Algorithmic Risk Assessment in the Hands of Humans

By M. Stevenson, Jennifer L. Doleac. Social Science Research Network, 2019

144 citations recorded by the source corpus.

We evaluate the impacts of adopting algorithmic risk assessments in sentencing. We find that judges changed sentencing practices in response to the risk assessment, but that discretion played a large role in mediating its impact. Judges deviated from the recommendations associated with the algorithm in systematic ways, suggestive of alternative objectives. As a result, risk assessment did not lead to detectable gains in terms of public safety or reduced incarceration rates. Using simulations, we show that strict adherence to the sentencing recommendations associated with the algorithm would have had benefits (less incarceration) but also some costs (increased sentences for youth). (JEL D81, D91, H76, K41, K42)

Subfields: Artificial Intelligence, Health Informatics, Safety Research

View Paper: https://www.semanticscholar.org/paper/45c9fe3a693ee2ae08c16f902f2443265238e308

Citations in the corpus

• Economics, Fairness and Algorithmic Bias (2020, unknown): “A related set of papers studies the effect of human judgement-guided, rather than replaced, by algorithms.63 Stevenson (2017) examines how judges are influenced by algorithmic guidance in 63 Cowgill (2017) contains some additional results about human screeners’ willingness to defer to algorithms,…”