Machines In The Dock: Evaluating The Constitutional Legitimacy Of Algorithmic Decision-Making In Judicial Proceedings
- IJLLR Journal
- 2 hours ago
- 1 min read
Priyam Pratik, Faculty of Law, University of Allahabad
ABSTRACT
The growing use of data-driven tools in courts, tribunals and quasi-judicial bodies across the globe raises questions that go well beyond technical efficiency. When a machine assigns a probability score that determines whether a person goes to prison, loses a welfare benefit, or is refused bail, the constitutional guarantees that exist to restrain arbitrary state power are placed under direct pressure. This article maps those pressures through a close reading of constitutional text, judicial doctrine and comparative practice. Drawing on the Indian Constitution's guarantees of personal liberty, equality and judicial independence, alongside the due process tradition of the United States, the fair-trial right in the European Convention on Human Rights, and the European Union's emerging data-rights framework, the article argues that current deployments of algorithmic adjudication systems fall short of the minimum standards that constitutional law demands. Particular attention is given to three clusters of problems: opacity and the right to reasoned decisions; systemic bias and the equal protection guarantee; and the structural argument that the delegation of judicial judgment to automated systems violates the separation of powers. The article then proposes a six-part framework of constitutional safeguards that must be in place before any algorithmic tool can play a legitimate role in proceedings that affect individual rights. Those safeguards include mandatory explainability, pre-deployment bias audits, a prohibition on sole reliance, and a requirement of clear legislative authorisation. The article concludes that the value of efficiency cannot justify the sacrifice of constitutional fairness.
Keywords: Algorithmic Adjudication; Constitutional Safeguards; Due Process; Judicial Independence; Algorithmic Bias; Right to Explanation; Separation of Powers
