Abstract
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 language | English |
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Title of host publication | CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems |
Subtitle of host publication | Engage with CHI |
Publisher | Association for Computing Machinery |
ISBN (Electronic) | 9781450356206, 9781450356213 |
DOIs | |
State | Published - 20 Apr 2018 |
Event | 2018 CHI Conference on Human Factors in Computing Systems, CHI 2018 - Montreal, Canada Duration: 21 Apr 2018 → 26 Apr 2018 |
Publication series
Name | Conference on Human Factors in Computing Systems - Proceedings |
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Volume | 2018-April |
Conference
Conference | 2018 CHI Conference on Human Factors in Computing Systems, CHI 2018 |
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Country/Territory | Canada |
City | Montreal |
Period | 21/04/18 → 26/04/18 |
Bibliographical note
Publisher Copyright:© 2018 Copyright is held by the owner/author(s).
Keywords
- Algorithms
- Big data
- Big data
- Design
- Emerging technologies
- Ethics
- Filter bubble
- Mental models
- Privacy
- Risk
- Technology harm
- User attitudes