In the process of learning things we take in wrong information all the time. A lot of it is even intentionally wrong, in the sense of being simplified. These are rarely large obstacles to true understanding. Sometimes they're even beneficial, as correcting prior beliefs can drive home the more accurate belief with greater force.
Not-quite-correct is a wordy misrepresentation when something is plainly incorrect.
In many fields being confidently wrong is how you get fucked over hard.
That ChatGPT will gleefully fabricate references like a schizophrenic is just more icing on this shit cake.
This isn't really not-quite-correct; it's egregiously wrong in the central aspect of the thesis. Refining and fixing it requires understanding that, and how, it's wrong--and if you have that level of knowledge, why are you using a tool to write this kind of thing? It's not going to save you much time from actually writing the whole thing yourself.
If you tell it that a fact it has wrong is wrong, you can get it to change its answer.
Also, you can just make tweaks manually.
Seems super useful to me as long as you understand the limitations.
Trust it the right it amount - don't trust it too much, and you're golden.
Probably. So, don't use ChatGPT unsupervised to take tests.