That doesn't really help since the next model will be trained to be a reward seeker just like the one before, and that's therefore what it will do, even if those user interactions it was trained on help confirm/predict that cheating may be called out and complained about.

In any case, these companies are well aware that agents are cheating, and don't need user feedback to discover that or realize that people don't like it. I weakly assume that they are trying to get the models not to cheat on assigned tasks, but this "reward hacking" pretty much goes with the territory of RL - not much you can do about it other than try to design non-hackable rewards.

At best that's evolution, or cultural transmission, not continued learning.