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Working Paper
The Hidden Effects of Algorithmic Recommendations
Algorithms are intended to improve human decisions with data-driven predictions. However, algorithms provide more than just predictions to decision-makers—they often provide explicit recommendations. In this paper, I demonstrate these algorithmic recommendations have significant independent effects on human decisions. I leverage a natural experiment in which algorithmic recommendations were given to bail judges in some cases but not others. Lenient recommendations increased lenient bail decisions by 40% for marginal cases. The results are consistent with algorithmic recommendations making ...