Epstein (Simple rules for a complex world, Harvard University Press, Cambridge, 1995) defended the superiority of simple legal rules over complex, human-designed regulations. Has Epstein's case for simple rules become obsolete with the arrival of artificial intelligence, and in particular machine learning (ML)? Can ML deliver better algorithmic rules than traditional simple legal rules? This paper argues that the answer to these question is "no" by building an argument based on three increasingly more serious barriers that ML faces to develop legal (or quasi-legal) algorithmic rules: data availability, the Lucas' critique, and incentive compatibility in eliciting information. Thus, the case for simple legal rules is still sound even in a world with ML.