.” In Global Catastrophic Risks. Oxford University Press. https://doi.org/10.1093/oso/9780198570509.003.0021.
   Google Scholar
• Zicari, R. V., J. Brodersen, J. Brusseau, B. Dudder, T. Eichhorn, T. Ivanov, G. Kararigas, et al. 2021. Z-Inspection®: A Process to Assess Trustworthy AI. IEEE Transactions on Technology and Society. 1–1. https://doi.org/10.1109/TTS.2021.3066209.
   Google Scholar
• Zweig, K. A. 2019. Algorithmische Entscheidungen: Transparenz und Kontrolle. Berlin: Konrad Adenauer Stiftung.
   Google Scholar