Analysis Of Competing Hypotheses
The Analysis of Competing Hypotheses (ACH) provides an unbiased methodology for evaluating multiple competing hypotheses for observed data. It was developed by Richards (Dick) J. Heuer, Jr., a 45-year veteran of the Central Intelligence Agency, in the 1970s for use by the Agency. ACH is used by analysts in various fields who make judgments that entail a high risk of error in reasoning. It helps an analyst overcome, or at least minimize, some of the cognitive limitations that make prescient intelligence analysis so difficult to achieve.
ACH was indeed a step forward in intelligence analysis methodology, but it was first described in relatively informal terms. Producing the best available information from uncertain data remains the goal of researchers, tool-builders, and analysts in industry, academia and government. Their domains include data mining, cognitive psychology and visualization, probability and statistics, etc. Abductive reasoning is an earlier concept with similarities to ACH.
Read more about Analysis Of Competing Hypotheses: Process, Strengths, Weaknesses, Automation
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