What's at stake: Characterizing risk perceptions of emerging technologies

Michaelwarren Skirpan, Tom Yeh, Casey Fiesler

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Scopus citations


One contributing factor to how people choose to use technology is their perceptions of associated risk. In order to explore this influence, we adapted a survey instrument from risk perception literature to assess mental models of users and technologists around risks of emerging, data-driven technologies (e.g., identity theft, personalized filter bubbles). We surveyed 175 individuals for comparative and individual assessments of risk, including characterizations using psychological factors. We report our observations around group differences (e.g., expert versus non-expert) in how people assess risk, and what factors may structure their conceptions of technological harm. Our findings suggest that technologists see these risks as posing a bigger threat to society than do non-experts. Moreover, across groups, participants did not see technological risks as voluntarily assumed. Differences in how people characterize risk have implications for the future of design, decision-making, and public communications, which we discuss through a lens we call risk-sensitive design.

Original languageEnglish
Title of host publicationCHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems
Subtitle of host publicationEngage with CHI
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450356206, 9781450356213
StatePublished - 20 Apr 2018
Event2018 CHI Conference on Human Factors in Computing Systems, CHI 2018 - Montreal, Canada
Duration: 21 Apr 201826 Apr 2018

Publication series

NameConference on Human Factors in Computing Systems - Proceedings


Conference2018 CHI Conference on Human Factors in Computing Systems, CHI 2018

Bibliographical note

Publisher Copyright:
© 2018 Copyright is held by the owner/author(s).


  • Algorithms
  • Big data
  • Big data
  • Design
  • Emerging technologies
  • Ethics
  • Filter bubble
  • Mental models
  • Privacy
  • Risk
  • Technology harm
  • User attitudes


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