Pournaras, E. orcid.org/0000-0003-3900-2057, Ballandies, M.C., Bennati, S. orcid.org/0000-0001-7603-8564 et al. (1 more author) (2024) Collective privacy recovery: Data-sharing coordination via decentralized artificial intelligence. PNAS Nexus, 3 (2). ARTN pgae029. ISSN 2752-6542
Abstract
Collective privacy loss becomes a colossal problem, an emergency for personal freedoms and democracy. But, are we prepared to handle personal data as scarce resource and collectively share data under the doctrine: as little as possible, as much as necessary? We hypothesize a significant privacy recovery if a population of individuals, the data collective, coordinates to share minimum data for running online services with the required quality. Here, we show how to automate and scale-up complex collective arrangements for privacy recovery using decentralized artificial intelligence. For this, we compare for the first time attitudinal, intrinsic, rewarded, and coordinated data sharing in a rigorous living-lab experiment of high realism involving real data disclosures. Using causal inference and cluster analysis, we differentiate criteria predicting privacy and five key data-sharing behaviors. Strikingly, data-sharing coordination proves to be a win–win for all: remarkable privacy recovery for people with evident costs reduction for service providers.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2024. Published by Oxford University Press on behalf of National Academy of Sciences. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Computer Sciences; Social and Political Sciences |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 04 Apr 2024 10:31 |
Last Modified: | 04 Apr 2024 10:31 |
Published Version: | http://dx.doi.org/10.1093/pnasnexus/pgae029 |
Status: | Published |
Publisher: | Oxford University Press (OUP) |
Identification Number: | 10.1093/pnasnexus/pgae029 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:210558 |