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How do people respond to the predictions made by pretrial risk assessments? My new paper (coauthored with Yiling Chen @hseas and forthcoming at #FAT2019) finds evidence for inaccurate and biased responses.
Available here: scholar.harvard.edu/files/19-fat.p…
+ tweet thread summary below:
Available here: scholar.harvard.edu/files/19-fat.p…
+ tweet thread summary below:
Research into fair machine learning fails to capture an essential aspect of how risk assessments impact the criminal justice system: their influence on judges. Considerations of risk assessments must be informed by rigorous studies of how judges actually interpret and use them.
So we ran experiments on Mechanical Turk to explore these human-algorithm interactions.
🚨 Caveat: our results are based on Turk workers, not judges. But they highlight interactions that should be studied further before risk assessments can be responsibly deployed. 🚨
🚨 Caveat: our results are based on Turk workers, not judges. But they highlight interactions that should be studied further before risk assessments can be responsibly deployed. 🚨
