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AI, big data, and the future of consent

In this paper, we discuss several problems with current Big data practices which, we claim, seriously erode the role of informed consent as it pertains to the use of personal information. To illustrate these problems, we consider how the notion of informed consent has been understood and operational...

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Detalles Bibliográficos
Autores principales: Andreotta, Adam J., Kirkham, Nin, Rizzi, Marco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer London 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8404542/
https://www.ncbi.nlm.nih.gov/pubmed/34483498
http://dx.doi.org/10.1007/s00146-021-01262-5
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author Andreotta, Adam J.
Kirkham, Nin
Rizzi, Marco
author_facet Andreotta, Adam J.
Kirkham, Nin
Rizzi, Marco
author_sort Andreotta, Adam J.
collection PubMed
description In this paper, we discuss several problems with current Big data practices which, we claim, seriously erode the role of informed consent as it pertains to the use of personal information. To illustrate these problems, we consider how the notion of informed consent has been understood and operationalised in the ethical regulation of biomedical research (and medical practices, more broadly) and compare this with current Big data practices. We do so by first discussing three types of problems that can impede informed consent with respect to Big data use. First, we discuss the transparency (or explanation) problem. Second, we discuss the re-repurposed data problem. Third, we discuss the meaningful alternatives problem. In the final section of the paper, we suggest some solutions to these problems. In particular, we propose that the use of personal data for commercial and administrative objectives could be subject to a ‘soft governance’ ethical regulation, akin to the way that all projects involving human participants (e.g., social science projects, human medical data and tissue use) are regulated in Australia through the Human Research Ethics Committees (HRECs). We also consider alternatives to the standard consent forms, and privacy policies, that could make use of some of the latest research focussed on the usability of pictorial legal contracts.
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spelling pubmed-84045422021-08-30 AI, big data, and the future of consent Andreotta, Adam J. Kirkham, Nin Rizzi, Marco AI Soc Open Forum In this paper, we discuss several problems with current Big data practices which, we claim, seriously erode the role of informed consent as it pertains to the use of personal information. To illustrate these problems, we consider how the notion of informed consent has been understood and operationalised in the ethical regulation of biomedical research (and medical practices, more broadly) and compare this with current Big data practices. We do so by first discussing three types of problems that can impede informed consent with respect to Big data use. First, we discuss the transparency (or explanation) problem. Second, we discuss the re-repurposed data problem. Third, we discuss the meaningful alternatives problem. In the final section of the paper, we suggest some solutions to these problems. In particular, we propose that the use of personal data for commercial and administrative objectives could be subject to a ‘soft governance’ ethical regulation, akin to the way that all projects involving human participants (e.g., social science projects, human medical data and tissue use) are regulated in Australia through the Human Research Ethics Committees (HRECs). We also consider alternatives to the standard consent forms, and privacy policies, that could make use of some of the latest research focussed on the usability of pictorial legal contracts. Springer London 2021-08-30 2022 /pmc/articles/PMC8404542/ /pubmed/34483498 http://dx.doi.org/10.1007/s00146-021-01262-5 Text en © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Open Forum
Andreotta, Adam J.
Kirkham, Nin
Rizzi, Marco
AI, big data, and the future of consent
title AI, big data, and the future of consent
title_full AI, big data, and the future of consent
title_fullStr AI, big data, and the future of consent
title_full_unstemmed AI, big data, and the future of consent
title_short AI, big data, and the future of consent
title_sort ai, big data, and the future of consent
topic Open Forum
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8404542/
https://www.ncbi.nlm.nih.gov/pubmed/34483498
http://dx.doi.org/10.1007/s00146-021-01262-5
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