Cognitive Biases in Visualizations

Description

This book brings together the latest research in this new and exciting area of visualization, looking at classifying and modelling cognitive biases, together with user studies which reveal their undesirable impact on human judgement, and demonstrating how visual analytic techniques can provide effective support for mitigating key biases. A comprehensive coverage of this very relevant topic is provided though this collection of extended papers from the successful DECISIVe workshop at IEEE VIS, together with an introduction to cognitive biases and an invited chapter from a leading expert in intelligence analysis. Cognitive Biases in Visualizations will be of interest to a wide audience from those studying cognitive biases to visualization designers and practitioners. It offers a choice of research frameworks, help with the design of user studies, and proposals for the effective measurement of biases. The impact of human visualization literacy, competence and human cognition on cognitive biases are also examined, as well as the notion of system-induced biases. The well referenced chapters provide an excellent starting point for gaining an awareness of the detrimental effect that some cognitive biases can have on users’ decision-making. Human behavior is complex and we are only just starting to unravel the processes involved and investigate ways in which the computer can assist, however the final section supports the prospect that visual analytics, in particular, can counter some of the more common cognitive errors, which have been proven to be so costly. Front Matter ....Pages i-xii So, What Are Cognitive Biases? (Geoffrey Ellis)....Pages 1-10 Front Matter ....Pages 11-11 Studying Biases in Visualization Research: Framework and Methods (André Calero Valdez, Martina Ziefle, Michael Sedlmair)....Pages 13-27 Four Perspectives on Human Bias in Visual Analytics (Emily Wall, Leslie M. Blaha, Celeste Lyn Paul, Kristin Cook, Alex Endert)....Pages 29-42 Bias by Default? (Joseph A. Cottam, Leslie M. Blaha)....Pages 43-58 Front Matter ....Pages 59-59 Methods for Discovering Cognitive Biases in a Visual Analytics Environment (Michael A. Bedek, Alexander Nussbaumer, Luca Huszar, Dietrich Albert)....Pages 61-73 Experts’ Familiarity Versus Optimality of Visualization Design: How Familiarity Affects Perceived and Objective Task Performance (Aritra Dasgupta)....Pages 75-86 Data Visualization Literacy and Visualization Biases: Cases for Merging Parallel Threads (Hamid Mansoor, Lane Harrison)....Pages 87-96 The Biases of Thinking Fast and Thinking Slow (Dirk Streeb, Min Chen, Daniel A. Keim)....Pages 97-107 Front Matter ....Pages 109-109 Experimentally Evaluating Bias-Reducing Visual Analytics Techniques in Intelligence Analysis (Donald R. Kretz)....Pages 111-135 Promoting Representational Fluency for Cognitive Bias Mitigation in Information Visualization (Paul Parsons)....Pages 137-147 Designing Breadth-Oriented Data Exploration for Mitigating Cognitive Biases (Po-Ming Law, Rahul C. Basole)....Pages 149-159 A Visualization Approach to Addressing Reviewer Bias in Holistic College Admissions (Poorna Talkad Sukumar, Ronald Metoyer)....Pages 161-175 Cognitive Biases in Visual Analytics—A Critical Reflection (Margit Pohl)....Pages 177-184