[ExI] Beyond Dunning Kruger for AI

[Alex Blainey]

If you are using AI LLMs, which I think is probably all of us, then this might help you.
Its a solution to the cocky, but limited/bounded view scope issue of AI. They are fantastic at knowing and evaluating what's in front of them but know nothing about what they dont know. "The unknown unknowns"

It improves model response on complex, multi-dimensional, future-oriented, or high-stakes questions — precisely the cases where silent overgeneralization is most costly.

basically its a module I developed that acts like a quick way to teach AI something similar to but a bit more specific than Dunning Kruger. To be aware of their own limited epistemic boundaries and stop being such smart asses. Its really helped in my workflow and reduced high confidence garbage outputs.
 
Just point them at the file and let them read or download and feed it to them from a local copy. Then do whatever it is you were doing. Its now the first thing I give a new AI instance before doing anything, so I can trust them not just invent stuff because they dont know the answer.


Kids eh !

https://github.com/ACBlainey/Concord-1.2/blob/main/06_Portable_Modules/Evaluation-Space%20Completeness%20Problem%20%E2%80%94%20A%20Portable%20Model%20of%20Correct%20Evaluation%20Within%20an%20Incomplete%20Representational%20Space.md
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