Method for Appropriating the Brief Implicit Association Test to Elicit Biases in Users

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 classifcations. 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 ft of crowdsourced test construction. Our method allows researchers of diferent 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.

• Human-centered computing → Human computer interaction (HCI); HCI design and evaluation methods; Empirical studies in HCI .