Judges Now Rely On Secret AI Algorithms To Guide Their Sentencing of Criminal Defendants
Daily Kos, May 25, 2021. 'Sentenced By Algorithm.'
Imagine for a moment that you’ve been convicted of a crime, and are awaiting sentencing. The prosecutor hands a computer-generated analysis to the judge that declares, based on a secret analysis performed by a complex algorithm, that you should receive the harshest possible sentence, since according to the algorithm you are highly likely to commit future crimes.
Your attorney, hoping to rebut this conclusion, asks how the report was prepared, but the judge rules that neither you nor your attorney are entitled to know anything about its preparation, only the results. The judge then proceeds to impose the maximum sentence, based on this secret calculation.
If that sounds like something out of a dystopian science fiction novel, well, it’s going on right now in several states throughout this country.
Jed Rakoff is a federal district judge for the Southern District of New York. A former federal prosecutor appointed to the bench in 1996, Rakoff has presided over the some of the most significant white-collar crime cases in this country. He is generally recognized as one of the leading authorities on securities and criminal law, and as a regular contributor to the New York Review of Books, he often writes about novel and emergent criminal justice issues. His latest essay addresses the increasingly widespread use by criminal prosecutors of artificial-intelligence-based (AI) computer programs or algorithms to support sentencing recommendations for convicted criminal defendants.
These programs, using a variety of controversial sociological theories and methods, are primarily used to assess recidivism (the propensity of a defendant to commit future crimes) and they are often given heavy weight by judges in determining the length of the sentence to be imposed. They also factor in decisions regarding setting bail or bond limits. The consideration of potential recidivism is based on the theory of “incapacitation:” the idea that criminal sentencing should serve the dual purpose of punishment as well as preventing a defendant from committing future crimes, in order to protect society.
Rakoff finds the use of these predictive algorithms troubling for a number of reasons, not the least of which are their demonstrated error rates and propensity for inherent racial bias. He notes that the theories on which they purportedly analyze a person’s propensity to commit future crimes are often untested, unreliable, and otherwise questionable.
However, his most recent essay for the NYRB, titled “Sentenced by Algorithm” and reviewing former district judge Kathleen Forrest’s, When Machines Can Be Judge, Jury, and Executioner, implicates even more disturbing questions raised by the introduction of artificial intelligence technology into our criminal justice system.
Is it fair for a judge to increase a defendant’s prison time on the basis of an algorithmic score that predicts the likelihood that he will commit future crimes? Many states now say yes, even when the algorithms they use for this purpose have a high error rate, a secret design, and a demonstrable racial bias...
More,
https://www.dailykos.com/stories/2021/5/25/2031872/-Judges-now-rely-on-secret-AI-algorithms-to-guide-their-sentencing-of-criminal-defendants
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