Book: Noise: A Flaw in Human Judgment

Author

Daniel Kahneman, Olivier Sibony, Cass R. Sunstein

Summary

A summary of decision hygiene practices to reduce noise in judgments.

Takeaways

Noise is ubiquitous in situations that require judgment and leads to unwanted and costly variability and unfairness in decisions. The reasons for noise in judgments are manifold. People have cognitive biases and a natural preference for causal thinking that finds comfort in finding coherent explanations even if the reality is more complex and less predictable.

Adherence to decision hygiene principles reduces noise. The goal of the principles is to delay premature intuition and to limit the influence of cognitive biases. For example, averaging independent judgments, or relying on formulas and simple models that are noise free allows for consistent judgment in situations that are similar to each other.

Quotes

“In summary, what people usually claim to strive for in verifiable judgments is a prediction that matches the outcome. What they are effectively trying to achieve, regardless of verifiability, is the internal signal of completion provided by the coherence between the facts of the case and the judgment. And what they should be trying to achieve, normatively speaking, is the judgment process that would produce the best judgment over an ensemble of similar cases."

“The illusion of validity is found wherever predictive judgments are made, because of a common failure to distinguish between two stages of the prediction task: evaluating cases on the evidence available and predicting actual outcomes. You can often be quite confident in your assessment of which of two candidates looks better, but guessing which of them will actually be better is an altogether different kettle of fish."

“Causal thinking helps us make sense of a world that is far less predictable than we think. It also explains why we view the world as far more predictable than it really is. In the valley of the normal, there are no surprises and no inconsistencies. The future seems as predictable as the past. And noise is neither heard nor seen."

“Most people are surprised to hear that the accuracy of their predictive judgments is not only low but also inferior to that of formulas. Even simple linear models built on limited data, or simple rules that can be sketched on the back of an envelope, consistently outperform human judges. The critical advantage of rules and models is that they are noise-free. As we subjectively experience it, judgment is a subtle and complex process; we have no indication that the subtlety may be mostly noise. It is difficult for us to imagine that mindless adherence to simple rules will often achieve higher accuracy than we can—but this is by now a well-established fact."