Advancing Responsible AI in Public Sector Application
Responsible 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/...
Sábháilte in:
| Formáid: | Online |
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| Teanga: | Béarla |
| Foilsithe / Cruthaithe: |
Taylor & Francis
2025
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| Ábhair: | |
| Rochtain ar líne: | ONIX_20251022T133414_9781040427989_5 |
| Clibeanna: |
Níl clibeanna ann, Bí ar an gcéad duine le clib a chur leis an taifead seo!
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| _version_ | 1869523478738108416 |
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| collection | Directory of Open Access Books |
| description | Responsible 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. |
| format | Online |
| id | doab-20.500.12854ir-168460 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Taylor & Francis |
| publisherStr | Taylor & Francis |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1684602025-10-23T05:02:26Z Advancing Responsible AI in Public Sector Application Ravindran, Balaraman Singh, Abhishek Participatory AI Loop AI Datasets Ethics Privacy Machine Learning thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering thema EDItEUR::P Mathematics and Science::PD Science: general issues::PDK Science funding and policy thema EDItEUR::P Mathematics and Science::PD Science: general issues::PDM Scientific research thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THR Electrical engineering thema EDItEUR::J Society and Social Sciences::JP Politics and government Responsible 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. 2025-10-23T05:02:24Z 2025-10-23T05:02:24Z 2025-10-22T11:36:29Z 2025 book ONIX_20251022T133414_9781040427989_5 https://library.oapen.org/handle/20.500.12657/107728 9781040427989 9781032703930 9781003663577 9781040428023 https://directory.doabooks.org/handle/20.500.12854/168460 eng open access image/jpeg n/a https://library.oapen.org/bitstream/20.500.12657/107728/1/9781040427989.pdf Taylor & Francis CRC Press 10.1201/9781003663577 10.1201/9781003663577 fa69b019-f4ee-4979-8d42-c6b6c476b5f0 9781040427989 9781032703930 9781003663577 9781040428023 CRC Press 232 open access |
| spellingShingle | Participatory AI Loop AI Datasets Ethics Privacy Machine Learning thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering thema EDItEUR::P Mathematics and Science::PD Science: general issues::PDK Science funding and policy thema EDItEUR::P Mathematics and Science::PD Science: general issues::PDM Scientific research thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THR Electrical engineering thema EDItEUR::J Society and Social Sciences::JP Politics and government Advancing Responsible AI in Public Sector Application |
| title | Advancing Responsible AI in Public Sector Application |
| title_full | Advancing Responsible AI in Public Sector Application |
| title_fullStr | Advancing Responsible AI in Public Sector Application |
| title_full_unstemmed | Advancing Responsible AI in Public Sector Application |
| title_short | Advancing Responsible AI in Public Sector Application |
| title_sort | advancing responsible ai in public sector application |
| topic | Participatory AI Loop AI Datasets Ethics Privacy Machine Learning thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering thema EDItEUR::P Mathematics and Science::PD Science: general issues::PDK Science funding and policy thema EDItEUR::P Mathematics and Science::PD Science: general issues::PDM Scientific research thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THR Electrical engineering thema EDItEUR::J Society and Social Sciences::JP Politics and government |
| topic_facet | Participatory AI Loop AI Datasets Ethics Privacy Machine Learning thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering thema EDItEUR::P Mathematics and Science::PD Science: general issues::PDK Science funding and policy thema EDItEUR::P Mathematics and Science::PD Science: general issues::PDM Scientific research thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THR Electrical engineering thema EDItEUR::J Society and Social Sciences::JP Politics and government |
| url | ONIX_20251022T133414_9781040427989_5 |