Published May 17, 2021

Our Noisy Minds

Daniel Kahneman delves into the concept of 'noise' and its detrimental effects on judgment and decision-making, advocating for decision hygiene and the adoption of algorithms to enhance accuracy and reduce bias across various fields.
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  • Decision Hygiene

    Decision hygiene is a concept introduced by to systematically reduce bias and noise in judgments. He compares it to public health measures like handwashing, which target a broad range of germs without knowing which specific ones are being eliminated 1. This approach involves creating procedures that improve judgment quality across various decisions, whether in organizations or individual contexts. suggests that identifying tasks carried out by interchangeable roles, like underwriters or physicians, and measuring noise in their judgments can help reduce variability 1.

       

    System Noise

    System noise refers to the variability in judgments within large organizations, where decisions should be predictable but often are not. highlights this issue with examples like asylum cases, where judges' decisions vary drastically despite similar circumstances 2. This unpredictability is not limited to external comparisons; even individual judgments can be inconsistent over time, as seen with radiologists and fingerprint examiners 2. notes that noise audits can help distinguish between noise and bias, revealing the extent of variability in professional judgments 3.

       

    Power of Averaging

    Averaging independent judgments is a powerful method to reduce noise, as demonstrated by the historical example of estimating an ox's weight at a county fair. explains that averaging multiple independent judgments eliminates noise because errors tend to cancel each other out 4. This method, however, does not necessarily reduce bias, as biases shared by judges will persist in the average 4. emphasizes that while averaging can significantly reduce noise, it must be applied carefully to ensure it addresses the same judgments or objects 5.

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