| 000 | 05518cam a22004458i 4500 | ||
|---|---|---|---|
| 999 |
_c93603 _d93603 |
||
| 001 | in00024319071 | ||
| 003 | DLC | ||
| 005 | 20260221100742.0 | ||
| 007 | t| | ||
| 008 | 250908s2026 flu b 001 0 eng | ||
| 010 | _a 2025019967 | ||
| 020 |
_a9781032703930 _qhardback |
||
| 020 |
_a9781041122012 _qpaperback |
||
| 020 |
_z9781003663577 _qebook |
||
| 040 |
_aDLC _beng _erda _cDLC _dDLC-MRC _dDLC _dDLC-MRC _dDLC |
||
| 041 | _aeng | ||
| 042 | _apcc | ||
| 050 | 0 | 0 |
_aJF1525.A8 _bA385 2026 |
| 245 | 0 | 0 |
_aAdvancing responsible AI in public sector application / _cedited by Abhishek Singh and Balaraman Ravindran. |
| 246 | 3 | _aAdvancing responsible artificial intelligence in public sector application | |
| 250 | _aGPAI edition, first edition. | ||
| 263 | _a2510 | ||
| 264 | 1 |
_aBoca Raton, FL : _bCRC Press, _c2026. |
|
| 300 | _a1 online resource | ||
| 336 |
_atext _btxt _2rdacontent |
||
| 337 |
_acomputer _bc _2rdamedia |
||
| 338 |
_aonline resource _bcr _2rdacarrier |
||
| 504 | _aIncludes bibliographical references and index. | ||
| 505 | 0 | _aRaising the standard in AI procurement : global opportunity and challenges / Gisele Waters, Cari Miller -- Data empowerment and protection architecture (DEPA) for training ML models / Shyam Sundaram, Kapil Vaswani, Gaurav Agarwal, Sunu Engineer, Sridhar AVS -- Generative AI governance : technological monoculture, market structure and the risk of correlated failures / Ramayya Krishnan, Prasanna Parasurama, Joao Sedoc, Arun Sundararajan -- Empowering citizens through responsible AI governance : policy recommendations for public algorithm registers / Jens Meijen, Niharika Gujela -- Responsible adoption of cloud-based artificial intelligence in healthcare : a validation case study of multiple artificial intelligence algorithms for diabetic retinopathy screening in public health settings / Mona Duggal, Anshul Chauhan, Ankita Kankaria, Preeti Syal, Vishali Gupta, Priyanka Verma, Vaibhav Miglani, Deepmala Budhija, Luke Vale -- Developing community led AI : notes from the trenches / Tarunima Prabhakar, Cheshta Arora, Arnav Arora -- Risk assessment methodology for AI regulation and navigating liability determination in AI driven world / Adithya Mohan, Karthik Satishkumar -- Harnessing the potential of AI for Indian agriculture : leveraging "bhashini" as a tool for deploying responsible AI and increasing uptake of AI applications among farmers / Abhishek Raj, Harsh Singh, Anshul Pachouri -- Regional inequities in extraction and flow of resources that support and power the design, development and access to AI : experiences from India and Kenya / Saikat Datta, Shachi Solanki, Anand Venkatanaryanan -- Assessing the trustworthiness of generative AI used for higher education / Adarsh Srivastava, Gokul Gawande, Divya Dwivedi, Manu Dev, Vinayak Kottawar, Roberto V. Zicari -- Actionable ethics : from philosophical principles to operational initiatives for responsible AI projects in public sector in the French context / Anthéa Serafin, Lisa Fériol, Bertrand Monthubert -- Supporting AI at scale in the APEC Region through international standards / Aurelie Jacquet, Karen Batt, Jesse Riddell -- A policy framework for third party auditing of AI systems / Harsh Lailer, Gadamsetti Srija, Aseem Saxena, Agrima Lailer -- AI in the healthcare sector : insights from Rwanda's Mbaze Chatbot Project / Lea Gimpel, Keegan McBride. | |
| 520 | _a"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 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 the 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"-- Provided by publisher. | ||
| 540 |
_aCreative Commons Attribution-NonCommercial-NoDerivatives 4.0 International _fCC BY-NC-ND 4.0 _uhttps://creativecommons.org/licenses/by-nc-nd/4.0 |
||
| 653 | _aArtificial intelligence in public administration | ||
| 655 | 4 | _aElectronic books. | |
| 700 | 1 |
_aSingh, Abhishek, _d1976- _eeditor _4http://id.loc.gov/vocabulary/relators/edt _0http://id.loc.gov/authorities/names/no2008024737 _1http://id.loc.gov/rwo/agents/no2008024737 |
|
| 700 | 1 |
_aRavindran, Balaraman _eeditor _4http://id.loc.gov/vocabulary/relators/edt _0http://id.loc.gov/authorities/names/n2025510825 _1http://id.loc.gov/rwo/agents/n2025510825 |
|
| 856 | 4 | 0 |
_uhttps://directory.doabooks.org/handle/20.500.12854/168460 _yFull text is available at the Directory of Open Access Books. Click here to view. |
| 906 |
_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg |
||
| 942 |
_2ddc _cOA |
||