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This is an expected consequence of using ML to detect AI. LLMs are more well-read than the average person, so they'll have a bigger vocabulary than the average
by logicchains 2y ago
This is an expected consequence of using ML to detect AI. LLMs are more well-read than the average person, so they'll have a bigger vocabulary than the average person, so the ML model will learn to associate a bigger vocabulary with a higher probability of being AI. Which unfairly penalises well-read humans, who also have a bigger vocabulary than average.
Personally I think the whole endeavour is a waste of energy. Unless there's a massive civilisational collapse, humans will always have LLMs as writing aides, so trying to teach them to write without one is teaching them a skill they'll never need to use.
If you want to teach them to reason on the spot, then go back to requiring them to orally put forth and defend an idea.
- rootusrootus 2y ago> If you want to teach them to reason on the spot, then go back to requiring them to orally put forth and defend an idea. I have been thinking for the last couple years that we may end up in that spot. It is more labor intensive, and perhaps a little more susceptible to bias, but pretty hard to fake. At the end of the term, each student has half an hour with the professor (or a TA) where they discuss the content of the class. It should be quickly apparent who knows the material well enough and who skipped too many lectures.