PSYCHOLOGY

Research: Learning a Little AboutSomething Makes UsOvercondentby Carmen Sanchez and David Dunning

MARCH 29, 2018

HBR STAFF/TOM KELLEY ARCHIVE/GETTY IMAGES

As former baseball pitcher Vernon Law once put it, experience is a hard teacher because it gives the

test first, and only then provides the lesson.

Perhaps this observation can explain the results of a survey sponsored by the Association of

American Colleges & Universities. Among college students, 64% said they were well prepared to

work in a team, 66% thought they had adequate critical thinking skills, and 65% said they were

proficient in written communication. However, among employers who had recently hired college

students, less than 40% agreed with any of those statements. The students thought they were much

further along in the learning curve toward workplace success than their future employers did.

Overcondence Among Beginners

Our research focuses on overconfidence as people tackle new challenges and learn. To be a beginner

is to be susceptible to undue optimism and confidence. Our work is devoted to exploring the exact

shape and timeline of that overconfidence.

One common theory is that beginners start off overconfident. They start a new task or job as

“unconscious incompetents,” not knowing what they don’t know. Their inevitable early mistakes

and miscues prompt them to become conscious of their shortcomings.

Our work, however, suggests the opposite. Absolute beginners can be perfectly conscious and

cautious about what they don’t know; the unconscious incompetence is instead something they

grow into. A little experience replaces their caution with a false sense of competence.

Specifically, our research focused on the common task of probabilistic learning in which people

learn to read cues from the environment to predict some outcome. For example, people must rely on

multiple signals from the environment to predict which company’s stock will rise, which applicant

will do the best job, or which illness a patient is suffering from. These can be hard tasks — and even

the most expert of experts will at times make the wrong prediction — but a decision is often essential

in many settings.

In a laboratory study, we asked participants to imagine they were medical residents in a post-

apocalyptic world that has been overrun by zombies. (We were confident that this would be a new

scenario to all our participants, allowing them all to start as total novices.) Their job, over 60

repeated trials, was to review the symptoms of a patient, such as whether the patient had glossy

eyes, an abscess, or brain inflammation, and diagnose whether the patient was healthy or infected

with one of two zombie diseases. Participants needed to learn, by trial and error, which symptoms to

rely on to identify zombie infections. Much as in a real-world medical diagnosis of a (non-zombie)

condition, the symptoms were informative but fallible clues. There were certain symptoms that

made one diagnosis more likely, but those symptoms were not always present. Other potential

symptoms were simple red herrings. Participants diagnosed patients one at a time, receiving

feedback after every diagnosis.

The Beginner’s Bubble

We found that people slowly and gradually learned how to perform this task, though they found it

quite challenging. Their performance incrementally improved with each patient.

Confidence, however, took quite a different journey. In each study, participants started out well-

calibrated about how accurate their diagnoses would prove to be. They began thinking they were

right 50% of the time, when their actual accuracy rate was 55%. However, after just a few patients,

their confidence began skyrocketing, far ahead of any accuracy they achieved. Soon, participants

estimated their accuracy rate was 73% when it had not hit even 60%.

It appears that Alexander Pope was right when he

said that a little learning is a dangerous thing. In our

studies, just a little learning was enough to make

participants feel they had learned the task. After a

few tries, they were as confident in their judgments

as they were ever going to be throughout the entire

experiment. They had, as we termed it, entered into

a “beginner’s bubble” of overconfidence.

What produced this quick inflation of confidence? In

a follow-up study, we found that it arose because

participants far too exuberantly formed quick, self-

assured ideas about how to approach the medical

diagnosis task based on only the slimmest amount of

data. Small bits of data, however, are often filled

with noise and misleading signs. It usually takes a

large amount of data to strip away the chaos of the

world, to finally see the worthwhile signal. However,

classic research has shown that people do not have a

feel for this fact. They assume that every small

sequence of data represents the world just as well as long sequences do.

But our studies suggested that people do eventually learn — somewhat. After participants formed

their bubble, their overconfidence often leveled off and slightly declined. People soon learned that

they had to correct their initial, frequently misguided theories, and they did. But after a correction

phase, confidence began to rise again, with accuracy never rising enough to meet it. It is important

to note that although we did not predict the second peak in confidence, it consistently appeared

throughout all of our studies.

A Real-World Bubble

The real world follows this pattern. Other research

has found that doctors learning to do spinal surgery

usually do not begin to make mistakes until their

15th iteration of the surgery. Similarly, beginning

pilots produce few accidents — but then their

accident rate begins to rise until it peaks at about

800 flight hours, where it begins to drop again.

We also found signs of the beginner’s bubble outside

of the laboratory. As with probabilistic learning, it

has been shown that most people under the age of

18 have little knowledge of personal finance. Most

primary and secondary educational systems do not

teach financial literacy. As such, personal finance is

something most learn by trial and error.

We found echoes of our laboratory results across the

life span in surveys on financial capability

conducted by the Financial Industry Regulatory

Authority. Each survey comprised a nationally

representative sample of 25,000 respondents who

took a brief financial literacy test and reported how knowledgeable about personal finance they

believed they were. Much like in the laboratory, both surveys showed that real financial literacy

arose slowly, incrementally, and uniformly across age groups.

Self-confidence, however, surged between late adolescence and young adulthood, then leveled off

among older respondents until late adulthood, where it began to rise again — a result perfectly

consistent with our laboratory pattern.

It is important to note that our work has several limitations. In our experiments, participants

received perfect feedback after each trial. In life, consistent feedback like this is often unavailable.

Also, our tasks traced how confidence changed as people learned truly novel tasks. There are plenty

of tasks people learn in which they can apply previous knowledge to the new task. We do not know

how confidence would change in these situations. Relatedly, we cannot be certain what would

happen to overconfidence after the 60th trial.

With that said, our studies suggest that the work of a beginner might be doubly hard. Of course, the

beginner must struggle to learn — but the beginner must also guard against an illusion they have

learned too quickly. Perhaps Alexander Pope suggested the best remedy for this beginner’s bubble

when he said that if a few shallow draughts of experience intoxicate the brain, the only cure was to

continue drinking until we are sober again.

Carmen Sanchez is a PhD candidate in Social and Personality Psychology at Cornell University. She studies howperceptions of abilities change as people learn, cultural differences in self-enhancement, and nancial decision-making.

David Dunning is a Professor of Psychology at the University of Michigan. His research focuses on the psychology ofhuman misbelief, particularly false beliefs people hold about themselves.