I disagree. Dunning Kruger is not a statement about predicted score correlating with actual score in some way. It states that predicted score does not correlate well with actual score. This can be rephrased as the prediction error having a negative correlation with the actual score. The article then claims that this negative correlation is autocorrelation. That is true but the correlation still exist. The thing is that ideally we EXPECT there to be no correlation of the prediction error with the actual score, but we find autocorrelation. Going back to variables where this autocorrelation is not there, we EXPECTED to find a 1:1 positive correlation between predicted score and actual score but find no correlation, or a weak correlation.
So finding autocorrelation when you expected to find no correlation is pretty much the Dunning-Kruger effect here.
In fact their example with the random data totally makes sense: Suppose people uniformly randomly estimate their performance. Then the people who are low skilled will consistently over-estimate and the people who are high-skilled will consistently underestimate. Of course there is no causation here, as the people choose randomly, but there is an undeniable correlation. I guess the question is if you view the Dunning-Kruger effect as a claim to low skill CAUSING positive prediction error, or just correlating with it.
So finding autocorrelation when you expected to find no correlation is pretty much the Dunning-Kruger effect here.
In fact their example with the random data totally makes sense: Suppose people uniformly randomly estimate their performance. Then the people who are low skilled will consistently over-estimate and the people who are high-skilled will consistently underestimate. Of course there is no causation here, as the people choose randomly, but there is an undeniable correlation. I guess the question is if you view the Dunning-Kruger effect as a claim to low skill CAUSING positive prediction error, or just correlating with it.