CHS:III:Small:Designing Visual Representations to Mitigate Potential Cognitive Biases in Complex Decision-Making Processes

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People often assess complex information to make decisions. For example, reviewers assess student applications to make college admissions decisions. In such cases, people can be subject to reasoning biases that may lead to unfair or poor decisions. Visuals, such as charts and graphs, can be used to support such complex processes. They can also help in countering some of the possible biases. This research will study the potential biases and how to reduce their effects with visual representations. The findings can be applied to support and improve many complex decision-making applications, including the college admissions process.The primary goal of this research project is to identify and understand the potential cognitive biases in the holistic review process through ethnographic studies and to devise corresponding debiasing approaches using visualizations. This will be achieved through three primary research phases. The first phase will employ a cognitive task analysis and socio-organizational analysis to understand and characterize the holistic admissions process in terms of the data and tasks involved as well as the potential cognitive biases. In the second phase, the project team will explore the potential of visual representations for mitigating several of the candidate cognitive biases. Through systematic crowdsourced studies, the visual debiasing approaches will be evaluated and will result in a set of guidelines for integrating bias-mitigation strategies into visualization design. Finally, the third phase of the project will test the resulting guidelines in practice. The project team will design and develop a visual analysis tool for the holistic admissions process that integrates the effective visual bias-mitigating strategies. This tool will be evaluated through a three-month deployment study.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.