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.
Overconfidence 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.
from HBR.org https://ift.tt/2pLoVLC
