In his book, Thinking Fast and Slow, Daniel Kahneman has an interesting example of a heuristic bias. Read the description, then answer the question.
Steve is very shy and withdrawn, invariably helpful but with little interest in people or in the world of reality. A meek and tidy soul, he has a need for order and structure, and a passion for detail.
Is Steve more likely to be a librarian or a farmer?
I used this example in my critical thinking class the other night. About two-thirds of the students guessed that Steve is a librarian; one-third said he’s a farmer. As we debated Steve’s profession, the class focused exclusively on the information in the simple description.
Kahneman’s example illustrates two problems with the rules of thumb (heuristics) that are often associated with our System 1 thinking. The first is simply stereotyping. The description fits our widely held stereotype of male librarians. It’s easy to conclude that Steve fits the stereotype. Therefore, he must be a librarian.
The second problem is more subtle — what evidence do we use to draw a conclusion? In the class, no one asked for additional information. (This is partially because I encouraged them to reach a decision quickly. They did what their teacher asked them to do. Not always a good idea.) Rather they used the information that was available. This is often known as the availability bias — we make a decision based on the information that’s readily available to us. As it happens, male farmers in the United States outnumber male librarians by a ratio of about 20 to 1. If my students had asked about this, they might have concluded that Steve is probably a farmer — statistically at least.
The availability bias can get you into big trouble in business. To illustrate, I’ll draw on an example (somewhat paraphrased) from Paul Nutt’s book, Why Decisions Fail.
Peca Products is locked in a fierce competitive battle with its archrival, Frangro Enterprises. Peca has lost 4% market share over the past three quarters. Frangro has added 4% in the same period. A board member at Peca — a seasoned and respected business veteran — grows alarmed and concludes that Peca has a quality problem. She sends memos to the executive team saying, “We have to solve our quality problem and we have to do it now!” The executive team starts chasing down the quality issues.
The Peca Products executive team is falling into the availability trap. Because someone who is known to be smart and savvy and experienced says the company has a quality problem, the executives believe that the company has a quality problem. But what if it’s a customer service problem? Or a logistics problem? Peca’s executives may well be solving exactly the wrong problem. No one stopped to ask for additional information. Rather, they relied on the available information. After all, it came from a trusted source.
So, what to do? The first thing to remember in making any significant decision is to ask questions. It’s not enough to ask questions about the information you have. You also need to seek out additional information. Questioning also allows you to challenge a superior in a politically acceptable manner. Rather than saying “you’re wrong!” (and maybe getting fired), you can ask, “Why do you think that? What leads you to believe that we have a quality problem?” Proverbs says that “a gentle answer turneth away wrath”. So does an insightful question.
I disagree with your designer centric view Antoine. I have a long and successful background in different aspects of design and it took a large chunk of that time to realise that my point of view was not only limiting my success but the success of Design. While both creative and analytical thinkers remain in their separate silos, the world will suffer from either stifling sameness or clever uselessness. To bring forward well thought out solutions that solve real problems for real people requires maintaining the tension between very different approaches and valuing both contributions.
I decided on librarian here, but not for these reasons — I think the base rate fallacy about famers : librarians is a red herring, the important information is the neighbour. 90% of people live in urban areas.
If we accept this then the more important deduction is that the average librarian will have thousands of neighbours compared to the farmers hundreds. Average urban population density is 4251/mile2 (wikipedia). Average rural density is 87.
So if we devin 97% of neighbours live in cities. if we randomly chose our neighbour to ask about Steve then there is 97% chance that our neighbour will live in a city.
I didnt think about relative numbers of farmers to librarians. However, if we accept that there is an overwhelming chance that the neighbour lives in a city, then we have to consider what the incidence of population center dwelling farmers is to librarians. I suspect this is much lower than 20:1, it’s probably in the librarians favour