Defining ethical standards for the application of digital tools to population health research
Defining ethical standards for the application of digital tools to population health research
There is growing interest in population health research which uses methods basedon artificial intelligence. Such research draws on a range of clinical and non-clinicaldata to make predictions about health risks, such as identifying epidemics andmonitoring disease spread. Much of this research uses data from social media in thepublic domain or anonymous secondary health data and is therefore exempt fromethics committee scrutiny. While the ethical use and regulation of digital-basedresearch has been discussed, little attention has been given to the ethicsgovernance of such research in higher education institutions in the field of populationhealth. Such governance is essential to how scholars make ethical decisions andprovides assurance to the public that researchers are acting ethically. We propose aprocess of ethics governance for population health research in higher educationinstitutions. The approach takes the form of review after the research has beencompleted, with particular focus on the role artificial intelligence algorithms play inaugmenting decision-making. The first layer of review could be national, openscience repositories for open-source algorithms and affiliated data or informationwhich are developed during research. The second layer would be a sector-specificvalidation of the research processes and algorithms by a committee of academicsand stakeholders with a wide range of expertise across disciplines. The committeecould be created as an off-shoot of an already functioning national oversight body orhealth technology assessment organization. We use case studies of good practice toexplore how this process might operate.
239-244
Samuel, Gabrielle Natalie
66af6213-08de-4c0e-92c1-12083ec456e3
Derrick, Gemma
9403a4d9-e3f2-40d9-9483-7fcad8523468
1 April 2020
Samuel, Gabrielle Natalie
66af6213-08de-4c0e-92c1-12083ec456e3
Derrick, Gemma
9403a4d9-e3f2-40d9-9483-7fcad8523468
Samuel, Gabrielle Natalie and Derrick, Gemma
(2020)
Defining ethical standards for the application of digital tools to population health research.
Bulletin of the World Health Organization, 98 (4), .
(doi:10.2471/BLT.19.237370).
Abstract
There is growing interest in population health research which uses methods basedon artificial intelligence. Such research draws on a range of clinical and non-clinicaldata to make predictions about health risks, such as identifying epidemics andmonitoring disease spread. Much of this research uses data from social media in thepublic domain or anonymous secondary health data and is therefore exempt fromethics committee scrutiny. While the ethical use and regulation of digital-basedresearch has been discussed, little attention has been given to the ethicsgovernance of such research in higher education institutions in the field of populationhealth. Such governance is essential to how scholars make ethical decisions andprovides assurance to the public that researchers are acting ethically. We propose aprocess of ethics governance for population health research in higher educationinstitutions. The approach takes the form of review after the research has beencompleted, with particular focus on the role artificial intelligence algorithms play inaugmenting decision-making. The first layer of review could be national, openscience repositories for open-source algorithms and affiliated data or informationwhich are developed during research. The second layer would be a sector-specificvalidation of the research processes and algorithms by a committee of academicsand stakeholders with a wide range of expertise across disciplines. The committeecould be created as an off-shoot of an already functioning national oversight body orhealth technology assessment organization. We use case studies of good practice toexplore how this process might operate.
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Accepted/In Press date: 25 October 2019
e-pub ahead of print date: 17 January 2020
Published date: 1 April 2020
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Together, national infrastructures, which incorporate ex-post review for artificial intelligence-based algorithms designed for health applications can start to re-balance the ethics ecosystem. In this way nations would begin the process of developing a new-shared understanding of ethics best practice for artificial intelligence-based public health research. Within this best practice, artificial intelligence-associated research will be openly scrutinized before any application that affects wider society is disseminated and used, to minimize as much as possible the potential for these systems to cause harm. Whether artificial intelligence-based health research continues to generate new ethical concerns or becomes just one more method in a researcher’s toolbox we must take care to avoid any unintended consequences of big data studies. ■ Funding: The authors received a Seed Award in Humanities and Social Science from the Wellcome Trust for the project entitled “The ethical governance of artificial intelligence health research in higher education institutions,” grant number: 213619/Z/18/Z/.
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© 2020, World Health Organization. All rights reserved.
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Local EPrints ID: 451217
URI: http://eprints.soton.ac.uk/id/eprint/451217
ISSN: 0042-9686
PURE UUID: 4d0a25e5-70de-4c68-9839-8c0672d5065c
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Date deposited: 14 Sep 2021 17:10
Last modified: 16 Mar 2024 10:28
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Author:
Gemma Derrick
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