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Title Toward Interactional Trust For Humans And Automation: Extending Interdependence
ID_Doc 57707
Authors Razin Y.; Feigh K.
Year 2019
Published Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019
DOI http://dx.doi.org/10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00247
Abstract Trust in human-automation interaction is increasingly imperative as AI and robots become ubiquitous at home, school, and work. Interdependence theory allows for the identification of one-on-one interactions that require trust by analyzing the structure of the potential outcomes. This paper synthesizes multiple, formerly disparate research approaches by extending Interdependence theory to create a unified framework for outcome-based trust in human-automation interaction. This framework quantitatively contextualizes validated empirical results from social psychology on relationship formation, stability, and betrayal. It also contributes insights into trust-related concepts, such as power and commitment, which help further our understanding of trustworthy system design. This new integrated interactional approach reveals how trust and trustworthiness machines from merely reliable tools to trusted teammates working hand-in-actuator toward an automated future. © 2019 IEEE.
Author Keywords Human-Automation Trust; Human-Robot Interaction; Interdependence Theory; Social Exchange


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