Modeling and critiquing the confirmation bias in human reasoning

Barry G. Silverman

31 citations0/0 files storedIEEE Transactions on Systems Man and Cybernetics

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Decision-Making and Behavioral Economics AI-based Problem Solving and Planning Clinical Reasoning and Diagnostic Skills

Abstract

In trying to solve even small problems, humans often form wrong hypotheses by looking only at the most salient factors and by ignoring contrary evidence. Once they form their initial beliefs, they exhibit a strong tendency to seek only additional confirming evidence. This type of behavior is the confirmation bias. Empirical evidence is presented suggesting that computers can interact with humans by qualitatively modeling and detecting their confirmation bias and by offering criticism strategies that will effectively mitigate the unwanted effects. The degree of improvement is sensitive to the strategy and content of the critic. A number of strategies are constructed and evaluated, and it is shown which ones are most likely to lead to success for varying circumstances and user types. Additional fruitful research directions are pinpointed.>

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References

1959The Logic of Scientific Discovery 1960On the Failure to Eliminate Hypotheses in a Conceptual Task 1987Confirmation, disconfirmation, and information in hypothesis testing.1990Bias in Human Reasoning: Causes and Consequences 1977Confirmation Bias in a Simulated Research Environment: An Experimental Study of Scientific Inference 1985Rationality and Intelligence 1987Rationality and Intelligence 1980Strategies of Rule Discovery in an Inference Task

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