What is the curse of knowledge?
The curse of knowledge is the difficulty of setting aside what you know when you judge what someone else knows. Handover notes, briefs and training plans are where it does most of its work.
Answer to the question
What is the curse of knowledge?
The curse of knowledge is a bias in which people who know something find it hard to imagine not knowing it, and so misjudge what others understand. Colin Camerer, George Loewenstein and Martin Weber named it in 1989. At work it shows up in handover notes, briefs and training plans written by the person who knows most.
Key takeaways
- Camerer, Loewenstein and Weber (1989) found that better-informed people could not ignore their private information even where ignoring it would have paid, and that market conditions reduced the bias without removing it.
- In Elizabeth Newton's 1990 tapping study, tappers predicted that listeners would name half of the songs, and listeners named 2.5 per cent of the 120 tried.
- A 2014 replication of a false-belief version, with 3,074 participants in seven experiments, found the effect at less than half its original size, in the same direction.
- Hinds (1999) reported that the more expert the predictor, the worse the forecast of novice learning time, and that the debiasing methods tested did not remove the bias.
- Hinds, Patterson and Pfeffer (2001) found that novices taught by beginners did better on a circuit-wiring task, while novices taught by experts did better on a different task in the same domain.
Handover notes, project briefs, onboarding guides and delegated tasks share a weakness. They are written by the person who needs them least and read by the person who needs them most. The curse of knowledge, a term coined by economists, names the reason: it is the difficulty of setting aside what you know when you judge what someone else knows. The person with the information treats it as shared, and the gap goes unnoticed by the one person best placed to close it. The research behind the term is about forty years old and points in one direction: knowing more does not make a person better at imagining knowing less.
Where the term began
The effect is hard to see from the inside. A writer rereads a note and finds every line clear, because each line calls up the missing background without effort. A reader who lacks that background meets the same lines as gaps. Neither person is careless. They are standing in different places in relation to the same page.
Colin Camerer, George Loewenstein and Martin Weber gave the effect its name in a paper in the Journal of Political Economy. Economic models of the period assumed that a better-informed person can reproduce the judgement of a less-informed one, for instance when trading against someone who lacks the same information. The authors tested that assumption in experiments and found that better-informed people could not ignore their private information, even where ignoring it would have paid. Market conditions reduced the curse of knowledge without removing it.
The term dates from 1989 and has since been used for any case where knowledge distorts a judgement about another mind. Teachers, writers, designers and managers have all been described in its terms. The instruction-writing studies are covered in [The Curse of Knowledge in Instructions](https://thewhyweproject.com/articles/the-curse-of-knowledge-in-instructions), and this piece stays with the working setting: what moves between colleagues, and what goes missing on the way.
The most quoted picture of the curse of knowledge is a tapping game, and it moves the idea out of economics and into everyday communication. Elizabeth Newton, in a 1990 Stanford dissertation, asked one person to tap the rhythm of a well-known song and another to name it. Tappers predicted on average that listeners would name half of the songs. Listeners named 2.5 per cent of the 120 tried. Richard Shotton retells the study in The Choice Factory. The tapper hears the melody while the listener hears knocks on a table.
Shotton carries the idea into advertising. The people who make a poster look at it on a screen, at a desk, with a brief beside them, and a consumer sees it for a moment from a moving car. The maker cannot easily recover the consumer's view because the maker already knows what the poster is for. His remedy is to judge work where the audience meets it, which is a rule about location rather than effort.
The maker cannot easily recover the consumer's view because the maker already knows what the poster is for.
What replications leave standing
The best-known laboratory version of the curse concerns false beliefs. Participants who know where an object really is tend to credit another person with that knowledge, and the result was first reported in an earlier study. The task asks people to judge what someone without their information would believe, and the 2014 authors describe the error as more likely when the answer based on the participant's own knowledge seems plausible.
A 2014 replication of that false-belief version of the curse of knowledge ran seven experiments with 3,074 participants. The direction held, and the effect came out at less than half the original size, a knowledge effect of 0.20 against 0.47 in standardised units. The authors suggested that the influence of plausibility on adults' curse of knowledge may be too small to matter much for real-world perspective-taking.
That result concerns one paradigm, and it is a reminder to quote the direction of the curse of knowledge rather than a size. The 1989 markets, the tapping task and the workplace studies below each measure different things in different units, so their sizes cannot be set side by side. What they share is a direction, and the two papers that follow test it on skilled people handing work to beginners.
Expert instructions, novice results
Pamela Hinds asked people with different levels of expertise to predict how long novices would need to learn a task on a mobile phone. Her 1999 abstract reports that the more expert the predictor, the worse the prediction, with novice completion times underestimated, and that the debiasing methods she tested did not remove the bias. One reading is that experience of the task had made the task look shorter.
For a manager the practical reading concerns estimates. A person who has run a process for years will tend to quote a short learning time for a newcomer, so a ramp-up plan written by the expert carries the curse of knowledge into the schedule itself. Hinds's task was a phone, not a department, and the step from her result to onboarding plans is our extension. It is still a useful place to look first when a new starter is reported to be slower than the plan assumed.
In 2001 Hinds, with two colleagues, moved from predictions to instructions, using an electronic circuit-wiring task. Experts who instructed novices used more abstract and advanced statements and fewer concrete ones than beginners did. Novices instructed by beginners performed better on the target task and reported fewer problems with the instructions. Novices instructed by experts did better on a different task in the same domain, which the authors took to mean that the abstract concepts helped learning transfer.
Read together, the two results make the curse of knowledge a trade rather than a plain fault, since the abstraction that confuses a beginner on day one is the same abstraction that carries over to a new task.
Concrete steps carry a newcomer through a first run, and the expert's abstractions seem to pay later, when the task changes. A handover written only in the expert's terms leaves out the first layer. A handover written only as steps leaves out the second, and which one a given team needs probably depends on whether the successor will repeat the job or adapt it.
Concrete steps carry a newcomer through a first run, and the expert's abstractions seem to pay later, when the task changes.
Why familiar colleagues are harder
Kenneth Savitsky and four colleagues tested a related idea in 2011 in the Journal of Experimental Social Psychology, under the name closeness-communication bias. In one experiment, participants who followed directions from a friend were more likely to make an egocentric error, looking at and reaching for an object that only they could see, than those who followed directions from a stranger. In two further experiments, people who tried to convey a meaning with an ambiguous phrase overestimated their success more when the listener was a friend or spouse than when the listener was a stranger.
The authors' account is simple. People monitor a stranger's different perspective because they know they must, and let their guard down with a friend, relying more on their own view. The participants were friends and spouses, not colleagues. Carried to a team that has worked together for years, the account suggests that handovers inside it are the ones where the writer feels least need to spell anything out.
A handover test worth running
Hinds found that the debiasing methods she tried did not remove the bias in predictions, and Savitsky and colleagues found that closeness makes the writer more confident. Rereading your own note for signs of the curse of knowledge is therefore a weak check. The findings point to a simple alternative: give the document to someone who has not done the task, watch where they stall, and count each stall as the writer's omission.
The reader should come from outside the team where possible, and should be asked to say back what they think the work is for as well as how to do it, since the closeness result suggests an insider supplies the missing context without noticing.
The same applies to briefs and delegated tasks, where the person setting the work already knows what finished looks like and the person receiving it does not. Confidence is no guide here. In the closeness experiments, people communicating with friends and spouses overestimated their success more than people communicating with strangers, so a brief that feels obvious to its author has passed no test at all. Run the same test on the layers Hinds's circuit study separates.
Ask a newcomer to follow the steps once, then ask a second person to adapt the work to a changed case. Two different failures point to two different gaps in the note. Shotton's advice to judge work where the audience meets it translates directly, because the place a handover is read is a busy desk on a first day, not the writer's calm afternoon.
One outside reader turns a feeling of clarity into a record.
Common questions
What is the curse of knowledge?
The curse of knowledge is a bias in which a person who knows something finds it hard to imagine not knowing it, and so misjudges what others understand. Colin Camerer, George Loewenstein and Martin Weber named it in a 1989 economics paper after finding that better-informed people could not ignore what they knew.
Does the curse of knowledge affect close colleagues more?
A 2011 set of experiments by Kenneth Savitsky and colleagues found that people overestimated how well they communicated with a friend or spouse more than with a stranger. Colleagues were not tested, so the application to a long-standing team is an inference.
How large is the curse of knowledge?
It depends on the task, and no single figure covers them all. A 2014 replication of one false-belief version, with 3,074 participants, found the effect at less than half its first reported size while keeping the same direction. The tapping, forecasting and instruction studies use other measures.
How can a team reduce the curse of knowledge in handovers?
The studies do not test a remedy that works every time. Hinds's debiasing methods did not remove the bias in predictions. A practical step, ours rather than a research result, is to give the handover note to someone who has not done the task and record where they stall.
Sources
Shotton, R. (2018). The Choice Factory. Seed book.
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. doi:10.1086/261651 https://doi.org/10.1086/261651
Newton, E. L. (1990). The rocky road from actions to intentions (Doctoral dissertation). Stanford University, Department of Psychology.
Ryskin, R. A., & Brown-Schmidt, S. (2014). “Do adults show a curse of knowledge in false-belief reasoning? A robust estimate of the true effect size.” PLoS ONE, 9(3), e92406. doi:10.1371/journal.pone.0092406 https://doi.org/10.1371/journal.pone.0092406
Hinds, P. J. (1999). “The curse of expertise: The effects of expertise and debiasing methods on prediction of novice performance.” Journal of Experimental Psychology: Applied, 5(2), 205-221. doi:10.1037/1076-898X.5.2.205 https://doi.org/10.1037/1076-898X.5.2.205
Hinds, P. J., Patterson, M., & Pfeffer, J. (2001). “Bothered by abstraction: The effect of expertise on knowledge transfer and subsequent novice performance.” Journal of Applied Psychology, 86(6), 1232-1243. doi:10.1037/0021-9010.86.6.1232 https://doi.org/10.1037/0021-9010.86.6.1232
Savitsky, K., Keysar, B., Epley, N., Carter, T., & Swanson, A. (2011). “The closeness-communication bias: Increased egocentrism among friends versus strangers.” Journal of Experimental Social Psychology, 47(1), 269-273. doi:10.1016/j.jesp.2010.09.005 https://doi.org/10.1016/j.jesp.2010.09.005