Claire Textor

Papers

Total Citations

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About

Claire Textor investigates the cognitive mechanisms that determine whether humans successfully trust and interact with automation. Her work bridges human-automation interaction (HAI) and attention control, challenging mixed findings in working memory research by focusing instead on how attentional resources shape trust decisions. In her highly cited paper “Paying Attention to Trust: Exploring the Relationship Between Attention Control and Trust in Automation” (2021), she demonstrates that individual differences in attention control—not just memory capacity—explain why some human-automation interactions succeed while others fail. This contribution reframes the debate in HAI, offering a more precise cognitive predictor of trust calibration. Her research has important implications for designing safer autonomous systems, from self-driving cars to AI decision-support tools. With her work gaining traction among cognitive scientists and human factors engineers, Textor is establishing herself as a key voice in understanding the cognitive architecture underlying human trust in increasingly autonomous technologies.