De-emphasizing the understanding of causal mechanisms and
abstract relationships may come at a cost: many major steps forward in science involve the
ability to leverage an understanding of “big picture” theoretical structure to make sense of, of
recognize the implications of, smaller discoveries. For example, it is easy to imagine a deep
learning system trained on a large amount of x-ray diffraction data quickly “discovering” the
double helix structure of DNA at very low marginal cost, but it would likely require human
judgment and insight about a much broader biological context to notice that the proposed
structure suggests a direct mechanism for heredity.
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