Feedback loops and mutual reinforcement in personalized interaction

Eelco Herder*, Claus Atzenbeck

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

Abstract

In personalized interaction between humans and computers, not only computers and personalization algorithms learn about the users: the users also learn about the system's behavior and adapt their expectations accordingly. Particularly, as users expect systems to support their daily activities, this feedback loop may result in long-term changes in these daily activities and user decisions themselves. This can be observed in activities as different as autonomous driving and social media consumption. In this chapter, we investigate these effects by reviewing and analyzing a wide range of relevant literature.

Original languageEnglish
Title of host publicationPersonalized Human-Computer Interaction
PublisherDe Gruyter
Pages153-171
Number of pages19
ISBN (Electronic)9783110988567
ISBN (Print)9783110999600
DOIs
Publication statusPublished - 7 Aug 2023

Keywords

  • Bounded rationality
  • Choice
  • Cognitive friction
  • Mutual reinforcement
  • Personalization

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