Why Experts Are Often Wrong, and How to Get Better Advice From Them

Experts are often right. That's why we go to them. But they can also give bad advice without being frauds or fools, for reasons researchers have documented in detail: their knowledge makes it hard to explain things to people who don't share it, their confidence can run ahead of their accuracy, and their incentives don't always line up with yours.

The first of these has a name, the curse of knowledge. Once you understand something well, it's very hard to remember what it was like not to, and that makes experts consistently worse at explaining than they think. This article covers the curse of knowledge and two related traps, when expertise deserves your trust, and how to get better advice out of the experts you rely on.

The curse of knowledge: why experts give bad advice they think is clear

In 1990, Elizabeth Newton, a graduate student at Stanford, ran a simple experiment. One group of people, the "tappers," tapped out the rhythm of well-known songs such as "Happy Birthday" on a table. Another group, the "listeners," tried to name the songs.

Before they started, the tappers predicted how often listeners would get it right. They guessed about half the time. Out of 120 songs, listeners identified 3, about 2.5%.

The tappers were surprised. In their heads, they could hear the melody playing along with their fingers. The listeners heard only knocking.

That gap is the curse of knowledge. The economists Colin Camerer, George Loewenstein and Martin Weber gave it its name in 1989, after showing that people with better information struggled to predict how less-informed people would behave, even when getting it right earned them money.

It shows up whenever an expert explains something. A doctor who has seen your symptoms many times may skip the steps that would make the diagnosis clear to you, because to them those steps are obvious. You leave with a prescription you half understand.

When expert forecasts fail

Philip Tetlock spent about two decades collecting roughly 28,000 forecasts from 284 experts in politics and economics, published in Expert Political Judgment in 2005. On average, the experts did only slightly better than simple rules of thumb, and not much better than chance on many questions.

Two patterns stood out. Experts who organised their thinking around one big idea, whom he called "hedgehogs," did worse than more flexible "foxes" who drew on many ideas and adjusted as they went. And experts who were more often in the media tended to be less accurate.

Later, in the Good Judgment Project, Tetlock's team found a group of volunteers, "superforecasters," who consistently beat other forecasters, including in some comparisons intelligence analysts with access to classified information. They weren't all specialists. What they shared was a way of thinking: putting numbers on beliefs, updating often in small steps, and actively looking for evidence against their current view. (More on that habit in Bayesian thinking.)

Three ways expertise misleads

1. Confidence that runs ahead of accuracy

Feeling certain isn't the same as being right, and experts aren't exempt. Daniel Kahneman, in Thinking, Fast and Slow, cites a study of patients who died in intensive care. Their doctors' diagnoses were compared with autopsy results, and clinicians who had been "completely certain" of a diagnosis while the patient was alive were wrong about 40% of the time.

Part of the reason is how expertise feels from the inside. After years of practice, answers arrive quickly and fluently, and fluency feels like certainty. But the feeling comes from pattern recognition, not from a check on whether the pattern fits this case.

2. Incentives that bend advice

Advice can be shaped by what the adviser is paid for, without anyone being dishonest. Sendhil Mullainathan, Markus Noeth and Antoinette Schoar sent trained actors posing as ordinary clients to real financial advisers. The advisers tended to steer clients towards actively managed, higher-fee funds and away from cheap index funds, even when the client's existing portfolio was low-cost and well diversified.

Medicine has its own version. In a survey by David Studdert and colleagues, 93% of Pennsylvania doctors in high-liability specialties said they sometimes practised "defensive medicine," ordering tests or procedures partly to protect themselves from lawsuits.

None of this requires bad faith. The adviser can sincerely believe the advice, and it can still be shaped by things unrelated to your outcome.

3. Expertise stretched beyond its field

Experts get asked about things outside their speciality all the time: the economist on health policy, the surgeon on running a hospital, the founder on education. Expertise doesn't transfer cleanly between fields, but the authority does. That's the edge of the circle of competence, where an expert sounds as sure as they do at home.

When to trust experts, and when to ask more questions

Daniel Kahneman and Gary Klein, who came from opposite camps on the value of intuition, wrote a joint paper in 2009 about when expert intuition can be trusted. Their answer: when the environment is regular enough to be learned, and the expert has had plenty of practice with quick, clear feedback. Firefighters, chess players and anaesthetists can meet those conditions. Stock pickers and long-range political forecasters often can't.

Trust expert judgment more when:

• the field gives fast, clear feedback (weather forecasting, anaesthesia, chess)
• their predictions are regularly checked against outcomes
• their incentives line up with your outcome
• they mention the limits of their knowledge without being asked

Ask more questions when:

• the field is complex and open-ended (markets, geopolitics, the long-run economy)
• they sound certain and never mention uncertainty
• nobody checks their track record
• they benefit from your accepting one particular recommendation

The two-experts test

For an important decision, get a second opinion from someone with no connection to the first expert, and don't tell them what the first one said.

If they reach the same conclusion independently, your confidence is better justified. If they disagree, you've learned something important: the question is more uncertain than the first expert's confidence suggested.

Getting better advice out of experts

You can't remove the curse of knowledge from an expert's head, but you can ask questions that work around it.

"Can you explain it as you would to a smart twelve-year-old?" If they can't explain the core logic simply, either they're struggling to translate it or the logic is weaker than it sounds. Either way, you've learned something.

"Out of 100 people in my situation, how many get this result?" Experts often think in terms of the story of your particular case. Base rates anchor that story in what usually happens. Gerd Gigerenzer's research shows that both doctors and patients understand risks much better when they're given as counts like this rather than percentages.

"What would change your mind?" A well-calibrated expert can name conditions under which their recommendation would be wrong. If they can't think of any, be cautious.

"How do you get paid for this?" Asked politely, it's a reasonable question, and the answer tells you which way any incentive might lean.

Check your own calibration

Experts aren't the only ones whose confidence can outrun their accuracy. The Bayesian Betting Hall is a short calibration test: you bet on ten claims, say how sure you are of each, and see your average confidence next to how often you were right. It's a quick way to see the gap this article describes, from the inside.

The verdict on expert advice

Experts aren't frauds. Their knowledge can outgrow their ability to explain it, their confidence is often rewarded more than their accuracy, and their incentives can pull their advice slightly away from your interests. The right response is structured scepticism, not distrust: treat expert advice as strong evidence that deserves real weight, then ask the questions that check it.

The experts most worth trusting are often the ones who tell you where their expertise ends.

Frequently Asked Questions

What is the curse of knowledge?

It's the difficulty, once you know something, of imagining what it's like not to know it. Elizabeth Newton's tapping study is the classic example: people tapping songs expected listeners to name about half of them, and listeners named about one in forty.

Why do experts give bad advice?

Usually not from dishonesty. The curse of knowledge makes their explanations less clear than they think, their confidence can outrun their accuracy, incentives can shape their recommendations, and they're often asked about things outside their speciality.

Are expert predictions worse than non-experts'?

In complex, open-ended fields such as politics and economics, Tetlock found experts did only slightly better than simple baselines, and the most famous did worse than average. In fields with fast, clear feedback, like weather forecasting, expertise is much more reliable.

How do I know when to trust an expert?

Trust them more when their field gives fast feedback, their track record is checked, their incentives align with yours and they're open about uncertainty. Ask more questions when they sound certain in an unpredictable field or benefit from one particular recommendation.

What is the two-experts test?

Getting a second opinion from an expert with no link to the first, without telling them what the first said. Agreement increases your confidence; disagreement tells you the question is more uncertain than it seemed.

Sources

1. Newton, E. L. (1990). The rocky road from actions to intentions (Doctoral dissertation). Stanford University.
2. Camerer, C., Loewenstein, G., & Weber, M. (1989). The curse of knowledge in economic settings: An experimental analysis. Journal of Political Economy, 97(5), 1232–1254. https://doi.org/10.1086/261651
3. Tetlock, P. E. (2005). Expert Political Judgment: How Good Is It? How Can We Know? Princeton University Press.
4. Tetlock, P. E., & Gardner, D. (2015). Superforecasting: The Art and Science of Prediction. Crown.
5. Kahneman, D. (2011). Thinking, Fast and Slow. Farrar, Straus and Giroux.
6. Podbregar, M., Voga, G., Krivec, B., Skale, R., Parežnik, R., & Gabršček, L. (2001). Should we confirm our clinical diagnostic certainty by autopsies? Intensive Care Medicine, 27(11), 1750–1755. https://doi.org/10.1007/s00134-001-1129-x
7. Mullainathan, S., Noeth, M., & Schoar, A. (2012). The market for financial advice: An audit study. NBER Working Paper 17929.
8. Studdert, D. M., et al. (2005). Defensive medicine among high-risk specialist physicians in a volatile malpractice environment. JAMA, 293(21), 2609–2617. https://doi.org/10.1001/jama.293.21.2609
9. Kahneman, D., & Klein, G. (2009). Conditions for intuitive expertise: A failure to disagree. American Psychologist, 64(6), 515–526. https://doi.org/10.1037/a0016755
10. Gigerenzer, G., Gaissmaier, W., Kurz-Milcke, E., Schwartz, L. M., & Woloshin, S. (2007). Helping doctors and patients make sense of health statistics. Psychological Science in the Public Interest, 8(2), 53–96. https://doi.org/10.1111/j.1539-6053.2008.00033.x