How Come Smart People Can Make Stupid Decisions?

After more than 100 years of research a majority of psychologists has agreed upon a definition of measurable intelligence (IQ) that can be described:

as the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly and learn from experience. It is not merely book learning, narrow academic skill, or test-taking smarts. Rather it reflects a broader and deeper capability for comprehending our surroundings – “catching on,” “making sense” of things, or “figuring out” what to do.

Given such a definition of IQ we should expect that people with high IQ (measurable intelligence) to show superior judgment and decision making in their lives. Actually there is quite a lot of scientific evidence in favor of this expectation – this stuff called IQ is a reasonably good predictor of grades at school, performance at work, and many other aspects of success in life. Nevertheless, I would bet that all of you have met people during your life and/or professional career about whom you have posed observations such as these: Such a smart person, how is it possible that he/she has made such a silly decision? I know that he/she is really very clever and that he/she had all the necessary information to make good decision, so how it is possible that he/she has decided so stupidly? In other words, Why is that smart people sometimes do dumb things?

Keith Stanovich, a cognitive psychologist who studies how people reason, has offered an interesting answer to this important question. According to him, the psychological construct of IQ does not cover the entire terrain of cognitive abilities that enable us to efficiently adapt to our environment. Based on heuristics and biases research program, that has discovered many systematic flaws and biases in our judgments and decisions, he has identified an entirely new area of cognitive functioning that only weakly–moderately correlates with IQ, and thus can explain why smart people (with high IQ) can act stupidly. He talks about good old-fashioned rationality defined as taking the appropriate action given one’s goals and beliefs (instrumental rationality), and holding beliefs that are commensurate with available evidence (epistemic rationality). According to his model, in order to make sound judgments and decisions we need not only sufficiently high IQ (because IQ still predicts to some degree the adaptivity of our judgments and decisions, especially in situations when we know that we should do our best), but also two other crucial qualities: The first quality is the propensity to overcome our natural cognitive laziness – when we can get away with it, we do not think and instead of slow and effortful thinking we rely on faster, more automatic, but unfortunately also less accurate cognitive mechanisms.

As Henry Ford put it: “Thinking is the hardest work there is, which is the probable reason why so few people engage in it.”

The second quality rests on the possession of a special kind of “mindware” that consists of the basic principles of logic, probability theory, scientific thinking and other cognitive strategies, procedures and structures that taken together enable us to think and act rationally. In both of these qualities people differ among themselves in a similar way as they differ in their IQ. Unfortunately there is not any well-established tool on the psychometric market measuring this “new/old” construct, but the good news is that Keith Stanovich together with his team is working on it. To get a glimpse of tasks that tap the above mentioned aspects of rationality you can try to solve four teasers below (correct/rational answers are listed at the end of the article).

Test Yourself!

1. Jack is looking at Anne, but Anne is looking at George. Jack is married, but George is not. Is a married person looking at an unmarried person?

A) Yes, B) No, C) Cannot be determined

2. A bat and a ball cost $1.10 in total. The bat costs $1 more than the ball. How much does the ball cost?$ ___

. An experiment is conducted to test the efficacy of a new sales training course: 200 salesmen attended the course and improved their sales; 75 attended the course and did not improve their sales; 50 did not attend the course and improved their sales; and 15 did not attend the course and did not improve their sales. The 2 x 2 matrix below summarizes the results. Was the sales training effective? ___ [Yes/No]

Improvement No improvement
Training 200 75
No training 50 15

4. The probability of breast cancer is 1% for a woman at age forty who participates in routine screening. If a woman has breast cancer, the probability is 80% that she will have a positive mammogram. If a woman does not have breast cancer, the probability is 9.69% that she will also have a positive mammogram. If a woman in this age group has a positive mammogram in a routine screening, what is the probability that she actually has breast cancer? ___%

Why should we, professionals in the HR industry, be interested in Stanovich’s research? The simple answer is that large part of our business is about predicting the future. Thanks to 100 years of personnel selection research we now have a set of valid and reliable tools for predicting future job performance. Despite the fact that predictive power of the tools that are at our disposal is not bad (compare for example: 0.51 correlation between intelligence and job performance in moderately complex positions with 0.08 correlation between coronary bypass surgery and survival rate; 0.08 correlation between smoking and lung cancer within 25 years; 0.11 correlation between taking antihistamines and reduction of phlegm; 0.14 correlation between Ibuprofen consumption and pain reduction or 0.38 correlation between the administration of Viagra and improved sexual function), things always can be better. By adding a new tool with incremental validity to our portfolio of measures we can make our predictions even more precise and useful.

Luděk Stehlík
ASI R&D Manager

Correct answers

1. A) Yes
2. $0.05
3. No, the sales training was not effective.
4. 7.8%

Tasks 1 and 2 measure cognitive laziness – processing aspect of rationality; tasks 3 and 4 measure how proficient one is at application of scientific and probabilistic thinking principles that are part of the “rationality mindware” – knowledge aspect of rationality.

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