Noise: A Flaw in Human Judgment by noted authors Daniel Kahneman, Olivier Sibony, and Cass Sunstein. Noise is simply random, unpredictable decision making that cannot be explained. At the same time, is not accountable. This is very perplexing today.
At the same time, this is not easy to fully understand. Here is a good outline provided by the book:
Imagine that two doctors in the same city give different diagnoses to identical patients — or that two judges in the same courthouse give different sentences to people who have committed the same crime.
Suppose that different food inspectors give different ratings to indistinguishable restaurants — or that when a company is handling customer complaints, the resolution depends on who happens to be handling the particular complaint.
Now imagine that the same doctor, the same judge, the same inspector, or the same company official makes different decisions, depending on whether it is morning or afternoon, or Monday rather than Wednesday. These are examples of noise: variability in judgments that should be identical.
As a result, it is amazing to understand how and why people from all walks of life make really bad judgements. The fact that it can be quantified and even controlled offers us hope. However, based upon our crazy world today it only offers hope.
How many times have you found yourself impacted by Noise?
Sections that certainly stick most with organizations is within their hiring process. The authors really hit a home run here. Based upon their research and insights, this is worth the price of admission alone. Issues like prejudice are actually bias. When assessing decisions that go wrong, noise is the standard deviation of errors, while bias is the mean itself.
The role of bias?
Bias is a significant contributor to noise. However the authors go to great lengths to separate the two. We are well aware of bias (loss aversion, status quo, overconfidence, excessive discounting, etc.) and at the same time holds a much larger weight compared to bias.
The collaboration between Daniel, Cass, and Olivier certainly reveals their research in psychology and behavioral science will take time to fully digest and layout across society. Therefore, we are left to understand the amazing variety of errors across all fields and markets: medicine, law, economic forecasting, police behavior, food safety, bail, security checks at airports, strategy, and personnel selection.
Daniel addresses how bias is certainly bakes into algorithms, as referenced to the book Weapons of Math Destruction:
The potentially high costs of noise reduction often come up in the context of algorithms, where there are growing objections to “algorithmic bias.” As we have seen, algorithms eliminate noise and often seem appealing for that reason. Indeed, much of this book might be taken as an argument for greater reliance on algorithms, simply because they are noiseless. But as we have also seen, noise reduction can come at an intolerable cost if greater reliance on algorithms increases discrimination on the basis of race and gender, or against members of disadvantaged groups.
pp. 481-482.
Dealing with flaws in human judgement
While the overwhelming ways human judgment can be clouded is mind-boggling, race is not addressed as any aspect of Noise. A bit disappointing when you consider the documented history within Richard Rothstein’s powerful book The Color of Law.
I first read Daniel’s bestseller Thinking, Fast and Slow in 2015. So many of my books have this book’s citation that I have re-read select chapters. Yes, his revelations regarding system one thinking (fast) and system two (slow) has proven very insightful.
In conclusion, there are few books with such insights that you want to read the book twice. This is certainly one you will want to re-read. Noise joins a small list of books to read a second time to solidify the initial lessons and dig deeper for additional insights.
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