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Overview and commentary of the CDEI's extended roadmap to an effective AI assurance ecosystem
In recent years, the field of ethical artificial intelligence (AI), or AI ethics, has gained traction and aims to develop guidelines and best practices for the responsible and ethical use of AI across sectors. As part of this, nations have proposed AI strategies, with the UK releasing both national...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9400827/ https://www.ncbi.nlm.nih.gov/pubmed/36034593 http://dx.doi.org/10.3389/frai.2022.932358 |
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author | Barrance, Ethan Kazim, Emre Hilliard, Airlie Trengove, Markus Zannone, Sara Koshiyama, Adriano |
author_facet | Barrance, Ethan Kazim, Emre Hilliard, Airlie Trengove, Markus Zannone, Sara Koshiyama, Adriano |
author_sort | Barrance, Ethan |
collection | PubMed |
description | In recent years, the field of ethical artificial intelligence (AI), or AI ethics, has gained traction and aims to develop guidelines and best practices for the responsible and ethical use of AI across sectors. As part of this, nations have proposed AI strategies, with the UK releasing both national AI and data strategies, as well as a transparency standard. Extending these efforts, the Centre for Data Ethics and Innovation (CDEI) has published an AI Assurance Roadmap, which is the first of its kind and provides guidance on how to manage the risks that come from the use of AI. In this article, we provide an overview of the document's vision for a “mature AI assurance ecosystem” and how the CDEI will work with other organizations for the development of regulation, industry standards, and the creation of AI assurance practitioners. We also provide a commentary of some key themes identified in the CDEI's roadmap in relation to (i) the complexities of building “justified trust”, (ii) the role of research in AI assurance, (iii) the current developments in the AI assurance industry, and (iv) convergence with international regulation. |
format | Online Article Text |
id | pubmed-9400827 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94008272022-08-25 Overview and commentary of the CDEI's extended roadmap to an effective AI assurance ecosystem Barrance, Ethan Kazim, Emre Hilliard, Airlie Trengove, Markus Zannone, Sara Koshiyama, Adriano Front Artif Intell Artificial Intelligence In recent years, the field of ethical artificial intelligence (AI), or AI ethics, has gained traction and aims to develop guidelines and best practices for the responsible and ethical use of AI across sectors. As part of this, nations have proposed AI strategies, with the UK releasing both national AI and data strategies, as well as a transparency standard. Extending these efforts, the Centre for Data Ethics and Innovation (CDEI) has published an AI Assurance Roadmap, which is the first of its kind and provides guidance on how to manage the risks that come from the use of AI. In this article, we provide an overview of the document's vision for a “mature AI assurance ecosystem” and how the CDEI will work with other organizations for the development of regulation, industry standards, and the creation of AI assurance practitioners. We also provide a commentary of some key themes identified in the CDEI's roadmap in relation to (i) the complexities of building “justified trust”, (ii) the role of research in AI assurance, (iii) the current developments in the AI assurance industry, and (iv) convergence with international regulation. Frontiers Media S.A. 2022-08-10 /pmc/articles/PMC9400827/ /pubmed/36034593 http://dx.doi.org/10.3389/frai.2022.932358 Text en Copyright © 2022 Barrance, Kazim, Hilliard, Trengove, Zannone and Koshiyama. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Artificial Intelligence Barrance, Ethan Kazim, Emre Hilliard, Airlie Trengove, Markus Zannone, Sara Koshiyama, Adriano Overview and commentary of the CDEI's extended roadmap to an effective AI assurance ecosystem |
title | Overview and commentary of the CDEI's extended roadmap to an effective AI assurance ecosystem |
title_full | Overview and commentary of the CDEI's extended roadmap to an effective AI assurance ecosystem |
title_fullStr | Overview and commentary of the CDEI's extended roadmap to an effective AI assurance ecosystem |
title_full_unstemmed | Overview and commentary of the CDEI's extended roadmap to an effective AI assurance ecosystem |
title_short | Overview and commentary of the CDEI's extended roadmap to an effective AI assurance ecosystem |
title_sort | overview and commentary of the cdei's extended roadmap to an effective ai assurance ecosystem |
topic | Artificial Intelligence |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9400827/ https://www.ncbi.nlm.nih.gov/pubmed/36034593 http://dx.doi.org/10.3389/frai.2022.932358 |
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