Keen, J orcid.org/0000-0003-2753-8276, Ruddle, R, Palczewski, J orcid.org/0000-0003-0235-8746 et al. (4 more authors) (2019) Public services, personal data and machine learning: prospects for infrastructures and ecosystems. In: Kaya, T, (ed.) 19th European Conference on Digital Government (ECDG 2019). European Conference on Digital Government, 24-25 Oct 2019, Nicosia, Cyprus. Academic Conferences Ltd ISBN 9781510899018
Abstract
There is a widespread belief that machine learning tools will improve decision-making in health and social care. Equally there are concerns that the new tools, used with large personal datasets, will jeopardise privacy and erode trust. We reflect on experiences gained in the course of the Quanticode research and development project in England. These suggest that the opportunities are real: it is possible to generate insights that are valued by health and social care planners. The concerns are also real, though, indicating that there is a need to address them, and to balance opportunities and risks. The terrain is also contested, with evidence of differences in values relating to the ownership of datasets in particular. We argue that developments in the governance of tools and datasets will be substantially shaped by the concerns and by debates over values.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This item is protected by copyright. This is an author produced version of an article published in 19th European Conference on Digital Government (ECDG 2019). Uploaded with permission from the publisher . |
Keywords: | machine learning, visualisation, governance, personal data, health care, social care |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Health Sciences (Leeds) > Centre for Health Services Research (Leeds) |
Funding Information: | Funder Grant number EPSRC (Engineering and Physical Sciences Research Council) EP/N013980/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 04 Aug 2020 16:04 |
Last Modified: | 26 Feb 2021 03:04 |
Status: | Published |
Publisher: | Academic Conferences Ltd |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:163528 |