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Cognitive Bias in Intelligence Analysis
Martha Whitesmith
其他書名
Testing the Analysis of Competing Hypotheses Method
出版
Edinburgh University Press
, 2020-09-21
主題
Political Science / History & Theory
Political Science / Security (National & International)
Political Science / Intelligence & Espionage
Psychology / Cognitive Psychology & Cognition
ISBN
1474466362
9781474466363
URL
http://books.google.com.hk/books?id=AaUxEAAAQBAJ&hl=&source=gbs_api
EBook
SAMPLE
註釋
Tests whether the analysis of competing hypotheses reduces cognitive bias, and proposes a more effective approachReveals that a key element of current training provided to the UK and US intelligence communities (and likely all 5-EYES and several European agencies) does not have a proven ability to mitigate cognitive biasesDemonstrates that judging the credibility of information from human sources means that intelligence analysis faces greater complexity and cognitive strain than non-intelligence analysisExplains the underlying causes cognitive biases, based on meta-analyses of existing researchShows that identifying the ideal conditions for intelligence analysis is a more effective way of reducing the risk of cognitive bias than the use of ACHRecent high-profile intelligence failures - from 9/11 to the 2003 Iraq war - prove that cognitive bias in intelligence analysis can have catastrophic consequences. This book critiques the reliance of Western intelligence agencies on the use of a method for intelligence analysis developed by the CIA in the 1990s, the Analysis of Competing Hypotheses (ACH). The author puts ACH to the test in an experimental setting against two key cognitive biases with unique empirical research facilitated by UK's Professional Heads of Intelligence Analysis unit at the Cabinet Office, and finds that the theoretical basis of the ACH method is significantly flawed. Combining the insight of a practitioner with over 11 years of experience in intelligence with both philosophical theory and experimental research, the author proposes an alternative approach to mitigating cognitive bias that focuses on creating the optimum environment for analysis, challenging current leading theories.