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Technology-facilitated Societal Consensus
Umeå University, Faculty of Science and Technology, Department of Computing Science. (Interactive and Intelligent Systems Group)ORCID iD: 0000-0002-6458-2252
Umeå University, Faculty of Science and Technology, Department of Computing Science. AI-Robolab/ICR Computer Science and Communications University of Luxembourg Esch-sur-Alzette, Luxembourg.ORCID iD: 0000-0001-7784-6176
2019 (English)In: UMAP'19 Adjunct: Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization, Larnaca, Cyprus: ACM Digital Library, 2019, p. 3-7Conference paper, Published paper (Refereed)
Abstract [en]

The spread of radical opinions, facilitated by homophilic Internet communities (echo chambers), has become a threat to the stability of societies around the globe. The concept of choice architecture-the design of choice information for consumers with the goal of facilitating societally beneficial decisions-provides a promising (although not uncontroversial) general concept to address this problem. The choice architecture approach is reflected in recent proposals advocating for recommender systems that consider the societal impact of their recommendations and not only strive to optimize revenue streams. However, the precise nature of the goal state such systems should work towards remains an open question. In this paper, we suggest that this goal state can be defined by considering target opinion spread in a society on different topics of interest as a multivariate normal distribution; i.e., while there is a diversity of opinions, most people have similar opinions on most topics. We explain why this approach is promising, and list a set of cross-disciplinary research challenges that need to be solved to advance the idea.

Place, publisher, year, edition, pages
Larnaca, Cyprus: ACM Digital Library, 2019. p. 3-7
Keywords [en]
Choice architecture, Recommender systems, Persuasion
National Category
Human Computer Interaction
Research subject
human-computer interaction
Identifiers
URN: urn:nbn:se:umu:diva-158477DOI: 10.1145/3314183.3323451ISBN: 978-1-4503-6711-0 (print)OAI: oai:DiVA.org:umu-158477DiVA, id: diva2:1307601
Conference
UMAP 2019: The 27th ACM Conference on User Modelling, Adaptation and Personalization, Larnaca/Cyprus, June 9-12, 2019
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)Available from: 2019-04-28 Created: 2019-04-28 Last updated: 2019-07-17Bibliographically approved

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Kampik, TimotheusNajjar, Amro

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