GOVERNING BY ALGORITHM? NO NOISE AND (POTENTIALLY) LESS BIAS

As intuitive statisticians, human beings suffer from identifiable biases-cognitive and otherwise. Human beings can also be noisy in the sense that their judgments show unwanted variability. As a result, public institutions, including those that consist of administrative prosecutors and adjudicators, can be biased, noisy, or both. Both bias and noise produce errors. Algorithms eliminate noise, and that is important; to the extent that they do so, they prevent unequal treatment and reduce errors. In addition, algorithms do not use mental shortcuts; they rely on statistical predictors, which means that they can counteract or even eliminate cognitive biases. At the same time, the use of algorithms by administrative agencies raises many legitimate questions and doubts. Among other things, algorithms can encode or perpetuate discrimination, perhaps because their inputs are based on discrimination, or perhaps because what they are asked to predict is infected by discrimination. But if the goal is to eliminate discrimination, properly constructed algorithms nonetheless have a great deal of promise for administrative agencies.

Automated summary

As intuitive statisticians, humans are biased and noisy in their judgments. Algorithms can eliminate noise, reduce errors, prevent unequal treatment, and counter cognitive biases. However, the use of algorithms in administrative agencies raises legitimate questions and doubts, including concerns about encoding or perpetuating discrimination.