Isn’t exploration vs exploitation about the decision-making process, not about the actual reality in the world around you? It doesn’t matter if they are secretly identical or not. The exploration/exploitation trade-off is in the person making those decisions.
I don't understand what you suggest that implies?
I think they're saying that while it doesn't matter, the agent and human "do not actutally know" that it does not matter.
Philosophy sometimes says that knowledge is a "justified true belief"*; in this experiment, agents and humans have incorrectly justified a false belief that some applicants are better for certain roles.
* other times, it says this isn't good enough
Seems quite odd to cite all of philosophy as saying something, as if it were a single person with contradictory beliefs..
And then its like you are both saying the justification is incorrect and the belief is false, so its not really like the bare nuance of the concept is adding to the point. Why feel the need to appeal to an (imaginary) authority at all in this case?
"Oh well if philosophy said it, I better be taking this seriously!"
I think you misunderstood my point, just as the other commentor misunderstood one level up.
Perhaps a different approach to explain the problem here:
"It ain't what they don't know, it's what they know for sure that just ain't so".
Hm ok, but how are you mapping this, like, epistemological concept to what you are responding to re exploration/exploitation? Has exploration happened or not if it amounts to false beliefs? The whole point tradeoff doesn't seem to make sense if the person in fact can't actually successfully explore! Or even if there the possibility of that. But it is also very likely I am misunderstanding!
A flat distribution is still a distribution, and correct exploration would have revealed that the distribution is flat. The agent appears to have gained the false belief that it has learned something and done some exploring, when in fact it has not.
c.f. Sally-Anne test: Sally thinks she knows where her toy is, we know that she doesn't, and indeed couldn't. The LLM (and humans in similar conditions) think they know what the distribution is, we know that they don't.
Really not trying to be reductive here, but it feels like all you are trying to articulate here is that the LLM was wrong in this instance about something. Is that right? Is there something more we need to understand?
> Is there something more we need to understand?
Only if you're interested in the specific failure modes that LLMs have.
That's all this story is.