Have you heard of the ‘Dunning-Kruger effect’? It’s the (apparent) tendency for unskilled people to overestimate their competence. Discovered in 1999 by psychologists Justin Kruger and David Dunning, the effect has since become famous.

Except there’s a problem.

The Dunning-Kruger effect also emerges from data in which it shouldn’t. For instance, if you carefully craft random data so that it does not contain a Dunning-Kruger effect, you will still find the effect. The reason turns out to be embarrassingly simple: the Dunning-Kruger effect has nothing to do with human psychology.1 It is a statistical artifact — a stunning example of autocorrelation.

EDIT: see response from dustyData and the article they linked to https://www.bps.org.uk/psychologist/dunning-kruger-effect-and-its-discontents

  • Wogi@lemmy.world
    link
    fedilink
    English
    arrow-up
    5
    arrow-down
    9
    ·
    8 months ago

    Multiple researchers have debunked the effect, and they managed to recreate the results with completely random data. Meaning the effect being described doesn’t actually exist. They would have produced the same results regardless of the information they plugged in.

    • i_love_FFT
      link
      fedilink
      English
      arrow-up
      7
      arrow-down
      3
      ·
      8 months ago

      Recreating the results with completely random data is a proof of the DK effect!

      It means that there is no link between ability and perceived ability, so people without ability will overestimate while people with ability will underestimate.

      To refute the DK effect, we would need ability and perceived ability to be exactly the same.

      To me, this whole debate shows that some people without social science background think they understand social science better that the actual experts… Quite ironic in my opinion!

    • swayevenly@lemm.ee
      link
      fedilink
      English
      arrow-up
      2
      arrow-down
      2
      ·
      8 months ago

      Yup! The overall tone of the text comes of as arrogant and smug…

      I was writing a very long wall of text to explain how the authors comprehension of statistics is limited, but it doesn’t matter so much.

      I read the beginning of their response and I can’t tell if the rest was supposed to be a joke.