THE RELEVANCE PEOPLE ASSIGN TO ALGORITHMIC-SELECTION APPLICATIONS IN EVERYDAY LIFE

  • Michael V. Reiss University of Zurich, Switzerland
  • Noemi Festic University of Zurich, Switzerland
  • Michael Latzer University of Zurich, Switzerland
  • Tanja Rüedy University of Zurich, Switzerland
Keywords: algorithmic selection, everyday life, subjective relevance, survey data

Abstract

The fast-growing academic and public attention to algorithmic-selection applications such as search engines and social media is indicative of their alleged great social relevance and impact on daily life in digital societies. To substantiate these claims, this paper investigates the hitherto little explored subjective relevance that Internet users assign to algorithmic-selection applications in everyday life. A representative online survey of Internet users comparatively reveals the relevance that users ascribe to algorithmic-selection applications and to their online and offline alternatives in five selected life domains: political and social orientation, entertainment, commercial transactions, socializing and health. The results show that people assign a relatively low relevance to algorithmic-selection applications compared to offline alternatives across the five life domains. In particular social media are found to be of relatively low assigned relevance for all life domains investigated. The findings vary greatly by age and education. Altogether, such outcomes complement and qualify assessments of the social impact of algorithms that are primarily and often solely based on usage data and theoretical considerations.

Published
2020-10-05
How to Cite
Reiss, M. V., Festic, N., Latzer, M., & Rüedy, T. (2020). THE RELEVANCE PEOPLE ASSIGN TO ALGORITHMIC-SELECTION APPLICATIONS IN EVERYDAY LIFE. AoIR Selected Papers of Internet Research, 2020. https://doi.org/10.5210/spir.v2020i0.11313
Section
Papers R