Pramit Choudhary explores the usefulness of a generative approach that applies Bayesian inference to generate human-interpretable decision sets in the form of "if. . .and else" statements. These human interpretable decision lists with high posterior probabilities might be the right way to balance between model interpretability, performance, and computation.