Confirmation Bias in the Analysis of Remote Sensing Data

In practical application, analysis of remote sensing data requires a mix of technical analysis and best expert judgment. Unfortunately, a substantial experimental literature on judgment indicates that expert judgment is systematically flawed. In particular, experts are prone to a confirmation bias—where focus on a proposed hypothesis leads the expert to seek and overweigh confirming versus disconfirming evidence. In remote sensing, this predicts a tendency toward false positives in interpretation—concluding the evidence supports a hypothesis when it doesn't. In this paper, we empirically examine confirmation bias in technical data analysis, along with an approach to mitigating this bias that systematically promotes consideration of alternative causes in the analysis. Results suggest that analysts do exhibit confirmation bias in their technical analysis of remote sensing data; and furthermore that structured consideration of alternative causes mitigates this bias.