The Biases of Thinking Fast and Thinking Slow

Abstract

Visualization is a human-centric process, which is inevitably as- sociated with potential biases in humans’ judgment and decision making. While the discussions on humans’ biases have been heavily influenced the work of Daniel Kahneman as summarized in his book “Thinking, Fast and Slow” [8], there have also been viewpoints in psychology in favor of heuristics (e.g., [6]). In this paper, we present a balanced discourse on the humans’ heuristics and biases as the two sides of the same coin. In particular, we examine these two aspects from a probabilistic perspective, and relate them to the notions of global and local sampling. We use three case studies in Kahneman’s book to illustrate the potential biases of human- and machine-centric decision processes. Our discourse leads to a concrete conclusion that visual analytics, where interactive visualization is integrated with statistics and algorithms, offers an effective and efficient means to overcome biases in data intelligence.