Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI '19
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
... ogy 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.