Textbook in PDF format

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
So, What Are Cognitive Biases?
Front Matter
Studying Biases in Visualization Research: Framework and Methods
Four Perspectives on Human Bias in Visual Analytics
Bias by Default?
Front Matter
Methods for Discovering Cognitive Biases in a Visual Analytics Environment
Experts’ Familiarity Versus Optimality of Visualization Design: How Familiarity Affects Perceived and Objective Task Performance
Data Visualization Literacy and Visualization Biases: Cases for Merging Parallel Threads
The Biases of Thinking Fast and Thinking Slow
Front Matter
Experimentally Evaluating Bias-Reducing Visual Analytics Techniques in Intelligence Analysis
Promoting Representational Fluency for Cognitive Bias Mitigation in Information Visualization
Designing Breadth-Oriented Data Exploration for Mitigating Cognitive Biases
A Visualization Approach to Addressing Reviewer Bias in Holistic College Admissions
Cognitive Biases in Visual Analytics—A Critical Reflection