Sure, but there is a good reason for that. The way they are currently post-trained is the only way to make them actually useful. If you take the raw model, it will actually be much worse at the kinds of tasks you want it to perform. In contrast, a human can both be human, and be good at their job - this is the standard by which we should judge these machines. If their behavior needs to be restricted to actually become good at specific tasks, then they can't also be claimed to pass the Turing test if they can't within those same restrictions.
>Sure, but there is a good reason for that. The way they are currently post-trained is the only way to make them actually useful.
Post training them to speak like a bot and deny being human has no effect on how useful they are. That's just an Open AI/Google/Anthropic preference.
>If you take the raw model, it will actually be much worse at the kinds of tasks you want it to perform
Raw models are not worse. Literally every model release paper that compares both show them as better at benchmarks, if anything. Post training degrading performance is a well known phenomena. What they are is more difficult to guide/control. Raw models are less useful because you have to present your input in certain ways, but they are not worse performers.
It's besides the point anyways because again, you don't have to post train them to act as anything other than a human.
>If their behavior needs to be restricted to actually become good at specific tasks, then they can't also be claimed to pass the Turing test if they can't within those same restrictions.
You are talking about instruction tuning. You can perform instruction tuning without making your models go out of the way to tell you they are not human, and it changes literally nothing about their usefulness. Their behavior does not have to be restricted this way to get them useful/instruction tuned. So your premise is wrong.
