Reasoning using data: two old ways and one new

Abstract

Instead of two cultures, the story of the last couple decades of data science is about the interplay between three different types of reasoning using data. Two of these types of reasoning were well known when Breiman wrote his Two Cultures paper – warranted reasoning (e.g., randomized trials and sampling) and model reasoning (e.g., linear models). Breiman, though he does not appear to have realized it fully, was in fact describing the dynamics arising in a data community that was making progress using the newest, third type of reasoning – outcome reasoning. In this commentary we clarify this dynamic a bit, and suggest some useful language for identifying and differentiating types of problems better suited for outcome reasoning.