This is an interesting podcast talking about a social application of data analytics to fix the bail system of New Jersey.
In New Jersey, defense attorneys, judges, and prosecutors got together to try to reform a system that treated poor defendants so differently from rich ones. In the end: they got rid of bail.
… The Risk Assessment Algorithm predicts the probability of failing to show up in courts and the probability of committing to another crime before the next trial in a 1-to-6 scale. It considers the following factors
- Does the person have a priori conviction of violance within the past x years?
- Have the person had failed to appear in courts in priori cases?
- The age of the person when the crime was committed, and others.
… Data shows that, if your age was under 23 when committing a crime, the person is more likely to commit a new crime than an older person.
… Some specific factors such as race and wealth are excluded in order to prevent bias, whereas keeping the forecast reliable.
… Since the introduction of the algorithm, people are detained with real information. The jail population is reduced by almost 30%. The result is very profound.
Reference: New Jersey Bails Out