How should ai systems talk to users when collecting their personal information? efects of role framing and self-referencing on human-ai interaction

Mengqi Liao, S. Shyam Sundar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

AI systems collect our personal information in order to provide personalized services, raising privacy concerns and making users leery. As a result, systems have begun emphasizing overt over covert collection of information by directly asking users. This poses an important question for ethical interaction design, which is dedicated to improving user experience while promoting informed decision-making: Should the interface tout the benefts of information disclosure and frame itself as a help-provider? Or, should it appear as a help-seeker? We decided to fnd out by creating a mockup of a news recommendation system called Mindz and conducting an online user study (N=293) with the following four variations: AI system as help seeker vs. help provider vs. both vs. neither. Data showed that even though all participants received the same recommendations, power users tended to trust a help-seeking Mindz more whereas non-power users favored one that is both help-seeker and help-provider.

Original languageEnglish (US)
Title of host publicationCHI 2021 - Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Subtitle of host publicationMaking Waves, Combining Strengths
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450380966
DOIs
StatePublished - May 6 2021
Event2021 CHI Conference on Human Factors in Computing Systems: Making Waves, Combining Strengths, CHI 2021 - Virtual, Online, Japan
Duration: May 8 2021May 13 2021

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2021 CHI Conference on Human Factors in Computing Systems: Making Waves, Combining Strengths, CHI 2021
Country/TerritoryJapan
CityVirtual, Online
Period5/8/215/13/21

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design
  • Software

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