I’ve been thinking of Case 2. It seems harder to establish “capable of distinguishing between situations where the user wants A vs B” on individual examples since a random classifier would let you cherrypick some cases where this seems possible without the model really understanding. Though you could talk about individual cases as examples of Case 2. Agree that there’s some implicit “all else being equal” condition, I’d expect currently it’s not too likely to change conclusions. Ideally you’d just have the category A=”best answer according to user” B=”all answers that are worse than the best answer according to the user” but I think it’s simpler to analyze more specific categories.
I’ve been thinking of Case 2. It seems harder to establish “capable of distinguishing between situations where the user wants A vs B” on individual examples since a random classifier would let you cherrypick some cases where this seems possible without the model really understanding. Though you could talk about individual cases as examples of Case 2. Agree that there’s some implicit “all else being equal” condition, I’d expect currently it’s not too likely to change conclusions. Ideally you’d just have the category A=”best answer according to user” B=”all answers that are worse than the best answer according to the user” but I think it’s simpler to analyze more specific categories.