ELVIRA PEREZ VALLEJOS elvira.perez@nottingham.ac.uk
Professor of Digital Technology For Mental Health
Young people's policy recommendations on algorithm fairness
Perez, Elvira; Koene, Ansgar; Portillo, Virginia; Dowthwaite, Liz; Cano, Monica
Authors
Ansgar Koene
Dr VIRGINIA PORTILLO VIRGINIA.PORTILLO@NOTTINGHAM.AC.UK
Research Fellow
LIZ DOWTHWAITE LIZ.DOWTHWAITE@NOTTINGHAM.AC.UK
Senior Research Fellow
Monica Cano
Abstract
This paper explores the policy recommendations made by young people regarding algorithm fairness. It describes a piece of ongoing research developed to bring children and young people to the front line of the debate regarding children's digital rights. We employed the Youth Juries methodology which was designed to facilitate learning through discussions. The juries capture the deliberation process on a specific digital right, the right to know how algorithms govern and influence the Web and its users. Preliminary results show that young people demand to know more about algorithms, they want more transparency, more options, and more control about the way algorithms use their personal data.
Citation
Perez, E., Koene, A., Portillo, V., Dowthwaite, L., & Cano, M. (2017, June). Young people's policy recommendations on algorithm fairness. Presented at ACM Web Science Conference (WebSci' 17), Troy, New York, USA
Presentation Conference Type | Edited Proceedings |
---|---|
Conference Name | ACM Web Science Conference (WebSci' 17) |
Start Date | Jun 25, 2017 |
End Date | Jun 28, 2017 |
Acceptance Date | May 25, 2017 |
Publication Date | Jun 25, 2017 |
Deposit Date | Feb 26, 2018 |
Journal | Proceedings of the 2017 ACM on Web Science Conference |
Peer Reviewed | Peer Reviewed |
Pages | 247-251 |
Book Title | WebSci '17: Proceedings of the 2017 ACM on Web Science Conference |
ISBN | 9781450348966 |
DOI | https://doi.org/10.1145/3091478.3091512 |
Keywords | Youth jury; algorithm fairness; youth opinion; deliberation; digital literacy; digital citizenship, privacy; policy |
Public URL | https://nottingham-repository.worktribe.com/output/868506 |
Publisher URL | https://dl.acm.org/citation.cfm?id=3091512 |
Additional Information | Published in: WebSci '17 : proceedings of the 2017 ACM on Web Science Conference. New York : ACM, 2017, ISBN: 978-1-4503-4896-6. pp. 247-251, doi:10.1145/3091478.3091512 |
Contract Date | Feb 26, 2018 |
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