Tl;dr

AI alignment has a culture clash. On one side, the “technical-alignment-is-hard” / “rational agents” school-of-thought argues that we should expect future powerful AIs to be power-seeking ruthless consequentialists. On the other side, people observe that both humans and LLMs are obviously capable of behaving like, well, not that. The latter group accuses the former of head-in-the-clouds abstract theorizing gone off the rails, while the former accuses the latter of mindlessly assuming that the future will always be the same as the present, rather than trying to understand things. “Alas, the power-seeking ruthless consequentialist AIs are still coming,” sigh the former. “Just you wait.”

As it happens, I’m basically in that “alas, just you wait” camp, expecting ruthless future AIs. But my camp faces a real question: what exactly is it about human brains^[1] that allows them to not always act like power-seeking ruthless consequentialists? I find that existing explanations in the discourse—e.g. “ah but humans just aren’t smart and reflective enough”, or evolved modularity, or shard theory, etc.—to be wrong, handwavy, or otherwise unsatisfying.

So in this post, I offer my own explanation of why “agent foundations” toy models fail to describe humans, centering around a particular non-“behaviorist” RL reward function in human brains that I call Approval Reward, which plays an outsized role in human sociality, morality, and self-image. And then the alignment culture clash above amounts to the two camps having opposite predictions about whether future powerful AIs will have something like Approval Reward (like humans, and today’s LLMs), or not (like utility-maximizers).e