Complexity-Driven Trust Dynamics in Human–Robot Interactions: Insights from AI-Enhanced Collaborative Engagements
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Published:2023-12-05
Issue:24
Volume:13
Page:12989
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ISSN:2076-3417
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Container-title:Applied Sciences
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language:en
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Short-container-title:Applied Sciences
Author:
Zhu Yi1, Wang Taotao1, Wang Chang2ORCID, Quan Wei3, Tang Mingwei1
Affiliation:
1. School of Computer Science, Nanjing Audit University, Nanjing 211800, China 2. College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China 3. School of Statistics and Data Science, Nanjing Audit University, Nanjing 211800, China
Abstract
This study explores the intricate dynamics of trust in human–robot interaction (HRI), particularly in the context of modern robotic systems enhanced by artificial intelligence (AI). By grounding our investigation in the principles of interpersonal trust, we identify and analyze both similarities and differences between trust in human–human interactions and human–robot scenarios. A key aspect of our research is the clear definition and characterization of trust in HRI, including the identification of factors influencing its development. Our empirical findings reveal that trust in HRI is not static but varies dynamically with the complexity of the tasks involved. Notably, we observe a stronger tendency to trust robots in tasks that are either very straightforward or highly complex. In contrast, for tasks of intermediate complexity, there is a noticeable decline in trust. This pattern of trust challenges conventional perceptions and emphasizes the need for nuanced understanding and design in HRI. Our study provides new insights into the nature of trust in HRI, highlighting its dynamic nature and the influence of task complexity, thereby offering a valuable reference for future research in the field.
Funder
National Natural Science Foundation of China National Social Science Fund of China Significant Project of Jiangsu College Philosophy and Social Sciences Research Jiangsu College Philosophy and Social Sciences Research Planning Fund Project of Humanities and Social Sciences Research of Ministry of Education of China
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Reference57 articles.
1. Human-in-the-Loop Optimization of Wearable Robotic Devices to Improve Human-Robot Interaction: A Systematic Review;Voss;IEEE Trans. Cybern.,2022 2. Ling, H., Liu, G., Zhu, L., Huang, B., Lu, F., Wu, H., Tian, G., and Ji, Z. (2022, January 27–31). Motion Planning Combines Human Motion Prediction for Human-Robot Cooperation. Proceedings of the 2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER), Baishan, China. 3. Wang, C., Wen, X., Niu, Y., Wu, L., Yin, D., and Li, J. (December, January 30). Dynamic task allocation for heterogeneous manned-unmanned aerial vehicle teamwork. Proceedings of the 2018 Chinese Automation Congress (CAC), Xi’an, China. 4. Three Strikes and you are out!: The impacts of multiple human-robot trust violations and repairs on robot trustworthiness;Esterwood;Comput. Hum. Behav.,2023 5. The trustworthy and acceptable HRI checklist (TA-HRI): Questions and design recommendations to support a trust-worthy and acceptable design of human-robot interaction;Kraus;Gruppe. Interaktion. Organisation. Z. Angew. Organ. (GIO),2022
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