I definitely agree with that. There has to be room to find traction. The concern is about things which specifically push the field toward “near-term” solutions, which slides too easily into not-solving-the-same-sorts-of-problems-at-all. I think a somewhat realistic outcome is that the field is taken over by standard machine learning research methodology of achieving high scores on test cases and benchmarks, to the exclusion of research like logical induction. This isn’t particularly realistic because logical induction is actually not far from the sorts of things done in theoretical machine learning. However, it points at the direction of my concern.
I definitely agree with that. There has to be room to find traction. The concern is about things which specifically push the field toward “near-term” solutions, which slides too easily into not-solving-the-same-sorts-of-problems-at-all. I think a somewhat realistic outcome is that the field is taken over by standard machine learning research methodology of achieving high scores on test cases and benchmarks, to the exclusion of research like logical induction. This isn’t particularly realistic because logical induction is actually not far from the sorts of things done in theoretical machine learning. However, it points at the direction of my concern.