Julian Sanchez suggests that research on information cascades may provide insight into recent intelligence failures:
There may be a special problem with "accountability" in intelligence work: If you're wrong when the majority gets it wrong, you're unlikely to get singled out, but if you dissent from an accurate consensus, the mistake is much more likely to get noticed. One way to break cascades, then, is to leave analysts feeling free to draw conclusions that run against the grain on the basis of the specific information they're studying, even if it seems to them that on balance their info is an aberration. Another is to share raw data, yes, and independent conclusions based on that data at the end of the process, but to insulate analysts from the previous conclusions of their peers while they're deciding how to interpret new pieces of intelligence.
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