@blterrible @audioflyer79 @alisynthesis @davidaugust True. I apologize in advance for the personification, but it does seem to make some concepts easier for me. In robotics, the "user" is shorthand for any agent that initiates a task. (I'll spare you the technical discussion about whether users are the same as operators.) "Users" as agents can be known knowns (represented), unknown knowns (the concept of a user agent is encoded without being linked to specific data or goals), known unknowns (there is an interaction with something during the task, but the robot doesn't associate it with the concept of "user"), and unknown unknowns (the robot has not been given the concept of a "user" and the concept is irrelevant to its operation). In this case, there are at least two factors feeding into an LLMs response: the model is trained to provide the kind of answer it sees most often, but is also constrained to provide the kind of answer the designers have decided is what most people expect to see. Depending on how the constraints and interface layers are designed, the system could be in any of these states. So while the internal trained model generating the words may not be aware, I think it's hard to argue definitively that the system the user is interacting with is unaware of the concept of a user.