It didn't though, it just spat out what is basically a 1:1 copy of some Indiana Jones promo shoot. No where did the prompt ask for it to look like Harrison Ford.
If we were playing Charades, just about anyone would have guessed you were describing Indiana Jones.
If you gave a street artist the same prompt, you'd probably get something similar unless you specified something like "... but something different than Indiana Jones".
But if you look at it from the perspective that there is only one example to learn, from it is maybe not over it.
That's not overfitting. That's either just correct or underfitting (if we say it's never returning anything but 2)!
Overfitting is where the model matches the training data too closely and has inferred a complex relationship using too many variables where there is really just noise.
How can you express, in term of AI training, ignoring the existence of something that's widely present in your training data set? if you ask the same question to a 18yo girl in rural Thailand, would she draw Harrison Ford as Indiana Jones? Maybe not. Or maybe she would.
But IMO an AI model must be able to provide a more generic (unbiased?) answer when the prompt wasn't specific enough.
Maybe it would have some point if you are targetting users in a substantially different social context. In the case, you would design the model to be familiar with their tropes instead. So when they describe a character iconic in their culture, by a few distinguishing characteristics, it would produce that character for them. That's no different at all.