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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. ==Process== Heuer outlines the ACH process in considerable depth in his book, ''Psychology of Intelligence Analysis''.〔 It consists of the following steps: # Hypothesis – The first step of the process is to identify all potential hypotheses, preferably using a group of analysts with different perspectives to brainstorm the possibilities. The process discourages the analyst from choosing one "likely" hypothesis and using evidence to prove its accuracy. Cognitive bias is minimized when all possible hypotheses are considered.〔 # Evidence – The analyst then lists evidence and arguments (including assumptions and logical deductions) for and against each hypothesis.〔 # Diagnostics – Using a matrix, the analyst applies evidence against each hypothesis in an attempt to disprove as many theories as possible. Some evidence will have greater "diagnosticity" than other evidence — that is, some will be more helpful in judging the relative likelihood of alternative hypotheses. This step is the most important, according to Heuer. Instead of looking at one hypothesis and all the evidence ("working down" the matrix), the analyst is encouraged to consider one piece of evidence at a time, and examine it against all possible hypotheses ("working across" the matrix).〔 # Refinement – The analyst reviews the findings, identifies any gaps, and collects any additional evidence needed to refute as many of the remaining hypotheses as possible.〔 # Inconsistency – The analyst then seeks to draw tentative conclusions about the relative likelihood of each hypothesis. Less consistency implies a lower likelihood. The least consistent hypotheses are eliminated. While the matrix generates a definitive mathematical total for each hypothesis, the analyst must use their judgment to make the final conclusion. The result of the ACH analysis itself must not overrule analysts' own judgments. # Sensitivity – The analyst tests the conclusions using sensitivity analysis, which weighs how the conclusion would be affected if key evidence or arguments were wrong, misleading, or subject to different interpretations. The validity of key evidence and the consistency of important arguments are double-checked to assure the soundness of the conclusion's linchpins and drivers. # Conclusions and evaluation – Finally, the analyst provides the decisionmaker with his or her conclusions, as well as a summary of alternatives that were considered and why they were rejected. The analyst also identifies milestones in the process that can serve as indicators in future analyses.〔 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Analysis of competing hypotheses」の詳細全文を読む スポンサード リンク
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