I agree my last point is more speculative. The question is whether vast amounts of pre-trained data + a smaller amount of finetuning by online RL substitutes for the human experience. Given the success of pre-training so far, I think it probably will.
Note that the modern understanding of causality in stats/analytic philosophy/Pearl took centuries of intellectual progress—even if it seems straightforward. Spurious causal inference seems ubiquitous among humans unless they have learned—by reading/explicit training—about the modern understanding. Your examples from human childhood (dropping stuff) seem most relevant to basic physics experiments and less to stochastic relationships between 3 or more variables.
I agree my last point is more speculative. The question is whether vast amounts of pre-trained data + a smaller amount of finetuning by online RL substitutes for the human experience. Given the success of pre-training so far, I think it probably will.
Note that the modern understanding of causality in stats/analytic philosophy/Pearl took centuries of intellectual progress—even if it seems straightforward. Spurious causal inference seems ubiquitous among humans unless they have learned—by reading/explicit training—about the modern understanding. Your examples from human childhood (dropping stuff) seem most relevant to basic physics experiments and less to stochastic relationships between 3 or more variables.