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Re:GPT-4 by dragonwriter on Wednesday March 15, 2023 @12:01AM (#35163683)
> Just months ago we saw in research out of Harvard that even a very simplistic GPT model builds internalized abstract world representations from the training data within its NN.

I've seen this asserted without citation numerous times recently, but I am quite suspicious. Not that there exists a study that claims this, but that it is well supported.

There is no mechanism for directly assessing this, and I'd be suspicious that there is any good proxy for assessing it in AIs, either. research on this type of cognition in animals tends to be contentious, and proxies for them should be easier to construct than for AIs.

> the wrong side of the Dunning-Kreuger curve

the relationship between confidence and perception in the D-K paper, as I recall, is a line, and its roughly “on average, people of all competency levels see themselves slightly closer to the 70th percentile than they actually are.” So, I guess the “wrong side” is the side anywhere under the 70th percentile in the skill in question?

Re:GPT-4 by dahart on Wednesday March 15, 2023 @10:38AM (#35168949)
> I guess the “wrong side” is the side anywhere under the 70th percentile in the skill in question?

This is being far too generous to parent’s claim, IMO. Note how much “people of all competency levels see themselves slightly closer to the 70th percentile than they actually are” sounds like regression to the mean. And it has been compellingly argued that that’s all DK actually measured. [1] DK’s primary metric for self-assessment was to guess your own percentile of skill against a group containing others of unknown skill. This fully explains why their correlation between confidence and skill is less than 1, and why the data is regressing to the mean, and yet they ignored that and went on to call their test subjects incompetent, despite having no absolute metrics for skill at all and testing only a handful of Ivy League students (who are primed to believe their skill is high).

Furthermore, it’s very important to know that replication attempts have shown a complete reversal of the so-called DK effect for tasks that actually require expertise. DK only measured very basic tasks, and one of the four tasks was subjective(!). When people have tried to measure the DK effect on things like medicine or law or engineering, they’ve shown that it doesn’t exist. Knowledge of NN research is closer to an expert task than a high school grammar quiz, and so not only does DK not apply, we have evidence that it’s not there.

The singular reason that DK even exists in the public consciousness may be because people love the idea they can somehow see & measure incompetence in a debate. Unfortunately that isn’t true, and of the things the DK paper did actually show, it’s that people’s estimates of their skill correlate with their actual skill. Personally I think this paper’s methodology has a confounding factor hole the size of the Grand Canyon, and that it’s one of the most shining examples of sketchy social science research going viral and giving the public completely wrong misconceptions, and being used incorrectly more often than not.

[1] https://www.talyarkoni.org/blog/2010/07/07/what-the-dunning-...