File:TRUST AND UNDERSTANDABILITY IN AUTONOMOUS AND UNMANNED SURFACE VEHICLES (IA trustandundersta1094563429).pdf

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TRUST AND UNDERSTANDABILITY IN AUTONOMOUS AND UNMANNED SURFACE VEHICLES   (Wikidata search (Cirrus search) Wikidata query (SPARQL)  Create new Wikidata item based on this file)
Author
Adesanya, Kehinde A.
Shivashankar, Santhosh K.
image of artwork listed in title parameter on this page
Title
TRUST AND UNDERSTANDABILITY IN AUTONOMOUS AND UNMANNED SURFACE VEHICLES
Publisher
Monterey, CA; Naval Postgraduate School
Description

Within the human-machine relationship, distrust can arise. The Department of Defense utilizes automation, autonomous systems, and artificial intelligence to reduce cognitive workload and improve mission capabilities; however, adoption rates of autonomous unmanned surface vehicles (USVs) remain low. This thesis asks how human distrust of machines and machine learning relates to adoption rates. First, we identify trust components by building upon a model created by Gari Palmer, Anne Selwyn, and Dan Zwillinger in 2016. Then, we identify components that apply to the military environment that could affect the adoption rate such as smoothing time, policies and regulations, competition, robustness, understandability, subjective norm, human interaction, policy effect, risk to force, time sensitivity, war, time between wars, and catastrophic failure. Through S-curve and smoothing modeling, we find that trust components can be quantified in the human machine relationship as positive or negative trust, and that a relationship exists between understandability and adoption. While autonomous system components generally undergo rigorous testing to verify suitability and operability, human-machine trust is not usually incorporated into design and testing phases. When trust is built into the design and acquisition process, adoption of autonomous USVs is more likely to increase. Researchers can apply our trust model to future autonomous systems to mitigate distrust and human-machine teaming.


Subjects: trust; understandability; autonomous; autonomy; transparency; adoption; unmanned; quantitative; USV
Language English
Publication date September 2019
Current location
IA Collections: navalpostgraduateschoollibrary; fedlink
Accession number
trustandundersta1094563429
Source
Internet Archive identifier: trustandundersta1094563429
https://archive.org/download/trustandundersta1094563429/trustandundersta1094563429.pdf
Permission
(Reusing this file)
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.

Licensing[edit]

Public domain
This work is in the public domain in the United States because it is a work prepared by an officer or employee of the United States Government as part of that person’s official duties under the terms of Title 17, Chapter 1, Section 105 of the US Code. Note: This only applies to original works of the Federal Government and not to the work of any individual U.S. state, territory, commonwealth, county, municipality, or any other subdivision. This template also does not apply to postage stamp designs published by the United States Postal Service since 1978. (See § 313.6(C)(1) of Compendium of U.S. Copyright Office Practices). It also does not apply to certain US coins; see The US Mint Terms of Use.

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Date/TimeThumbnailDimensionsUserComment
current15:07, 25 July 2020Thumbnail for version as of 15:07, 25 July 20201,275 × 1,650, 76 pages (1.89 MB) (talk | contribs)FEDLINK - United States Federal Collection trustandundersta1094563429 (User talk:Fæ/IA books#Fork8) (batch 1993-2020 #31045)

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