Data Trusts: Ethics, Architecture and Governance for Trustworthy Data Stewardship
Data Trusts: Ethics, Architecture and Governance for Trustworthy Data Stewardship
In their report on the development of the UK AI industry, Wendy Hall and Jérôme Pesenti recommend the establishment of data trusts, “proven and trusted frameworks and agreements” that will “ensure exchanges [of data] are secure and mutually beneficial” by promoting trust in the use of data for AI. This paper defends the following thesis: A data trust works within the law to provide ethical, architectural and governance support for trustworthy data processing. Data trusts are therefore both constraining and liberating. They constrain: they respect current law, so they cannot render currently illegal actions legal. They are intended to increase trust, and so they will typically act as further constraints on data processors, adding the constraints of trustworthiness to those of law. Yet they also liberate: if data processors are perceived as trustworthy, they will get improved access to data. The paper addresses the areas of: trust and trustworthiness; ethics; architecture; legal status.
Trust, Ethics, Data Sharing, Trustworthiness, Governance, Trust law, equity, web observatory
University of Southampton
O'hara, Kieron
0a64a4b1-efb5-45d1-a4c2-77783f18f0c4
13 February 2019
O'hara, Kieron
0a64a4b1-efb5-45d1-a4c2-77783f18f0c4
O'hara, Kieron
(2019)
Data Trusts: Ethics, Architecture and Governance for Trustworthy Data Stewardship
(WSI White Papers, 1)
Southampton.
University of Southampton
27pp.
(doi:10.5258/SOTON/WSI-WP001).
Record type:
Monograph
(Project Report)
Abstract
In their report on the development of the UK AI industry, Wendy Hall and Jérôme Pesenti recommend the establishment of data trusts, “proven and trusted frameworks and agreements” that will “ensure exchanges [of data] are secure and mutually beneficial” by promoting trust in the use of data for AI. This paper defends the following thesis: A data trust works within the law to provide ethical, architectural and governance support for trustworthy data processing. Data trusts are therefore both constraining and liberating. They constrain: they respect current law, so they cannot render currently illegal actions legal. They are intended to increase trust, and so they will typically act as further constraints on data processors, adding the constraints of trustworthiness to those of law. Yet they also liberate: if data processors are perceived as trustworthy, they will get improved access to data. The paper addresses the areas of: trust and trustworthiness; ethics; architecture; legal status.
Text
WSI White Paper 1
- Version of Record
More information
Published date: 13 February 2019
Keywords:
Trust, Ethics, Data Sharing, Trustworthiness, Governance, Trust law, equity, web observatory
Identifiers
Local EPrints ID: 428276
URI: http://eprints.soton.ac.uk/id/eprint/428276
PURE UUID: a0701bbc-8d07-480c-962e-381e968128ae
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Date deposited: 20 Feb 2019 17:30
Last modified: 16 Mar 2024 03:20
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