Are Cognitive Biases as Important as they Seem for Data Visualization?

TL;DR

The paper questions the field's heavy emphasis on cognitive biases in data visualization, arguing that this focus can understate human adaptive capabilities. By reviewing a decade of visualization literature and presenting a NASA-relevant scenario, it shows that heuristics can be ecologically rational and that decision-making in complex environments benefits from context-aware strategies. It advocates integrating naturalistic decision-making and adaptive-expertise perspectives to reframe biases as part of human problem-solving, not merely errors to be corrected. The work implications include designing visualization tools that support adaptive reasoning, hypothesis generation, and collaborative sense-making in real-world settings.

Abstract

Research on cognitive biases and heuristics has become increasingly popular in the visualization literature in recent years. Researchers have studied the effects of biases on visualization interpretation and subsequent decision-making. While this work is important, we contend that the view on biases has presented human cognitive abilities in an unbalanced manner, placing too much emphasis on the flaws and limitations of human decision-making, and potentially suggesting that it should not be trusted. Several decision researchers have argued that the flip side of biases -- i.e., mental shortcuts or heuristics -- demonstrate human ingenuity and serve as core markers of adaptive expertise. In this paper, we review the perspectives and sentiments of the visualization community on biases and describe literature arguing for more balanced views of biases and heuristics. We hope this paper will encourage visualization researchers to consider a fuller picture of human cognitive limitations and strategies for making decisions in complex environments.