A novel framework for identifying the threshold of trust-worthiness of Artificial Intelligence

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dc.contributor.authorForsyth, Tim
dc.contributor.authorKumar, Ajay
dc.contributor.authorEconomou, John T.
dc.date.accessioned2023-11-10T11:16:21Z
dc.date.available2023-11-10T11:16:21Z
dc.date.issued2021-10-12
dc.descriptionPresentationen_UK
dc.identifier.citationKumar A, Forsyth T, Economou J. (2021) A novel framework for identifying the threshold of trust-worthiness of Artificial Intelligence. Presented at: AI Fest 4: Trustworthy AI, 12-13 October 2021, Virtual Eventen_UK
dc.identifier.urihttps://www.gov.uk/government/news/global-ai-experts-to-present-at-dstls-virtual-ai-fest
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/20533
dc.language.isoenen_UK
dc.publisherCranfield Universityen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectTrustworthiness Frameworken_UK
dc.subjectArtificial Intelligenceen_UK
dc.subjectFuzzy Logicen_UK
dc.titleA novel framework for identifying the threshold of trust-worthiness of Artificial Intelligenceen_UK
dc.typePresentationen_UK

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