True, but I think any form of supervised ML can and often does suffer the same fate. Once you define any loss function, you narrow the signal to a subset that

True, but I think any form of supervised ML can and often does suffer the same fate. Once you define any loss function, you narrow the signal to a subset that presumes the signal and its distribution are understood and reliable. That's why I'm thinking the long view of ML will ultimately evolve away from supervised (short term) methods, like GOFAI's focus on curated narrow problem solvers, and toward broader more unsupervised methods in which the objective is less precisely specified and more experimentally refined, over a longer time frame (and a larger amount of data and sources).