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Algorithmic sentencing and the bias in the code

Crime, courts & justice

Algorithmic sentencing and the bias in the code

11 min

Courts increasingly use risk-assessment software to inform bail, sentencing, and parole. Explore how these tools work, the evidence of built-in bias, and the debate over letting algorithms shape justice.

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Show notes

Black defendants are twice as likely as white defendants to be misclassified as high risk by sentencing software.

Proprietary trade secrets prevent lawyers from cross-examining the algorithms used to determine a defendant's future risk.

Sentencing algorithms use residential stability and parental incarceration as proxies for criminal risk.

The COMPAS algorithm correctly predicts violent re-offending only twenty percent of the time.

Judges often suffer from automation bias, favoring numerical scores over their own observations of a defendant.

Four out of five people flagged as violent threats by the software do not actually commit violent crimes.

In this episode

  1. 1Intro1 min
  2. 2The Rise of the Risk Score2 min
  3. 3The ProPublica Investigation and the Bias Problem3 min
  4. 4The Black Box and Proprietary Justice3 min
  5. 5Human-AI Interaction in the Courtroom2 min
  6. 6Outro1 min

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Algorithmic sentencing and the bias in the code — Fylom