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If you ever took psych 101, it was immediately obvious it's mostly horse shit. Made up nonsense theory, with studies that have few participants and are done by people who don't know math.
It is both amazing and saddening to me how you can have such an arrogant view of a whole field with just taking a 101 course.
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My experience has been that this isn't limited to engineers. I'm sure most people here have had people from other departments tell them how they need to do their jobs in one way or another. For example, there are always at least a few people who you have to consult regularly because their tickets are always written how they perceive a problem should be solved rather than explaining the underlying problem to be solved…
I'd say celebrities and creatives in general are often big offenders here too. Lots of actors/athletes/musicians acting like being good at what they do means they're also qualified to talk about science and engineering. And a lot of reviewers, documentary creators and specialist writers that decide to wade into discussions about topics they have no knowledge of/cover something they're new to, only to look ridiculousl…
A similar argument was made a couple of years ago, here's the rebuttal of the argument from back then [2022]: https://andersource.dev/2022/04/19/dk-autocorrelation.html
The fact that given X and Y random and independent, that Y-X is correlated with X doesn't disprove the Dunning Kruger. It in fact proves that Y = 1 X is a poor predictor, and the true model is Y = 0 X. In other words, perceived ability (of the human) cannot predict the actual test scores. Which is exactly what DK claims, but to a very extreme effect.
Note that, if there is actual signal (plus noise), e.g., if Y = X + eps; so the actual score is exactly the perceived score plus some added variation, the (Y-X)~X will be uncorrelated. In such case, there will be no DK effect, because the users are good at predicting their actual test scores, plus some constant variation.
The key claim: "Random data actually mimics the effect really well." This makes some sense. If people are asked to guess a number between 1 and 6 and then roll a die, the people who roll low are more likely to overestimate and the people who roll high are more likely to underestimate. But the key is precisely how well random data mimics the effect.
No, the argument is that the best person cannot overestimate his own rank, and the worst person cannot underestimate it. The better you are the less room there is for you to overestimate your skill, second place can at most be off by one etc. This effect would disappear almost completely if they instead of estimating their rank they estimated their score, since then unless the test is so easy the best scores perfectl…
In the article, in the section "The effect is in the noise", just before the graphs, it says they estimated their score. Where did you get that they estimated their rank?
Replication crisis. More than half of all psychology studies are not reproducible. I'm at the point honestly, where I don't even consider psychology to be a science anymore.
Simply: Anytime anyone overestimates their ability, they will perform worse than if they had approached it with humility (on average).
Rather than speaking it like people “have Dunning Kruger”
Just a fact (heuristic) of behavior that anyone can fall subject to
as for the arrogant people - of course they do exist, but it does not really warrant an "effect" of its own name, especially that most of us know in one way or the other why estimations fail and how it happens too
It’s obviously real, at least as used in conversation, whether it meets some rigorous definition I’m sure there’s an out, but we’ve all known these people. With vibe coding they’re everywhere. Is this going to be a modern “begging the question” where everyone knows what you mean but someone pipes up that actually the technical meaning is different?
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This then boils down to people being generally bad at estimating their own level of ability.
Which is exactly what the Dunner-Kruger effect is . Knowledgeable people statistically underestimating their knowledge and non-knowledgeable people overestimating their knowledge.