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How do democratic societies establish and maintain order in ways that are conducive to growth? Contemporary scholarship associates order, democracy, and growth with centralized rule of law institutions. In this article, we test the robustness of modern assumptions by turning to the case of ancient Athens. Democratic Athens was remarkably stable and prosperous, but the ancient city-state never developed extensively centralized rule of law institutions. Drawing on the "what-islaw" account of legal order elaborated by Hadfield and Weingast (2012),we show that Athens' legal order relied on institutions that achieved common knowledge and incentive compatibility for enforcers in a largely decentralized system of coercion. Our approach provides fresh insights into how robust legal orders may be built in countries where centralized rule of law institutions have failed to take root.

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Errors and biases are earning algorithms increasingly malignant reputations in society. A central challenge is that algorithms must bridge the gap between high-level policy and on-the-ground decisions, making inferences in novel situations where the policy or training data do not readily apply. In this paper, we draw on the theory of street-level bureaucracies, how human bureaucrats such as police and judges interpret policy to make on-the-ground decisions. We present by analogy a theory of street-level algorithms, the algorithms that bridge the gaps between policy and decisions about people in a socio-technical system. We argue that unlike street-level bureaucrats, who re exively re ne their decision criteria as they reason through a novel situation, street-level algorithms at best re ne their criteria only after the decision is made. This loop-and-a-half delay results in illogical decisions when handling new or extenuating circumstances. This theory suggests designs for street-level algorithms that draw on historical design patterns for streetlevel bureaucracies, including mechanisms for self-policing and recourse in the case of error.

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