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dc.contributor.authorMichael Anderson-
dc.contributor.authorJohnathan Mun-
dc.identifier.citationPublished--Unlimited Distributionen_US
dc.descriptionAcquisition Management / Defense Acquisition Community Contributoren_US
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’s 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 a probability-based prediction of risk.-
dc.description.sponsorshipAcquisition Research Programen_US
dc.publisherAcquisition Research Programen_US
dc.relation.ispartofseriesAcquisition Management Presentation;SYM-AM-21-172-
dc.relation.ispartofseriesAcquisition Management Video;SYM-AM-21-229-
dc.subjectTechnology Trust|en_US
dc.subjectAutonomous Systems-
dc.subjectHigh-Risk Applications-
dc.titleTechnology Trust: The Impact of Anthropomorphic System Information on the Acceptance of Sutonomous Systems Used in High-Risk Applicationsen_US
Appears in Collections:Annual Acquisition Research Symposium Proceedings & Presentations

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SYM-AM-21-172.pdfPresentation PDF1.44 MBAdobe PDFView/Open

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