People crowd outside at a restaurant as restrictions on coronavirus disease (COVID-19) are relaxed in Ann Arbor, Michigan, United States, April 4, 2021.
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A new book by Nobel Laureate in Economics Daniel Kahneman asks why everyone makes such bad decisions and what can we do about them?
Why do we all make such bad decisions? Not just for investing, about everything.
Imagine two doctors giving two different diagnoses to identical patients, or two judges giving completely different sentences to people of the same background who have committed the same crime. Or two economic forecasters, faced with the same economic data, who make very different projections of US GDP.
Or, worse yet, a doctor or judge who might give a different diagnosis or judgment based on the time of day, or even what they ate.
Why is this happening? Is there a way to make better decisions? Can we make the decision making more logical? Can we remove some of the emotion that clouds our ability to make the right decisions?
More importantly, can we find a way to consistently make better judgments?
This is the subject of “Noise”, the new book by Kahneman and his colleagues, Oliver Sibony and Cass R. Sunstein. Kahneman is one of the founding fathers of behavioral economics and author of the seminal book, “Thinking Fast and Slow. “
Kahneman and his colleagues define “noise” as “the variability of judgments that should be the same” and he leaves no doubt how he feels about it: “There are too many”.
This “variability” comes from the fact that judgments are subjective and do not follow exact rules.
This “noise” is omnipresent in our lives. Medicine, law, economic forecasting, food safety, auto repair, it doesn’t matter. It is there, wherever people have to make judgments or decisions.
There is a difference between bias and noise. If you step on a scale and the scale overestimates your actual weight by two pounds each day, that’s a bias.
If you get on a scale and one day he overestimates your weight by two pounds, and the next day underestimates by one pound, and the next day overestimates by three pounds, that’s noise. (In case you were wondering, Kahneman states that “most inexpensive bathroom scales are somewhat biased and quite loud.”)
The study of bias is well developed. Kahneman himself has made many important contributions in this area.
Perhaps the most common bias is professional overconfidence, which Kahneman called “the most important of” cognitive biases “in” Thinking Fast and Slow. ” .
Many other biases have been identified, including confirmation bias (using information that matches existing beliefs while ignoring information that does not match those beliefs) and loss aversion (a potential loss is perceived as more serious than an equivalent potential gain, a condition well known to equity investors).
The bias, in other words, is easy to see and describe. Noise is harder to see but no less damaging.
The good news is that there is something we can do about it.
Most people think highly of their opinions. It makes life interesting, but it is a real problem when it comes to judgments that affect the lives, health and money of others, as judges, doctors, auto mechanics and financial advisers do not. generally do not understand how biased and noisy their judgments are.
For this reason, Kahneman strives to develop a more rules-based approach to decision-making.
He is aware that rules and algorithms can have their own biases, but believes that if properly constructed they are superior to human judgment: “Most people are surprised to learn that the accuracy of their predictive judgments is not only weak but inferior to that of the 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. “
To inform organizations of the potential amount of noise, Kahneman suggests a noise audit.
What is that? It is a way of measuring the noise there is in systems, which can range from a radiology department to an insurance agency to a financial services company.
For example, if members of a radiology team provide a very different analysis of the same x-ray of the same patient, it is a noise problem.
Kahneman describes a protocol for an acoustic audit that involves studying how a group of experts in a company (he suggests a minimum of twelve participants) reacts to two or three realistic case studies on an individual basis. Each member should summarize the case and judgment either numerically (in dollars, percentiles or probabilities) or on some scale with at least five degrees (such as “very strong”, “strong”, “average”, “poor”, ” or “very poor.”) They would not be allowed to communicate with each other.
The executives who assemble the case study are interviewed beforehand to assess how well they expect their experts to agree on a given case and what level of disagreement would be acceptable.
If the results deviate significantly from expectations, there is a noise problem.
Kahneman calls his main suggestion for reducing noise “decision-making hygiene,” a commitment to certainly follow clear procedures to reduce noise and bias.
Some principles of decision-making hygiene include:
- The goal of judgment is accuracy and not individual expression. Kahneman calls this “the first principle of decision-making hygiene”. Individual differences “cause different people to form different views on the same problem. This observation leads to a conclusion that will be as unpopular as it is compelling: judgment is not the place to express your individuality.” Can we replace human judgment with rules or algorithms? Kahneman says that while eliminating human judgment entirely is undesirable, the use of algorithms can improve judgments by making them less dependent on what he calls “the particulars of a professional.”
- Resist premature intuition. Professionals make very quick decisions on the basis of past experience, which is a major source of bias and noise. “Intuition doesn’t need to be forbidden, but it needs to be informed, disciplined and delayed,” Kahneman says.
- Obtain independent judgments from multiple judges, then consider consolidating those judgments. This is another well-studied bias: a group, for example, of financial analysts who have an opinion on the direction of the stock market will often change their mind after being exposed to a group expressing different opinions. Taking a large independent sample, whether it’s assessing an x-ray, an engine problem, or the future stock price, will improve the accuracy of the estimates.
Why is the future so difficult to predict? It has been well documented that the success rate of “experts” in predicting the future is terrible, from stock selection to elections to social trends.
First, Kahneman notes that people who try to predict the future have the same biases and noise as everyone else, which limits the quality of their predictions.
Second, Kahneman says that much of the future is inherently unknowable, and the further we go, the harder it becomes.
This is unknowable for two reasons: because we do not have complete information and because events occur which are unpredictable and may affect the results.
We do not have complete information on companies, the economy or individuals. Events can and do happen for businesses, CEOs, individuals, which are completely unpredictable and affect the quality and performance of the business, the individual and the decisions of individuals.
This should make prognosticators of political elections, of the stock market, of the future in general very humble: “None of these events and circumstances can be predicted today – neither by you, nor by anyone else, nor by by the best predictive model in the world ”, writes Kahneman.
Knowing this, a rational person might wonder why it is worth bothering.
The answer is that studying bias and noise is not just an academic exercise. Kahneman makes it clear that noise is at the heart of current debates about justice and fairness: “It is unfair that people in a similar situation are treated differently, and a system in which professional judgments are seen as inconsistent loses its value. credibility.”
Kahneman is referring here to forensic decision-making, but the lessons apply to anyone trying to give advice to people about the future, whether it’s an x-ray diagnosis, giving chances on a political race or a financial adviser who chooses stocks for clients.
Despite the imperfect nature of humans and the unknowability of the future, we are not helpless. We can improve our decision-making skills.
The battle against noise and prejudice, and the battle with the future in general, therefore comes down to a battle for credibility.