Please use this identifier to cite or link to this item:
https://dair.nps.edu/handle/123456789/4390
Title: | Technology Trust: The Impact of Trust Metrics on the Adoption of Autonomous Systems Used in High-Risk Applications |
Authors: | Michael Anderson, Johnathan Mun |
Keywords: | Technology Trust Metrics Autonomous Systems High-Risk Applications |
Issue Date: | 10-May-2021 |
Publisher: | Acquisition Research Program |
Citation: | Published--Unlimited Distribution |
Series/Report no.: | Acquisition Management;SYM-AM-21-083 |
Abstract: | As 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. |
Description: | Acquisition Management / Defense Acquisition Community Contributor |
URI: | https://dair.nps.edu/handle/123456789/4390 |
Appears in Collections: | Annual Acquisition Research Symposium Proceedings & Presentations |
Files in This Item:
File | Description | Size | Format | |
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SYM-AM-21-083.pdf | 543.4 kB | Adobe PDF | View/Open |
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