HUMAN-ARTIFICIAL INTELLIGENCE COLLABORATION FATIGUE: CAUSES, CONSEQUENCES, AND MITIGATION STRATEGIES

Arslan, A., Cooper, C., Khan, Z., Golgeci, I., & Ali, I. (2021). Artificial intelligence and human workers interaction at team level: a conceptual assessment of the challenges and potential HRM strategies. International Journal of Manpower. https://doi.org/10.1108/ijm-01-2021-0052

Bai, S., Zhang, X., Yu, D., & Yao, J. (2024). Assist me or replace me? Uncovering the influence of AI awareness on employees’ counterproductive work behaviors. Frontiers in Public Health, 12. https://doi.org/10.3389/fpubh.2024.1449561

Chand, S., & Lu, Y. (2023). Dual task scheduling strategy for personalized multi-objective optimization of cycle time and fatigue in human-robot collaboration. Manufacturing Letters. https://doi.org/10.1016/j.mfglet.2023.08.064

Chhetri, M., Tariq, S., Singh, R., Jalalvand, F., Paris, C., & Nepal, S. (2024). Towards Human-AI Teaming to Mitigate Alert Fatigue in Security Operations Centres. ACM Transactions on Internet Technology, 24, 1 - 22. https://doi.org/10.1145/3670009

Coles‐Brennan, C., Sulley, A., & Young, G. (2019). Management of digital eye strain. Clinical and experimental Optometry, 102(1), 18-29.

Corvite, S., Roemmich, K., Rosenberg, T., & Andalibi, N. (2023). Data Subjects' Perspectives on Emotion Artificial Intelligence Use in the Workplace: A Relational Ethics Lens. Proceedings of the ACM on Human-Computer Interaction, 7, 1 - 38. https://doi.org/10.1145/3579600

Fahnenstich, H., Rieger, T., & Roesler, E. (2024). Trusting under risk-comparing human to AI decision support agents. Computers in Human Behavior, 153, 108107.

Fügener, A., Grahl, J., Gupta, A., & Ketter, W. (2022). Cognitive challenges in human-artificial intelligence collaboration: Investigating the path toward productive delegation. Information Systems Research, 33(2), 678-696.

Hao, X., Demir, E., & Eyers, D. (2024). Exploring Collaborative Decision-Making: A Quasi-Experimental Study of Human and Generative AI Interaction. Technology in Society. https://doi.org/10.1016/j.techsoc.2024.102662

Hilmi, A., Hamid, A., & Ibrahim, W. (2024). Advancements in Cognitive Ergonomics: Integration with Human-Robot Collaboration, Workload Management, and Industrial Applications. Malaysian Journal of Ergonomics (MJEr). https://doi.org/10.58915/mjer.v6.2024.1368

Hopko, S., Khurana, R., Mehta, R., & Pagilla, P. (2021). Effect of Cognitive Fatigue, Operator Sex, and Robot Assistance on Task Performance Metrics, Workload, and Situation Awareness in Human-Robot Collaboration. IEEE Robotics and Automation Letters, 6, 3049-3056. https://doi.org/10.1109/lra.2021.3062787

Jackson, P. C. (2019). Introduction to artificial intelligence. Courier Dover Publications.

Jeon, H., Jin, D., Choi, S., Cho, H., Lee, K., & Koo, Y. (2024). AI-assisted Work Services Utilizing human-AI Collaboration Levels : The Case of Ward Nurses. Archives of Design Research. https://doi.org/10.15187/adr.2024.11.37.5.353

Jia, J., Ning, X. & Liu, W. The consequences and theoretical explanation of workplace AI on employees: a systematic literature review. J. Digit. Manag. 1, 14 (2025). https://doi.org/10.1007/s44362-025-00016-3

Kalatzis, A., Prabhu, V., & Stanley, L. (2025). Identifying the Contributors of Intrinsic, Extraneous, and Germane Load in Human-Robot Collaboration Through Interview Questions. AHFE International. https://doi.org/10.54941/ahfe1006374

Kolbjørnsrud, V. (2023). Designing the Intelligent Organization: Six Principles for Human-AI Collaboration. California Management Review, 66, 44 - 64. https://doi.org/10.1177/00081256231211020

Kolomaznik, M., Petrik, V., Slama, M., & Juřík, V. (2024). The role of socio-emotional attributes in enhancing human-AI collaboration. Frontiers in Psychology, 15. https://doi.org/10.3389/fpsyg.2024.1369957

Kong, H., Yuan, Y., Baruch, Y., Bu, N., Jiang, X., & Wang, K. (2021). Influences of artificial intelligence (AI) awareness on career competency and job burnout. International Journal of Contemporary Hospitality Management. https://doi.org/10.1108/ijchm-07-2020-0789

Kreye, F., Hynes, J., & Koç, H. (2025). Factors and consequences of loneliness in the digital workplace: A systematic literature review and framework for empirical testing. 24th International Conference on Perspectives in Business Informatics Research (BIR 2025), September 17-19, 2025, Riga, Latvia.

Li, Z. (2025). Enhancing Human-AI Collaboration through Adaptive Interaction and Explainability. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society , 26-27. https://doi.org/10.1609/aies.v7i2.31900

Lițan, D. E. (2025). The Impact of Technostress Generated by Artificial Intelligence on the Quality of Life: The Mediating Role of Positive and Negative Affect. Behavioral Sciences, 15(4), 552.

Lin, C., & Lukodono, R. (2021). Sustainable Human-Robot Collaboration Based on Human Intention Classification. Sustainability, 13, 5990. https://doi.org/10.3390/su13115990

Marr, N. (2021). Yapay zekâ devrimi, Dijital dönüşüm işinizi nasıl etkileyecek, Çev: Ümit Şensoy, Optimist Yayıncılık

McGrath, M. J., Duenser, A., Lacey, J., & Paris, C. (2025). Collaborative human-AI trust (CHAI-T): A process framework for active management of trust in human-AI collaboration. Computers in Human Behavior: Artificial Humans, 100200.

Meng, Q., Wu, T., Duan, W., & Li, S. (2025). Effects of Employee-Artificial Intelligence (AI) Collaboration on Counterproductive Work Behaviors (CWBs): Leader Emotional Support as a Moderator. Behavioral Sciences, 15. https://doi.org/10.3390/bs15050696

Messeri, C., Bicchi, A., Zanchettin, A., & Rocco, P. (2022). A Dynamic Task Allocation Strategy to Mitigate the Human Physical Fatigue in Collaborative Robotics. IEEE Robotics and Automation Letters, 7, 2178-2185. https://doi.org/10.1109/lra.2022.3143520

Mirbabaie, M., Brünker, F., Frick, N., & Stieglitz, S. (2021). The rise of artificial intelligence - understanding the AI identity threat at the workplace. Electronic Markets, 32, 73 - 99. https://doi.org/10.1007/s12525-021-00496-x

Nilsson, N. J. (1971). Problem-solving methods in artificial intelligence. New York: McGraw-Hill.

Okamura, K., & Yamada, S. (2020). Adaptive trust calibration for human-AI collaboration. PLoS ONE, 15. https://doi.org/10.1371/journal.pone.0229132

Parks, M., & Allison, M. (2023). Autonomy and Fatigue in Human-Robot Teams. In 2023 IEEE International Performance, Computing, and Communications Conference (IPCCC) (pp. 158-159). IEEE.

Peternel, L., Tsagarakis, N., Caldwell, D., & Ajoudani, A. (2017). Robot adaptation to human physical fatigue in human-robot co-manipulation. Autonomous Robots, 42, 1011 - 1021. https://doi.org/10.1007/s10514-017-9678-1

Rademaker, T., Klingenberg, I. & Süß, S. Leadership and technostress: a systematic literature review. Manag Rev Q 75, 429-494 (2025). https://doi.org/10.1007/s11301-023-00385-x

Roveda, L., Maskani, J., Franceschi, P., Abdi, A., Braghin, F., Tosatti, L., & Pedrocchi, N. (2020). Model-Based Reinforcement Learning Variable Impedance Control for Human-Robot Collaboration. Journal of Intelligent & Robotic Systems, 100, 417 - 433. https://doi.org/10.1007/s10846-020-01183-3

Steyvers, M., & Mayer, L. (2025). When not to help: planning for lasting human-AI collaboration. arXiv preprint arXiv:2508.01837.

Tang, P., Koopman, J., Mai, K., De Cremer, D., Zhang, J., Reynders, P., Ng, C., & Chen, I. (2023). No person is an island: Unpacking the work and after-work consequences of interacting with artificial intelligence. The Journal of applied psychology. https://doi.org/10.1037/apl0001103

Teng, R., Zhou, S., Zheng, W., & , C. (2023). Artificial intelligence (AI) awareness and work withdrawal: evaluating chained mediation through negative work-related rumination and emotional exhaustion. International Journal of Contemporary Hospitality Management. https://doi.org/10.1108/ijchm-02-2023-0240

Urrea, C. (2025). Fatigue-Aware Sub-Second Combinatorial Auctions for Dynamic Cycle Allocation in Human-Robot Collaborative Assembly. Mathematics, 13(15), 2429. https://doi.org/10.3390/math13152429

Vaccaro, M., Almaatouq, A., & Malone, T. (2024). When combinations of humans and AI are useful: A systematic review and meta-analysis. Nature Human Behaviour, 8, 2293 - 2303. https://doi.org/10.1038/s41562-024-02024-1

Vössing, M., Kühl, N., Lind, M., & Satzger, G. (2022). Designing Transparency for Effective Human-AI Collaboration. Information Systems Frontiers, 24, 877 - 895. https://doi.org/10.1007/s10796-022-10284-3

Westphal, M., Vössing, M., Satzger, G., Yom-Tov, G. B., & Rafaeli, A. (2023). Decision control and explanations in human-AI collaboration: Improving user perceptions and compliance. Computers in Human Behavior, 144, 107714. https://doi.org/10.1016/j.chb.2023.107714

Wu, S., Liu, Y., Ruan, M., Chen, S., & Xie, X. (2025). Human-generative AI collaboration enhances task performance but undermines human’s intrinsic motivation. Scientific Reports, 15. https://doi.org/10.1038/s41598-025-98385-2

Xu, G., Xue, M., & Zhao, J. (2023). The Association between Artificial Intelligence Awareness and Employee Depression: The Mediating Role of Emotional Exhaustion and the Moderating Role of Perceived Organizational Support. International Journal of Environmental Research and Public Health, 20. https://doi.org/10.3390/ijerph20065147

Yao, B., Li, X., Ji, Z., Xiao, K., & Xu, W. (2024). Task reallocation of human-robot collaborative production workshop based on a dynamic human fatigue model. Computers & Industrial Engineering, 189, 109855. https://doi.org/10.1016/j.cie.2023.109855

You, Y., Cai, B., Pham, D. T., Liu, Y., & Ji, Z. (2025). A human digital twin approach for fatigue-aware task planning in human-robot collaborative assembly. Computers & Industrial Engineering, 200, 110774., 200, 110774. https://doi.org/10.1016/j.cie.2024.110774

Zhang, R., Duan, W., Flathmann, C., Mcneese, N., Freeman, G., & Williams, A. (2023). Investigating AI Teammate Communication Strategies and Their Impact in Human-AI Teams for Effective Teamwork. Proceedings of the ACM on Human-Computer Interaction, 7, 1 - 31. https://doi.org/10.1145/3610072

Zheng, J., & Zhang, T. (2025). Association Between AI Awareness and Emotional Exhaustion: The Serial Mediation of Job Insecurity and Work Interference with Family. Behavioral Sciences, 15. https://doi.org/10.3390/bs15040401.