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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...

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Autores principales: Barrance, Ethan, Kazim, Emre, Hilliard, Airlie, Trengove, Markus, Zannone, Sara, Koshiyama, Adriano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
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.
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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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