Its already speeding up human decision processes, and while ethics / alignment may seem unique to humans we also see normative expressions in monkeys or apes (like the experiment where one is given a grapes, the other cucumber).
A lot of ethics is based on symmetry: symmetric relations, equal rights, equal voting power, ... symmetries sound rather mathematical if you ask me, and decision structures have historically been pressed towards democracy (or at least depiction of it). One could say that modeling humanity as an empire with a king, ignores the will of sometimes hungry farmers with pitchforks. To prevent the occasional "implicit democracy" (royaltycide), it turned out in the interest of the king to recognize the powers of those farmers, and to formalize it in the decision making process. Or at least pretend to.
I believe machines will be able predict the preference sentient creatures would prefer in terms of decision structures, but I don't believe it will be able to predict (without human exposition) those novel preferences that stem not from sentience but from being specifically human properties (i.e. irritants which are quasi universal for humans, etc.), some of them humans know how to make predictions for (we can run expensive simulations modeling what happens when protein X is exposed to substance Y, and then make heuristic predictions of the effect on a full human in a realistic environment). So at a fundamental level I agree: machine learning models are not guaranteed to help much in predictions concerning entirely unexplored territory, neither by humans nor by natural selection. But it will definitely be capable of replacing the average human job, which doesn't involve consensual exploration outside of the homeostasis required in the implicit job description, that seems entirely automatable, regardless if its physics, mathematics, (harder than computer science), let alone programming.
It won't be able to magically systematically correctly predict out of distribution datapoints, it could only explore it like humans could by trial and error.
Its already speeding up human decision processes, and while ethics / alignment may seem unique to humans we also see normative expressions in monkeys or apes (like the experiment where one is given a grapes, the other cucumber).
A lot of ethics is based on symmetry: symmetric relations, equal rights, equal voting power, ... symmetries sound rather mathematical if you ask me, and decision structures have historically been pressed towards democracy (or at least depiction of it). One could say that modeling humanity as an empire with a king, ignores the will of sometimes hungry farmers with pitchforks. To prevent the occasional "implicit democracy" (royaltycide), it turned out in the interest of the king to recognize the powers of those farmers, and to formalize it in the decision making process. Or at least pretend to.
I believe machines will be able predict the preference sentient creatures would prefer in terms of decision structures, but I don't believe it will be able to predict (without human exposition) those novel preferences that stem not from sentience but from being specifically human properties (i.e. irritants which are quasi universal for humans, etc.), some of them humans know how to make predictions for (we can run expensive simulations modeling what happens when protein X is exposed to substance Y, and then make heuristic predictions of the effect on a full human in a realistic environment). So at a fundamental level I agree: machine learning models are not guaranteed to help much in predictions concerning entirely unexplored territory, neither by humans nor by natural selection. But it will definitely be capable of replacing the average human job, which doesn't involve consensual exploration outside of the homeostasis required in the implicit job description, that seems entirely automatable, regardless if its physics, mathematics, (harder than computer science), let alone programming.
It won't be able to magically systematically correctly predict out of distribution datapoints, it could only explore it like humans could by trial and error.