Please use this identifier to cite or link to this item: https://dair.nps.edu/handle/123456789/1733
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dc.contributor.authorMichael Anderson
dc.contributor.authorJohnathan Mun
dc.date.accessioned2020-03-16T18:00:53Z-
dc.date.available2020-03-16T18:00:53Z-
dc.date.issued2019-05-13
dc.identifier.citationPublished--Unlimited Distribution
dc.identifier.urihttps://dair.nps.edu/handle/123456789/1733-
dc.descriptionAcquisition Management / Defense Acquisition Community Contributor
dc.description.abstractAs autonomous systems become more capable, end users must make decisions about how and when to deploy such technology. The use and adoption of a technology to replace a human actor depends on its ability to perform a desired task and on the user's experience-based trust that it will do so. The development of experience-based trust in autonomous systems is expensive and high-risk. This work focuses on identifying a methodology for technology discovery that reduces the need for experience-based trust and contributes to increased adoption of autonomous systems. Initial research reveals two problems associated with the adoption of high-risk technologies: (1) end user refusal to accept new systems without high levels of initial trust and (2) lost or uncollected experience-based trust data. The main research hypothesis is that a trust score, or trust metric, can influence the initial formation of trust by functioning as a surrogate for experience-based trust, and that trust in technology can be measured through an odds-based prediction of risk.
dc.description.sponsorshipAcquisition Research Program
dc.languageEnglish (United States)
dc.publisherAcquisition Research Program
dc.relation.ispartofseriesAcquisition Management
dc.relation.ispartofseriesSYM-AM-19-046
dc.subjectTrust Metrics
dc.subjectAutonomous Systems
dc.subjectExperience Based Trust
dc.subjectTrust Metric
dc.titleTechnology Trust: The Impact of Trust Metrics on the Adoption of Autonomous Systems Used in High-Risk Applications
dc.typeArticle
Appears in Collections:Annual Acquisition Research Symposium Proceedings & Presentations

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