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In other words people are quite bad at estimating their skill level. Some people will overestimate, while some other people will underestimate and on average th

In other words people are quite bad at estimating their skill level. Some people will overestimate, while some other people will underestimate and on average there will be a relatively constant estimated skill level that doesn't change all that much based on the actual abilities. Given that fact, it logically follows that people who score low ability tests will more often than not have overestimated their ability (and the same on the other end of the spectrum). You can frame this effect as autocorrelation if you wish or just as a logical consequence. But that's missing the point. The point is: why on earth are humans so bad at estimating their own competence level as to make it practically indistinguishable from random guesses.

kizer 5y ago
That’s what I was thinking; if the average is about constant all you’ve shown is that everyone is bad at self-assessment (another issue - not fully qualifying a distribution by just using the average loses information). But a comment above quoting the more recent paper presents a contradictory conclusion: that humans can self-assess with some accuracy. So now I’m confused again.
- d0mine 5y ago
  You might have meant this comment https://news.ycombinator.com/item?id=31039901 https://news.ycombinator.com/item?id=31039901 (it says people can self-assess (no bias), more competent people do it better (less variance))
d0mine 5y ago
- what DK claims: there is bias (incompetent people overestimate their ability) - what data actually shows: there is a greater variance (incompetent people both over and _under_ estimate to a larger degree compared with more competent people. Data shows heteroscedasticity. No bias (estimations are around zero +/-, tighter for more competent).
- ithkuil 5y ago
  The data supports the claim because indeed it turns out that incompetent people overestimate their ability. This phenomenon exhibits itself with random data too, so it clearly doesn't mean that incompetent people overestimate their ability because of their incompetence. Or is it? The trick lies in the fact that when asked to judge your competence you're given a range (e.g. 0-10) and both competent people and incompetent people have access to the whole range when taking a self-assessment. I.e. if less competent people were on average more aware of their incompetence they may be less likely to rate themselves 5 or 6, but yet the data shows that no matter what competence level you have on average you self-assess more or less the same. This seems to imply that your incompetence indeed doesn't allow you to truly appreciate the full range of skills that are required to reach a higher level of competence. In other words, the DK effect itself is the cause of the random distribution of the skill self-assessment (which in turn is the cause of the overestimation secondary effect)

kizer 5y ago

That’s what I was thinking; if the average is about constant all you’ve shown is that everyone is bad at self-assessment (another issue - not fully qualifying a distribution by just using the average loses information). But a comment above quoting the more recent paper presents a contradictory conclusion: that humans can self-assess with some accuracy. So now I’m confused again.

d0mine 5y ago
You might have meant this comment https://news.ycombinator.com/item?id=31039901 https://news.ycombinator.com/item?id=31039901 (it says people can self-assess (no bias), more competent people do it better (less variance))

d0mine 5y ago

- what DK claims: there is bias (incompetent people overestimate their ability) - what data actually shows: there is a greater variance (incompetent people both over and _under_ estimate to a larger degree compared with more competent people. Data shows heteroscedasticity. No bias (estimations are around zero +/-, tighter for more competent).

ithkuil 5y ago
The data supports the claim because indeed it turns out that incompetent people overestimate their ability. This phenomenon exhibits itself with random data too, so it clearly doesn't mean that incompetent people overestimate their ability because of their incompetence. Or is it? The trick lies in the fact that when asked to judge your competence you're given a range (e.g. 0-10) and both competent people and incompetent people have access to the whole range when taking a self-assessment. I.e. if less competent people were on average more aware of their incompetence they may be less likely to rate themselves 5 or 6, but yet the data shows that no matter what competence level you have on average you self-assess more or less the same. This seems to imply that your incompetence indeed doesn't allow you to truly appreciate the full range of skills that are required to reach a higher level of competence. In other words, the DK effect itself is the cause of the random distribution of the skill self-assessment (which in turn is the cause of the overestimation secondary effect)