A4 Refereed article in a conference publication
Explaining data-driven personas to end users
Authors: Soon Gyo Jung, Joni Salminen, Bernard J. Jansen
Editors: Alison Smith-Renner, Styliani Kleanthous, Brian Lim, Tsvi Kuflik, Simone Stumpf, Jahna Otterbacher, Advait Sarkar, Casey Dugan, Avital Shulner
Conference name: Workshop on Explainable Smart Systems for Algorithmic Transparency in Emerging Technologies
Publisher: CEUR-WS
Publication year: 2020
Journal: CEUR Workshop Proceedings
Book title : 2020 Workshop on Explainable Smart Systems for Algorithmic Transparency in Emerging Technologies, ExSS-ATEC 2020
Journal name in source: CEUR Workshop Proceedings
Series title: CEUR Workshop Proceedings
Volume: 2582
ISSN: 1613-0073
Web address : http://ceur-ws.org/Vol-2582/
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/48042328
Enabled by digital user data and algorithms, persona user interfaces
(UI) are moving to digital formats. However, algorithms and user data,
if left unexplained to end users, might leave data-driven personas
(DDPs) difficult to understand and trust. This is because the data and
the way it is processed are complex and not self-evident, requiring
explanations of the DDP information and UIs. In this research, we
provide a proof of concept for adding transparency to DDP using a real
system UI. Furthermore, we demonstrate ways to add breakdown information
that can help alleviate user stereotyping associated with the use of
personas.
Downloadable publication This is an electronic reprint of the original article. |  |
