The Rational Animal: How Evolution Made Us Smarter Than We Think (17 page)

Why is learning to talk easy while learning to write is difficult?
The answer lies in our evolutionary history.
Our ancestors have been talking for hundreds of thousands of years.
The ability to talk gave such an advantage that humans across the world have been naturally selected for being good talkers.
Talking is like walking.
We don’t need to sign up for a walking class—we just do it.
But writing is very different.
The written word is the new evolutionary kid on the block.
From the perspective of our 2-million-year hominid lifespan, we have been writing for only a brief time.
And most of the writing in the last few thousand
years has been done by a tiny number of select individuals.
Even in the modern world, the majority of people are still illiterate—they speak but don’t read or write.
Whereas talking is like walking, writing is like doing ballet.
If you buy your child a pair of ballet slippers, it’s highly unlikely she will spontaneously start doing triple pirouettes.
You’d be fortunate if the kid merely starts hopping clumsily up in the air without hitting her head on the floor.
If you want anything even vaguely resembling
Swan Lake
, better sign her up for a few years of ballet classes.

Many things in life are like talking—evolutionarily old and easy.
We don’t have to try hard to learn how to see, breathe, eat, or run.
But many other things in the modern world are like writing—evolutionarily novel and difficult.
This includes most of the skills we need to read, write, play the violin, perform brain surgery, and do rocket science.
And when it comes to making decision errors, many of them stem from something we’ve all spent over a dozen years and thousands of hours desperately trying to learn: math.

WHY CAN’T JOHNNY DO THE MATH?

Imagine you are a woman at your gynecologist’s office.
Your doctor suggests a mammogram to screen for breast cancer, and your worst fear comes true: it comes back positive.
But you’ve heard that these kinds of tests aren’t always right, so you ask your doctor, “Does this really mean I have breast cancer?
What’s the likelihood?”

It would certainly make a huge difference if your chances of having cancer are 1 percent or 90 percent.
And many people assume that every physician knows the precise answer.
But we shouldn’t be so sure.
In a recent study, 160 respected doctors were provided with the relevant statistical information needed to calculate the chances that a woman with a positive test actually has the disease.
Here is everything you need to know:

•
The probability that a woman has breast cancer is 1 percent.

•If a woman has breast cancer, the probability that she will test positive is 90 percent.

•If a woman does not have breast cancer, the probability that she will nevertheless test positive is 9 percent.

If a woman tests positive, what are the chances that she has breast cancer?

The correct answer is roughly 10 percent.
Given the odds above, if a woman tests positive, there is about a 10 percent chance that she actually has breast cancer.
(If you do the math, you’ll see that nine out of one hundred women who don’t have breast cancer will be false positives, and a little less than one in one hundred will be a true positive.
So just about one in ten who test positive, or 10 percent, actually has breast cancer.)

But of the doctors who were asked this question, only 21 percent got it right.
This should already be pretty disturbing, but the situation is much more disconcerting than that.
For starters, these doctors were all gynecologists.
These are the people who actually do mammography screening!
The doctors could have simply recalled what they should already know about false positives, but that didn’t happen.
Even more troubling is the range of responses.
Almost half of the doctors said the likelihood of having breast cancer was 90 percent!
And one in five doctors said the likelihood was only 1 percent!
But here is the final kicker.
The question was multiple choice—there were only four options (90 percent, 81 percent, 10 percent, and 1 percent).
This means that monkeys would have likely done better in answering this question correctly, since randomly guessing the answer will lead monkeys to be right 25 percent of the time, while only 21 percent of doctors got it right.

The literature on judgment and decision making is overflowing with these kinds of shocking studies.
It is tempting to present such findings as prime evidence of the stupidity and inability of humankind.
Errors are in fact being made—gross errors by the people who should know best.
But before condemning humanity as hopelessly deficient, let’s take a step back and think about the situation.
The people making these errors are doctors.
They’ve been full-time students receiving formal education from the age of five to thirty.
And it’s not just the schooling.
You have to be pretty smart and motivated
to get into medical school in the first place, not to mention finish it and pass all your exams.
It hardly makes sense to relegate this group to the category of stupid people.

From the evolutionary psychologist’s perspective, it’s unlikely that the brain evolved to be dumb.
Instead, the problem might be not with the test takers but with the test makers.
The breast cancer problem is asking us a question on a frequency our brains don’t receive.
And it’s pretty important that we adjust the antenna.

COMMUNICATING ON OUR NATURAL FREQUENCY

In the modern world, we are awash in numerically expressed statistical information.
You may have spent enough years in math classes to cognitively understand that a 0.07 probability and a 7 percent likelihood are the same thing, but many of us will still furrow our brows and squint our eyes when digesting a statement about a 0.07 probability.
Probabilities and likelihood estimates are a common way to present statistical information, but they are also an evolutionarily recent invention.
Mathematical probabilities were invented in Europe in the mid-1600s.
And thanks to this statistical renaissance, we now have a really smart way to present numbers—so smart that probabilities often outsmart even us.

Gerd Gigerenzer, a decision scientist at the Max Plank Institute, is not a fan of mathematical probabilities or likelihood estimates.
He has long realized that trying to understand probabilities and likelihoods is the evolutionary equivalent of writing as compared to talking—an unnatural and difficult variant of something that’s easy in another format.
Hence, statistics presented in probability format can lead to a lot of problems.
Just as even well-educated writers have problems spelling words like “dumbbell,” “embarrass,” and “misspell,” smart doctors can have problems figuring out the likelihood that you have breast cancer if your mammogram comes back positive.

Instead of presenting information as conditional probabilities or likelihood estimates, Gigerenzer has demonstrated that people are much better at computing statistical information if it’s presented in terms of
natural frequencies
.
“Natural frequencies represent the
way ancestral humans encoded information,” Gigerenzer explains.
Whereas probabilities are like writing, natural frequencies are like talking.

Let’s take a boat upriver to the Shiwiar village.
Imagine that the village chief wants to catch dinner today, and he’s trying to decide whether it would be worthwhile to go hunting in the nearby red canyon.
For the Shiwiar, as for most of our ancestors, the only database available to make any kind of calculation consists of their own observations and those communicated by a handful of close others.
When the chief is trying to determine whether it’s wise to go hunting in the red canyon, he can consider what happened the last twenty times people went hunting there.
The chief observes natural frequencies—five out of the last twenty hunts in the red canyon were successful.
He doesn’t think in terms of probabilities, though.
Neither did our ancestors, who did not observe probabilities in their natural environment.
As a consequence, our brains do not process probabilities (“0.25 probability of success”) in the same way as they do natural frequencies (“5 out of 20 were successful”).
Years of formal math training have taught most of us that these two statistical statements mean the same thing, but decades of writing training still hasn’t outmoded spell-checkers.

Gigerenzer has found dramatic improvements in both novices and experts when hard questions are asked in terms of natural frequencies rather than probabilities.
Take the probability-laced breast cancer question asked earlier—the one that dumbfounded our panel of doctors.
Here is the same exact information translated into natural frequencies:

•
Ten out of every one thousand women have breast cancer.

•
Of these ten women with breast cancer, nine test positive.

•
Of the 990 women without breast cancer, about 89 also test positive.

If a woman tests positive, what are the chances that she has breast cancer?

When Gigerenzer asked doctors this question, the difference was remarkable.
Whereas only 21 percent of doctors answered correctly
when the question was presented in terms of probabilities, 87 percent answered correctly when it was presented in terms of natural frequencies.
One question is hard; the other is easy—even though, to a mathematician, both are asking the same exact thing.

And remember the Linda problem mentioned earlier?
It suffers from the same problem: it asks people a simple question in terms of complex probabilities.
Below is the Linda problem translated into natural frequencies:

Researchers polled one hundred women with the following features. They are on average thirty-one years old, single, outspoken, and very bright. They majored in philosophy. As students, they were deeply concerned with issues of discrimination and social justice, and also participated in antinuclear demonstrations.

Which is larger?

A.The number of women out of that one hundred that might be bank tellers.

B.The number of women out of that one hundred that might be bank tellers and active in the feminist movement.

Whereas only about 10 percent of people answer the Linda problem correctly when it is asked in probability format as presented earlier, almost 100 percent get the right answer when it’s presented in natural frequency format.
Mathematically, both versions ask the exact same question.
But the first version is confusing and leads to errors, whereas the second one is surprisingly easy.

TAPPING THE ANCESTRAL WISDOM OF OUR DIFFERENT SUBSELVES

To tap into the innate intelligence of the human brain, we need to understand how the mind expects to take in information.
Because our brains are designed to receive information in the way our ancestors would have received it, people will be much better problem solvers when problems are presented in ancestral formats—such as presenting
math problems by using natural frequencies (five out of one hundred) rather than probabilities (0.05).

We should also expect that people will be superb problem solvers when it comes to ancestral challenges—solving the types of evolutionary problems faced by our subselves.
And because each of our subselves specializes in different types of problems, we should be able to improve our reasoning abilities by making complex problems relevant to our different subselves.
In the remainder of the chapter, we look at two cases that unlock the wisdom of our inner team player—the affiliation subself.

DETECTING CHEATERS

Cognitive psychologists have developed some particularly difficult problems to test people’s abilities in deciphering what’s known as
conditional logic
.
A classic problem of this sort is known as the
Wason Task:

Figure 5.2
shows four cards. Each card has a number on one side and a letter on the other. Which card(s) should you turn over in order to test whether the following rule is true: If a card has an even number on one side, then it must have a consonant on the other side?

Figure 5.2.
The Wason Task

The correct answer is that you need to turn over two cards: The card with the “8” and the card with the “A.”
You don’t need to turn over any other card.
If you turn over the card labeled “3” and find that the second side has a consonant, this does not invalidate the rule
(which says nothing about odd numbers).
Likewise, if you turn over the “B” card and find an odd number, this also does not break the rule.

Don’t feel too bad if you didn’t get the right answer.
People are not very good at these kinds of problems.
Only about 10 percent of college students get the right answer.
The Shiwiar of the Amazon got it right 0 percent of the time.
We can take comfort in knowing that the payoff from many years of formal education is a boost in those test scores—to 10 percent.
And in case you’re wondering, paying over $40,000 per year for a Harvard education may improve scores even further—all the way up to 12 percent.