Abstract
Implicit tendencies and cognitive biases play an important role in how information is perceived and processed, a fact that can be both utilised and exploited by computing systems. The Implicit Association Test (IAT) has been widely used to assess people's associations of target concepts with qualitative attributes, such as the likelihood of being hired or convicted depending on race, gender, or age. The condensed version-the Brief IAT-aims to implicit biases by measuring the reaction time to concept classifications. To use this measure in HCI research, however, we need a way to construct and validate target concepts, which tend to quickly evolve and depend on geographical and cultural interpretations. In this paper, we introduce and evaluate a new method to appropriate the BIAT using crowdsourcing to measure people's leanings on polarising topics. We present a web-based tool to test participants' bias on custom themes, where self-assessments often fail. We validated our approach with 14 domain experts and assessed the fit of crowdsourced test construction. Our method allows researchers of different domains to create and validate bias tests that can be geographically tailored and updated over time. We discuss how our method can be applied to surface implicit user biases and run studies where cognitive biases may impede reliable results.
Original language | English |
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Title of host publication | CHI 2022 - Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems |
Publisher | Association for Computing Machinery |
Publication date | 29 Apr 2022 |
Article number | 243 |
ISBN (Electronic) | 9781450391573 |
DOIs | |
Publication status | Published - 29 Apr 2022 |
Event | 2022 CHI Conference on Human Factors in Computing Systems, CHI 2022 - Virtual, Online, United States Duration: 30 Apr 2022 → 5 May 2022 |
Conference
Conference | 2022 CHI Conference on Human Factors in Computing Systems, CHI 2022 |
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Country/Territory | United States |
City | Virtual, Online |
Period | 30/04/2022 → 05/05/2022 |
Sponsor | ACM SIGCHI |
Series | Conference on Human Factors in Computing Systems - Proceedings |
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Bibliographical note
Publisher Copyright:© 2022 ACM.
Keywords
- Attitude-Aware Systems
- Brief Implicit Association Test
- Cognitive Biases