Dr Yen Nee Wong Y.Wong@napier.ac.uk
Research Fellow
Conditional trust: Citizens’ council on data-driven media personalisation and public expectations of transparency and accountability
Wong, Yen Nee; Jones, Rhia; Das, Ranjana; Jackson, Philip
Authors
Rhia Jones
Ranjana Das
Philip Jackson
Abstract
This article presents findings from a rigorous, three-wave series of qualitative research into public expectations of data-driven media technologies, conducted in England, United Kingdom. Through a range of carefully chosen scenarios and deliberations around the risks and benefits afforded by data-driven media personalisation technologies and algorithms, we paid close attention to citizens’ voices as our multidisciplinary team sought to engage the public on what ‘good’ might look like in the context of media personalisation. We paid particular attention to risks and opportunities, examining practical use-cases and scenarios, and our three-wave councils culminated in citizens producing recommendations for practice and policy. In this article, we focus particularly on citizens’ ethical assessment, critique and improvements proposed on media personalisation methods in relation to benefits, fairness, safety, transparency and accountability. Our findings demonstrate that public expectations and trust in data-driven technologies are, fundamentally, conditional, with significant emphasis placed on transparency, inclusiveness and accessibility. Our findings also point to the context dependency of public expectations, which appears more pertinent to citizens, in hard political as opposed to entertainment spaces. Our conclusions are significant for global data-driven media personalisation environments – in terms of embedding citizens’ focus on transparency and accountability, but equally, also, we argue that strengthening research methodology, innovatively and rigorously to build in citizen voices at the very inception and core of design – must become a priority in technology development.
Journal Article Type | Article |
---|---|
Acceptance Date | Jun 30, 2023 |
Online Publication Date | Aug 18, 2023 |
Publication Date | 2023-07 |
Deposit Date | Aug 25, 2023 |
Publicly Available Date | Aug 28, 2023 |
Print ISSN | 2053-9517 |
Electronic ISSN | 2053-9517 |
Publisher | SAGE Publications |
Peer Reviewed | Peer Reviewed |
Volume | 10 |
Issue | 2 |
DOI | https://doi.org/10.1177/20539517231184892 |
Keywords | User experience, trust, data-driven, personalisation, algorithms, publics |
Files
Conditional trust: Citizens’ council on data-driven media personalisation and public expectations of transparency and accountability
(504 Kb)
PDF
Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
You might also like
LGBT+ ballroom dancers and their shoes: Fashioning the queer self into existence
(2023)
Journal Article
Review Essay: On Their Own: Women, Urbanization, and the Right to the City in South Africa
(2017)
Journal Article
Downloadable Citations
About Edinburgh Napier Research Repository
Administrator e-mail: repository@napier.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search