2022
DOI: 10.1109/thms.2022.3144956
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A Review on Human–Machine Trust Evaluation: Human-Centric and Machine-Centric Perspectives

Abstract: As complex autonomous systems become increasingly ubiquitous, their deployment and integration into our daily lives will become a significant endeavor. Human-machine trust relationship is now acknowledged as one of the primary aspects that characterize a successful integration. In the context of human-machine interaction (HMI), proper use of machines and autonomous systems depends both on the human and machine counterparts. On one hand, it depends on how well the human relies on the machine regarding the situa… Show more

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Cited by 33 publications
(13 citation statements)
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“…Over-trust or lack of trust will lead to over-supervision or under-supervision of intelligent systems by miners ( 43 ), making miners react poorly in critical events and leading to safety accidents ( 44 ). Therefore, an appropriate level of trust is essential: operators must understand the capabilities of intelligent systems and adequately monitor them as they approach the limits of their capabilities ( 45 ). Maintaining an appropriate level of trust among miners begins with training miners with a clear and detailed introduction to the functions and operation of the intelligent system, explaining the system's limitations, and improving the miners' level of expertise.…”
Section: Resultsmentioning
confidence: 99%
“…Over-trust or lack of trust will lead to over-supervision or under-supervision of intelligent systems by miners ( 43 ), making miners react poorly in critical events and leading to safety accidents ( 44 ). Therefore, an appropriate level of trust is essential: operators must understand the capabilities of intelligent systems and adequately monitor them as they approach the limits of their capabilities ( 45 ). Maintaining an appropriate level of trust among miners begins with training miners with a clear and detailed introduction to the functions and operation of the intelligent system, explaining the system's limitations, and improving the miners' level of expertise.…”
Section: Resultsmentioning
confidence: 99%
“…At present, the academic community is focused on the human-centered development of interpretable technology [ 100 , 101 , 102 ]. Unfortunately, the human–XAI interaction techniques face many challenges that need massive work to be solved [ 103 , 104 ].…”
Section: Discussion Challenges and Prospectsmentioning
confidence: 99%
“…To achieve this goal, many researchers are looking to design more sophisticated interpretation methods to achieve trustfulness [ 99 ]. Currently, the academic community is focused on the human-centered development of interpretable technology [ 100 , 101 , 102 ]. Unfortunately, human–XAI interaction techniques also face many challenges.…”
Section: Discussion Challenges and Prospectsmentioning
confidence: 99%
“…Of 23 studies, only seven explicitly define trust, while eight conceptualize it and the remaining nine provide neither. This is likely due to trust being an abstract concept that can be relatively difficult to define or generalize (Gebru et al, 2022;Gulati et al, 2019;Sousa et al, 2016), with dynamic characteristics, meaning that trust can change over time and in different contexts and situations (Elkins & Derrick, 2013). The difficulty in defining trust is reflected by findings that only one of the 23 included studies develop their own trust definition (Yan et al, 2013), whereas six studies use Mayer's and Lee and See's trust definitions (Lee & See, 2004;Mayer et al, 2006).…”
Section: Rq1: How Is User Trust In Ai-enabled Systems Defined?mentioning
confidence: 99%