Confirmation Bias in the
Analysis of Remote Sensing Data
June 2007
Paul E. Lehner, The MITRE Corporation
Leonard Adelman, The MITRE Corporation
Robert J. DiStasio, Jr., The MITRE Corporation
Marie C. Erie, The MITRE Corporation
Janet S. Mittel, The MITRE Corporation
Sherry L. Olson, The MITRE Corporation
ABSTRACT
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.
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