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Intelligence Squared

Daniel Kahneman on Making Intelligent Decisions in a Chaotic World - Part 1

Jul 11, 2023
34:20

Podcast summary created with Snipd AI

Quick takeaways

  • Noise and bias both contribute to inaccurate judgments, but noise is often more prevalent and harder to detect.
  • Organizations should encourage independent judgments and consider algorithms to reduce noise and address biases effectively.

Deep dives

What is noise and how is it different from bias?

Noise refers to the variability in judgments that should be identical. It exists when people make judgments about the same subject, but the judgments turn out to be different. In contrast, bias refers to consistent average errors in judgment. While bias represents systematic mistakes, noise represents the variability of judgments. Both bias and noise contribute to the inaccuracy of judgments, but noise is often more prevalent and harder to detect.

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