Factoring (Possible) Effect of Dunning-Kruger.

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In summary, the Dunning Kruger effect likely affects the level of perceived error. Without empirical data to back this up, it is difficult to make an accurate estimate of error.
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WWGD
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Hi All, I am looking at some data regarding correlation between control measures and (perceived)errors at
a given position. The level of error seems , intuitively, suspiciously low. I suspect the low perceived error may
be at least partially explained by the Dunning Kruger effect:
https://en.wikipedia.org/wiki/Dunning–Kruger_effect

Does anyone know of anyway of factoring the effects of Dunning-Kruger to come up with a more realistic
expectation of error given control? We have a measure of Control from 0-5, same scale for error(both scales are linear; control goes from high to low, error goes from low to high: control near 5 is high, error near 5 is low) . Say a an input of control is 1 , a low measure, and the perceived error at that level is 4. Can I make a more accurate estimate of error by factoring out effects of Dunning-Kruger?
Thanks.
 
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WWGD said:
Hi All, I am looking at some data regarding correlation between control measures and (perceived)errors at
a given position. The level of error seems , intuitively, suspiciously low.
Do you have data about the "actual" error as well as the perceived error?
 
  • #3
Without at least some comparison of actual and perceived error I don't see how you could do anything useful.

A more detailed description what exactly you have as data would be useful.
 
  • #4
Stephen Tashi said:
Do you have data about the "actual" error as well as the perceived error?

No, sorry, I was trying to estimate any possible error. I was wondering if there were ways to do this. I was wondering to what extent ( and if ) DK provided some means to do this. I have data about the perceived error and I was wondering if DK allowed to estimate the margin of under/evaluating or general mis-evaluation of error.
 
  • #5
Not without a study how strong the effect is in your particular setup - and including such a study in your particular setup is probably the only reliable way to estimate that. I guess you cannot say anything about actual errors, just something about perceived errors.
 

1. What is the Dunning-Kruger effect?

The Dunning-Kruger effect is a cognitive bias in which individuals with low levels of competence or expertise tend to overestimate their abilities. This can lead to inflated self-confidence and a lack of recognition of one's own limitations.

2. How does the Dunning-Kruger effect impact decision making?

The Dunning-Kruger effect can lead to poor decision making, as individuals with low levels of competence may make decisions based on their overconfidence rather than actual knowledge or skills. This can also lead to a lack of willingness to seek out and consider alternative perspectives or information.

3. Are there any factors that can increase the likelihood of the Dunning-Kruger effect?

Yes, there are certain factors that can make individuals more susceptible to the Dunning-Kruger effect, such as lack of experience or knowledge in a particular subject, a desire to appear competent, and a lack of self-awareness. Additionally, certain personality traits, such as narcissism, can also contribute to the effect.

4. Can the Dunning-Kruger effect be overcome?

While it may be difficult to completely overcome the Dunning-Kruger effect, there are steps that can be taken to mitigate its impact. These include seeking out feedback and advice from others, being open to new information and perspectives, and continuously learning and improving in areas of weakness.

5. How does the Dunning-Kruger effect relate to factoring in scientific research?

The Dunning-Kruger effect can have a significant impact on the quality and validity of scientific research. Scientists who are overly confident in their abilities may overlook important information or make flawed conclusions, leading to inaccurate or unreliable results. It is important for scientists to be aware of the Dunning-Kruger effect and take steps to minimize its influence in their research.

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