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dc.contributor.editorRavindran, Balaraman
dc.contributor.editorSingh, Abhishek
dc.date.accessioned2025-10-22T11:36:29Z
dc.date.available2025-10-22T11:36:29Z
dc.date.issued2025
dc.identifierONIX_20251022T133414_9781040427989_5
dc.identifier.urihttps://library.oapen.org/handle/20.500.12657/107728
dc.description.abstractResponsible use of AI in public sector applications requires engagement with various technical and non-technical areas such as human rights, inclusion, diversity, innovation and economic growth. The book covers topics spanning the technological socio-economic spectrum, including the potential of AI/ML technologies to address social and political inequities, privacy-enhancing technologies for datasets, friction-less data sharing and data stewardship models, regional/geographical inequities in extraction and so forth. Features: Focuses on technical aspects of responsible AI in the public sector Covers a wide range of topics spanning the technological socio-economic spectrum Presents viewpoints from public sector agencies as well as from practitioners Discusses privacy-enhancing technologies for collecting, processing and storing datasets, and friction Reviews frameworks to identify and address biased AI outcomes in the design, development and use of AI This book is aimed at professionals, researchers and students in artificial intelligence, computer science and engineering, policy-makers, social scientists, economists and lawyers.
dc.languageEnglish
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence
dc.subject.classificationthema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering
dc.subject.classificationthema EDItEUR::P Mathematics and Science::PD Science: general issues::PDK Science funding and policy
dc.subject.classificationthema EDItEUR::P Mathematics and Science::PD Science: general issues::PDM Scientific research
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UB Information technology: general topics
dc.subject.classificationthema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THR Electrical engineering
dc.subject.classificationthema EDItEUR::J Society and Social Sciences::JP Politics and government
dc.subject.otherParticipatory AI
dc.subject.otherLoop AI
dc.subject.otherDatasets
dc.subject.otherEthics
dc.subject.otherPrivacy
dc.subject.otherMachine Learning
dc.titleAdvancing Responsible AI in Public Sector Application
dc.title.alternativeGPAI Edition
dc.typebook
oapen.identifier.doi10.1201/9781003663577
oapen.relation.isPublishedBy7b3c7b10-5b1e-40b3-860e-c6dd5197f0bb
oapen.relation.isbn9781040427989
oapen.relation.isbn9781032703930
oapen.relation.isbn9781003663577
oapen.relation.isbn9781040428023
oapen.imprintCRC Press
oapen.pages232


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