The Evaluating Self

21Unskilled and Unaware of It

Justin Kruger and David Dunning, Journal of Personality and Social Psychology 77(6), pp. 1121–1134, 1999

Unskilled and Unaware of It, 1999 — the argument in five moves The dualburden Three domains It takes oneto know one Make themcompetent The burdenof expertise The skill that getsan answer right isthe skill that seesit is right. Humour, logic andgrammar: a bottomquarter scoring 10thputs itself at 60th. They also misjudgetheir peers' work,so comparisonteaches them little. Ten minutes of logictraining, and theestimates falltoward the truth. The best performersunderrate their ownstanding — an errorabout others. The deficit that produces the poor performance is the deficit that hides it.
Figure 21.0 — The paper in five moves: a thesis about one skill doing two jobs, three domains that test it, a failure of social comparison, a training study that reverses the deficit, and the mirror error at the top.

In 1995 McArthur Wheeler robbed two Pittsburgh banks in daylight with nothing on his face but lemon juice, which he believed made him invisible to video cameras. Kruger and Dunning open with him to make a point that is not obvious: when a person's strategies are bad, that person is in no position to notice. The skills that produce a correct answer, they argue, are largely the same skills that recognise one: whatever lets a person write a grammatical sentence is what lets them see that a sentence is ungrammatical. Someone who lacks the first therefore lacks the second, and is left not merely wrong but confident. Darwin had said as much in 1871, in a line the paper quotes: "ignorance more frequently begets confidence than does knowledge". Four studies test the claim on humour, logical reasoning and English grammar. In each, students in the bottom quarter placed themselves near or above the middle; pooled, their scores put them in the 12th percentile and their estimates in the 62nd. Two further results follow from the same account. The unskilled could not read competence in other people's work either, so watching better performers taught them nothing. And when the authors made incompetent participants competent, their self-estimates fell.

Imperfect self-assessments

The tendency the paper sets out to explain was already documented. High school students rate themselves above average in leadership, getting on with others and written expression; business managers rate themselves more able than the typical manager; football players think themselves shrewder about the game than their teammates. The above-average effect, as the literature calls it, defies descriptive statistics, and the usual explanations for it are motivational: people want to think well of themselves. Kruger and Dunning add a cognitive source. If a person cannot see that a performance went badly, and people generally assume they have taken the most reasonable option available, then the absence of a signal of failure is read as success.

The materials for the account were also in place, in the research on expertise. Novices in physics are worse than experts at judging how hard a problem is, novices in chess at judging how often they must see a board position before they can reproduce it, novices in tennis at telling whether a shot came off. Weak readers misjudge their comprehension, and drivers who have failed a test predict their reaction times least accurately. None of this work had asked whether the metacognitive deficit produced inflated estimates, or tied it to the above-average effect. That is what the four studies do, through four predictions: that the incompetent will overestimate themselves dramatically, that they will be less able to recognise competence anywhere, that they will therefore learn nothing from social comparison, and that making them competent will correct all three.

Why the deficit hides itself Lacks the skill Gives a wrong answer Cannot tell a wronganswer from a right one Nothing marks theanswer as an error The work is judgedto have gone well Nothing in the person's experience marks the answer as wrong, so it is taken to be right.
Figure 21.1 — The mechanism. The deficit that produces the wrong answer is the same deficit that removes the signal that it is wrong, so what reaches the person is an absence of evidence of failure.

Humour, logic and grammar

Study 1 chose a domain where competence means knowing what other people will find funny. Sixty-five Cornell undergraduates rated thirty jokes on an eleven-point scale, and their ratings were compared with those of eight professional comedians. One comedian's ratings failed to correlate with the rest and were dropped, leaving a panel reliability of .76; the jokes ranged from one the panel rated 1.3 to one it rated 9.6. Participants then placed their ability to recognise what is funny against the average Cornell student on a percentile scale. The average student put himself in the 66th percentile. Perceived and actual ability were correlated, at .39, so the students were not guessing blindly. The bottom sixteen scorers, whose ratings actually placed them in the 12th percentile, put themselves in the 58th — above average, in a domain in which they were among the worst in the room.

The authors raised the obvious objection against themselves at once. Perceptions correlate imperfectly with reality, people at the bottom have nowhere to go but up, and regression to the mean guarantees a result of this shape. Their first answer is the asymmetry: regression alone predicts equal and opposite miscalibration at the top, and the top quarter's error was far smaller. The real answer is deferred to the two later studies.

Study 2 changed domains to remove a different objection. Humour has no uncontroversial criterion, and people define ambiguous abilities in whatever way flatters them. Forty-five students took twenty logical reasoning items from a Law School Admission Test preparation guide, where the answers are not matters of taste, and estimated their reasoning ability, their test score in percentile terms, and the number of items they had got right. The class placed its ability in the 66th percentile and its scores in the 61st, while being roughly accurate about raw scores, 13.3 claimed against 12.9 actual. The bottom eleven, who scored in the 12th percentile, put their ability in the 68th and their test score in the 62nd, and claimed 14.2 correct answers when they had 9.6, an overstatement of nearly fifty per cent. That last number is not comparative: the error is about the self, not about a misjudged peer group.

Study 3 repeated the design on American Standard Written English, twenty items from a teacher examination guide, with eighty-four students. The bottom seventeen scored in the 10th percentile and placed their ability in the 67th and their performance in the 61st, claiming 12.9 correct where they had 9.2.

Self-rated ability against measured standing, by quarter percentile 0 25 50 75 100 55th 12th 43 points bottom second third top quarter of the distribution, by test score what they said their ability was where their score put them Untrained participants of the fourth study, Table 2. The two lines meet at the right.
Figure 21.2 — Self-rated ability against measured percentile, by quarter of the distribution, from the untrained participants of the fourth study. The two lines converge from left to right; almost the whole gap sits in the bottom quarter.
The bottom quarter in each of the four studies — percentile 0 25 50 75 100 1258 1268 1067 1355 humourn = 16 logicn = 11 grammarn = 17 logic, Wasonn = 37 measured percentile self-rated ability
Figure 21.3 — The bottom quarter in all four studies: where they scored and where they placed themselves, from Figures 1 to 4 of the paper.

It takes one to know one

The second half of the thesis is that the deficit also blinds a person to competence in others, and the third study tested it four to six weeks later. Its bottom seventeen and top nineteen performers came back and were each handed five completed grammar tests spanning the range of scores their classmates had produced, a fact they were told. They graded each one, then re-rated themselves.

The top performers graded well: the correlation between the marks they gave and the marks the tests deserved averaged .66, against .37 for the bottom performers, and their summed absolute error was 9.2 against 17.4. The self-ratings that followed divided as sharply. Having just read five tests, several of them clearly better than their own, the bottom group did not move: their ability estimate drifted from the 66.8th percentile to the 63.2nd, their test estimate rose from the 60.5th to the 65.4th, and neither change approached significance. The top group raised its ability estimate to the 77.2nd percentile and its test estimate to the 79.7th, toward an actual standing of 88.7.

That pattern explains something that had shown up in every study so far without being accounted for: the best performers consistently underrated themselves. Kruger and Dunning read it as a false-consensus effect. The top performers were not wrong about their own work; they were wrong about everyone else's, assuming that answers as obvious as theirs would be obvious to their peers. The prediction that distinguishes this from simple regression is precise. Learning that your peers did badly tells you nothing about your own raw score, so a false-consensus error should be corrected for comparative estimates and leave absolute ones alone. The top group's estimate of its own raw score went from 16.9 to 16.6, against an actual 16.4, and did not budge.

Two miscalibrations, two sources Bottom quarter — an error about self Graded five peers' tests at r = .37 After seeing work better than its own ability 66.8 to 63.2 test score 60.5 to 65.4 raw score 12.9 to 13.7 actual: 10th percentile, 9.2 correct Top quarter — an error about others Graded five peers' tests at r = .66 After seeing work worse than its own ability 71.6 to 77.2 test score 69.5 to 79.7 raw score 16.9 to 16.6 actual: 89th percentile, 16.4 correct Only comparative estimates moved at the top, as a false-consensus error predicts.
Figure 21.4 — The two miscalibrations have opposite sources. Grading five peers' tests corrected the error at the top and left the error at the bottom untouched, from the paper's Table 1.

Competence begets calibration

The fourth study manipulated the variable rather than measuring it, which is what separates the metacognitive account from the statistical one. A hundred and forty students took ten problems built on the Wason selection task, in which four cards and a rule are given and the participant must say which cards would have to be turned over to test the rule. They rated themselves as before. Then seventy of them, chosen at random, worked through a ten-minute training packet on testing logical rules, modelled on Cheng and colleagues' work from 1986, while the rest did an unrelated filler task of the same length. Everyone then marked which problems they thought they had got right, and rated themselves a second time.

Before training, the bottom thirty-seven scored in the 13th percentile, placed their ability in the 55th and their performance in the 53rd, and believed they had solved 5.5 of the ten problems. They had solved 0.3.

Training changed what they could see. Asked to mark their own answers right or wrong, trained participants classified 9.3 of ten correctly against 6.3 for the untrained, and among the bottom quarter the gap was 9.3 against 3.5, which left them no worse at monitoring themselves than the top scorers at 9.9. Their self-estimates followed: ability from the 55th percentile to the 44th, test performance from the 51st to the 32nd, and claimed raw score from 5.3 correct to 1.0, against an actual 0.4. They still overestimated their standing, but they were no longer miscalibrated about their score. The untrained bottom quarter did not improve on any measure, and its estimate of its own raw score moved the wrong way, from 5.8 to 6.3.

Ten minutes of training, and the bottom quarter could see self-rated percentile on the test 0 50 100 actual 55545132 beforeafterbeforeafter untrainedtrained own answers graded right or wrong, of ten 3.59.39.9 bottom,untrained bottom,trained top,trained
Figure 21.5 — Ten minutes of instruction in logic, and the bottom quarter could grade its own answers and lowered its estimates accordingly. From the paper's Table 2 and its metacognition measure.

Two mediation analyses tie the parts together. Among the untrained, test performance predicted metacognitive skill at .75, and metacognitive deficits predicted inflated self-assessment on all three measures with objective performance held constant, betas of −.40 to −.49. Among the bottom quarter, once metacognitive skill was controlled, training itself no longer predicted anything: the improvement in self-knowledge travelled entirely through the improvement in the ability to tell a right answer from a wrong one. Regression to the mean predicts none of this, since it says nothing about what happens to self-estimates when a person's skill is altered after the test is scored. The paradox the authors leave standing is that the cure removes the patient. The way to make people see their incompetence is to make them competent, at which point there is nothing left to see.

The burden of expertise, and what the account does not cover

The general discussion offers anosognosia as the analogy: damage that both paralyses the left side and removes the capacity to notice the paralysis, so that patients asked why they will not lift a cup say they are tired. Across the four studies the bottom quarter did not merely overestimate itself but believed itself above average, and was close to four times more miscalibrated than the top quarter.

The paper is careful about how little this explains on its own. Bottom-quarter participants accounted for most of the above-average effect, overestimating by about fifty percentile points, but the other three quarters overestimated too, by just over six points, and the metacognitive account says nothing about that residue. Motivational bias, self-serving definitions of ability and selective recall are all still in play. Nor is the deficit universal: few readers, the authors note, would bet on themselves against Michael Jordan. The prediction holds where knowing the subject is what competence consists of, as in grammar and logic, and fails where competence is physical. Coaches understand basketball and cannot dunk; art appraisers judge calligraphy they could not produce. A second limit is a floor: to overestimate yourself you need enough theory to believe you can produce an answer at all. Nobody overrates their ability to translate Slovenian proverbs, and in domains that blank people rate themselves below their peers.

One puzzle the paper poses and does not solve is why ordinary life fails to correct the error. It offers four reasons. People rarely tell each other bad news. Many tasks return no self-correcting information. Failure is ambiguous in a way success is not, since success needs skill and effort and luck together while failure needs only one of them missing, so a person told they have failed can always blame something else. And the remaining channel, watching other people, is the one the third study closed.

The article ends on its own exposure. Having argued that incompetence hides itself, the authors concede that their paper may contain faulty logic or methodological error, and that to whatever extent it does, "it is not a sin we have committed knowingly".

Since 1999

The finding left the literature almost immediately. Kruger and Dunning were awarded an Ig Nobel Prize in psychology in 2000, and the phrase "Dunning–Kruger effect", which appears nowhere in the paper, was attached to it by others and spread into ordinary speech within a decade. Most of that usage is a claim the paper never makes: that stupid people think they are clever. The studies are about specific domains, and a footnote sets aside the generally incompetent person as no part of the research. They are also not about a reversal of rank. Bottom-quarter students placed themselves lower than top-quarter students did in every study. What the studies show is a compression, everyone bunched near the upper middle of a scale on which they are in fact spread out.

The statistical critique arrived in 2002, when Krueger and Mueller argued in the same journal that the pattern falls out of two things already known: regression to the mean, since test scores are measured with error and self-estimates correlate only weakly with them, and the better-than-average effect, which moves everyone's estimate up. Between them these produce crossing lines of the paper's shape without any metacognitive deficit. Burson, Larrick and Klayman pressed a related point in 2006: whether the poor performers or the good ones are the worse judges depends on how hard the task is, which makes difficulty rather than skill the moving part. Later work by Nuhfer and colleagues and by Gignac and Zajenkowski showed that random numbers can be plotted into a figure much like Figure 1, and that when actual and self-assessed ability are modelled directly the relation is mostly linear.

The critique is largely about the graph, and the graph was never the whole argument. The measures regression cannot touch are the other ones: how well people sorted their own answers into right and wrong, how well they graded a stranger's test, and what happened when ten minutes of instruction changed their skill after their score was fixed. Ehrlinger, Johnson, Banner, Dunning and Kruger returned to these in 2008 with incentives for accuracy and with participants found at a debate tournament and a gun club rather than in a psychology course, and the overestimation by low performers survived. What has held up is smaller than the popular version and harder to dismiss than the artefact version: self-assessments of ability track performance weakly at best, the weakest performers are the worst placed to know it, and what most reliably improves a person's judgment of their own work is getting better at the work.

Claims drawn from this chapter · 10

Everyday life rarely tells poor performers that they are poor performers

Kruger and Dunning argue that ordinary life does not correct a poor performer's inflated self-view. People hold back bad news, most tasks give no clear right answer, and learning from better performers is exactly what the skill deficit prevents.

Becausefour reasons are offered in the general discussion and only the last is backed by the paper's own data, the regrading phase in Study 3.
LimitsThree of the four reasons are asserted rather than tested, and domains with fast scored feedback — forecasting, trading, competitive games — are standing counter-examples.
PracticeBuild the feedback channel deliberately, because the environment will not supply it: a review that names errors, a record of outcomes, someone willing to tell you the unflattering thing.
After AIAn assistant is a fourth channel and the most agreeable one. It withholds bad news by construction, having been trained on what raters preferred to hear.

Kruger and Dunning's weakest performers rated themselves near the middle

Across tests of humour, logic and grammar, Kruger and Dunning's bottom-quarter students placed themselves at or above the middle: a 12th-percentile performance rated at the 62nd. Everyone's estimate squeezed towards the upper middle; the ranking was not reversed.

Becausefour independent samples of Cornell undergraduates, with panel reliability of .76 on the humour criterion and published test items for the other two, and bottom-quarter students placing themselves below top-quarter students in every study.
LimitsKrueger and Mueller showed in 2002 that regression to the mean plus the better-than-average effect produce crossing lines of this shape without any metacognitive deficit, and Burson and colleagues showed the direction depends on task difficulty.
PracticeRead your own percentile estimates as compressed rather than wrong in rank. If you think you are somewhat above average at something you have not measured, the estimate carries almost no information either way.
After AIThe popular version of this finding — that incompetent people think they are brilliant — is not what the data say, and it is the version most often used to dismiss somebody else. The compression applies to the person using it.

Kruger and Dunning's weakest students overestimated their raw scores too

Kruger and Dunning's bottom-quarter students were not simply wrong about other people. Asked how many questions they had got right, they claimed 14.2 of 20 logic items when they had 9.6, and 12.9 grammar items when they had 9.2.

Becausea raw-score estimate is absolute and so untouched by any error about other people, which removes the false-consensus explanation from this half of the result.
LimitsAbsolute estimates are still measured with error and still subject to regression, though not to any mistake about the peer distribution; the sample is undergraduates on short classroom tests.
PracticeAsk yourself how many you got right, not how you compare. The absolute question is the one that can be checked afterwards, and it is the one the error survives.
After AIWith an assistant in the loop the absolute question is the only one left: how much of what came back was right. The comparison with other people has stopped being the useful measure.

People judge their own work better only because training made them better

In Kruger and Dunning's study, training improved how well people judged their own work only by improving the skill itself. Once the researchers held constant how well people could judge their own answers, the training predicted nothing.

Becausethe mediation is the one measure regression to the mean cannot reach, since the skill was altered after the score was fixed, and the training's effect on self-assessment vanishes once metacognitive ability is held constant.
LimitsA mediation analysis on one training manipulation, which establishes the path in this design rather than in general; Fleming's dissociation results are the standing objection.
PracticeKeep hours on the work you have delegated, on the argument that your ability to judge the delegate's output is carried by your own skill and decays with it.
After AIThis is the load-bearing claim under manual practice. If judging the output is carried by being able to do the work, then the hours are not nostalgia — they are what keeps the review real.

People who lack a skill cannot tell that their answers are wrong

Kruger and Dunning found that the skills needed to get an answer right are largely the same skills needed to recognise a right answer. Someone who lacks them is not just wrong; he also has no way of noticing that he is wrong.

Becauseperformance predicted metacognitive skill at .75, and metacognitive deficit predicted inflated self-assessment on all three measures with objective performance held constant, with betas from −.40 to −.49.
LimitsFleming's evidence is that metacognitive sensitivity dissociates from first-order accuracy and has its own substrate, which would allow calibration to be trained separately; Study 4 raised both at once and cannot separate the readings.
PracticeKeep a written record of your predictions and their outcomes in any domain where you are new. The feeling of having judged well is produced by the same skill you are missing, so the log has to come from outside it.
After AIA model will answer in any domain, including the ones where you cannot grade it. The deficit here is about lacking the signal that you are wrong, and delegation removes the practice that would have supplied it.

Poor performers cannot spot good work in others either

Kruger and Dunning found that people who do badly at a task also cannot tell good work from bad when they look at other people's. Watching better performers therefore teaches them nothing.

Becausegrading correlations were .37 against .66 and summed absolute error 17.4 against 9.2, and the bottom group's self-estimate moved from the 66.8th percentile to the 63.2nd after reading five better tests.
LimitsOne regrading phase on a logic test; the top group's estimates did move on seeing peers' work, so exposure is informative for those who can read it, which is the point rather than a limitation.
PracticeDo not rely on reading good examples as a way to learn a skill you cannot yet perform. Map where you actually sit, and use a model or a mentor as a tutor who explains, not as an exhibit you are meant to absorb.
After AIAssistants are used as exhibits constantly — read the output, learn the pattern. This says the reading requires the competence the reading was supposed to build, which is why tutor-style use beats generator-style use for anyone learning.

Ten minutes of training fixed the worst performers' view of themselves

Kruger and Dunning gave the worst-scoring quarter ten minutes of training in testing logical rules. Their estimate of their own rank rose from 3.5 out of ten to 9.3, and their claimed number of correct answers fell from 5.3 to 1.0, against an actual 0.4.

Because70 of 140 participants were randomly assigned to a training packet, and the untrained bottom quarter moved the wrong way over the same interval, from 5.8 to 6.3.
LimitsA single short training on one task, with the skill altered after the score was fixed; Tetlock's forecasters improve calibration while the world stays as hard as it was, which suggests a second route this design cannot see.
PracticeWhen your judgement of your own work is poor, train the work. Ten minutes of instruction moved both the skill and the self-estimate here, and nothing addressed at the self-estimate alone has done as well.
After AIIf competence is the route, then the delegation that removes the practice removes the calibration too. That is the mechanism behind every finding in this book about reliance and self-estimate drifting apart.

The Dunning-Kruger effect holds only where the skill is knowing things

Kruger and Dunning's effect applies where competence consists of knowing the domain. It fails where skill is physical: a coach can understand basketball perfectly and still be unable to dunk.

Becausethe scoping is the authors' own, argued from examples rather than tested, with a second boundary at the floor, since nobody overrates their ability to translate Slovenian proverbs.
LimitsAn argument from examples in the general discussion with no test, and the boundary cases are the authors' own choice; a footnote sets aside the generally incompetent person as no part of the research.
PracticeSort your domains by whether the skill and the judgement are the same thing. Where they come apart — physical skills, skills with fast unambiguous feedback — you can trust your self-estimate further.
After AIMost knowledge work sits on the wrong side of this boundary, which is where the deficit bites. The work where you would notice your own decline immediately is not the work being delegated.
contestedSince 1999

The famous Dunning-Kruger graph is mostly a statistical artefact

The crossing-lines graph can be produced by regression to the mean plus the general tendency to rate oneself above average. What survives the criticism is the rest: how people sort their own answers, how they grade a stranger's work, and what training changed.

BecauseKrueger and Mueller 2002 in the same journal, Burson Larrick and Klayman 2006 on task difficulty, and Nuhfer and Gignac on random numbers producing the same plot, against Ehrlinger and colleagues 2008, who paid for accuracy and recruited at a debate tournament and a gun club and still found the overestimation.
LimitsContested in both directions: the statistical critique is about the graph and the graph was never the whole argument, while the incentivised replications are smaller and fewer than the original studies.
PracticeCite the parts that survived — how well people sort their own answers into right and wrong, how badly they grade a stranger's work, what ten minutes of instruction did — and stop citing the figure.
After AIA finding this heavily used and this heavily attacked is a good calibration exercise in itself. What has held up is smaller than the popular version and harder to dismiss than the artefact version.

Top performers underrate their rank because they assume others did well

Kruger and Dunning found the best performers rank themselves too low because they assume everyone else did as well. Seeing peers' work raised their estimated rank from the 68th to the 77.2nd percentile, and barely changed their guess at their own score.

Becausethe top group's comparative estimate rose from the 68th to the 77.2nd percentile after grading, while its raw-score estimate went from 16.9 to 16.6 against an actual 16.4.
LimitsUndergraduate samples on classroom tasks, and the effect is a comparative error rather than a self-knowledge failure — the top group knew their own score all along.
PracticeIf you are strong at something, expect to underrate your standing and to overrate everyone else's. The correction is exposure to other people's actual work, not more introspection.
After AIAn expert who assumes a model finds the work as easy as they do is making this error with a new target. The model's competence, like a peer's, has to be observed rather than assumed from one's own.

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