Human Decisions and Machine Predictions
Cornell University · Stanford University · +4 more institutions
Abstract
Abstract Can machine learning improve human decision making? Bail decisions provide a good test case. Millions of times each year, judges make jail-or-release decisions that hinge on a prediction of what a defendant would do if released. The concreteness of the prediction task combined with the volume of data available makes this a promising machine-learning application. Yet comparing the algorithm to judges proves complicated. First, the available data are generated by prior judge decisions. We only observe crime outcomes for released defendants, not for those judges detained. This makes it hard to evaluate counterfactual decision rules based on algorithmic predictions. Second, judges may have a broader set…
Citation impact
- FWCI
- 280.14
- Percentile
- 100%
- References
- 64
Authors
5Topics & keywords
- Counterfactual thinking
- Counterfactual conditional
- Concreteness
- Computer science
- Stochastic game
- Set (abstract data type)
- Machine learning
- Artificial intelligence
- Peace, Justice and strong institutions