This isn't training a model by giving something input data. Entire neural networks we do not understand are formed through an attempt at creating an artificial natural selection.

If your process isn't going to be similar to humans, you aren't going to produce something similar to humans. I honestly think that's dangerous in and of itself, you're creating something that might have a brain network that is fundamentally at odds with coexistence with humanity.

But you're able to designate what its goals are completely arbitrarily. It doesn't need to think like a human -- there are humans who have been at odds with coexistence with humanity -- it needs to be constructed based on the value of human benefit, and you can seriously just tell it that. That isn't changed by it cogitating in a structurally different way, which it also almost certainly would be doing anyway because the way we do is highly adapted to early humanity, but is structurally deeply based on random incidents of mutation before then. Something could think very differently and nonetheless be just as capable of flourishing in those circumstances. This difference is compounded by the fact that you probably aren't going to actually produce an accurate simulation of an early human environment because you can't just make a functional simulation of macroscopic reality like that. Even imagining your method made sense, it would still ultimately need to fall into aspects of what I'm saying about arbitrary stipulation because the model environment would be based on human heuristics.

But way more important than that is the part where you, again, can just tell it that human benefit based on human instructions is the primary goal and it will pursue that, handling things like energy acquisition and efficiency secondarily.