I think it's really important for people who lead with 'theory' and see it as a 'lens' to rethink their understanding of the scientific method in the era of data science. "In data science, you don't start with a hypothesis or prediction," Weber said. "You start with the data that already exists - maybe numbers someone collected years ago, or information gathered for a totally different purpose - and you work backward. You look for patterns, connections or surprises in the data, and those clues help you figure out what questions you should even be asking. So, instead of testing a hypothesis, you're discovering one." This article is based on a paywalled paper by Eric Weber, et al., though there's an archive version available (nor now) here.
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