Smart people know enough about a topic to know that they don’t know everything. Whereas less smart people don’t know what they don’t know so they think they know it all.
IIRC, Dunning-Kruger refers to the specific phenomenon where an expert in a subject underestimates the depth of their own expertise and think that the things they know are more commonly known.
For instance, I’m working in data analytics. If I vent my frustration that the data model I’m supposed to build is bullshit, because a dimension key composed of several attributes is formatted differently in two different fact tables, but I need to conform it to cross-reference between the two and it’s a mess to untangle, you’d probably agree on the “mess” part, but might not understand a whole lot of the rest unless you’re familiar with the field. I’d intuitively assume that “conform it” would need some explanation, because that’s a slighly more complex term than the rest, but experience has taught me that most people would have trouble following at “data model” already.
Simulation theory is just Plato’s cave…
“If a tree falls…” is Schrodinger’s cat…
We’re still talking about the same stuff, we’re just focused on details and aware that we might not yet be working with complete data.
The absolute smartest brains in the planet readily admit they don’t know what the fuck is going on. That’s a good thing.
We shouldn’t be listening to anyone that insists they have all the answers because no one does.
And to our detriment, the idiots are quite certain that they know everything.
It’s Dunning-Kruger.
Smart people know enough about a topic to know that they don’t know everything. Whereas less smart people don’t know what they don’t know so they think they know it all.
That’s a lot pf knows.
IIRC, Dunning-Kruger refers to the specific phenomenon where an expert in a subject underestimates the depth of their own expertise and think that the things they know are more commonly known.
For instance, I’m working in data analytics. If I vent my frustration that the data model I’m supposed to build is bullshit, because a dimension key composed of several attributes is formatted differently in two different fact tables, but I need to conform it to cross-reference between the two and it’s a mess to untangle, you’d probably agree on the “mess” part, but might not understand a whole lot of the rest unless you’re familiar with the field. I’d intuitively assume that “conform it” would need some explanation, because that’s a slighly more complex term than the rest, but experience has taught me that most people would have trouble following at “data model” already.
He was convinced he had the answer