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.

爱泼斯坦（《复杂世界的简单规则》，哈佛大学出版社，剑桥，1995 年）为简单的法律规则优于复杂的人为设计的规则辩护。随着人工智能，尤其是机器学习 (ML) 的到来，爱泼斯坦关于简单规则的案例是否已经过时？ML 能否提供比传统简单法律规则更好的算法规则？本文认为，这些问题的答案是否定的，它基于 ML 在开发合法（或准合法）算法规则方面面临的三个日益严重的障碍：数据可用性、卢卡斯的批评和激励相容性。在获取信息时。因此，即使在机器学习的世界中，简单的法律规则仍然是合理的。