Legal Safeguards for Ai-Assisted Judicial Decision-Making: A Comparative Framework of Transparency, Human Oversight and Effective Remedies

Abstract Courts are adopting artificial intelligence faster than lawmakers are writing rules for it. Risk scores inform bail and sentencing, language models draft summaries and sometimes reasoning, and judicial councils issue guidance in the absence of statutes. This article asks what a litigant is legally entitled to when an AI system touches the decision that affects them. Using a doctrinal and functional comparative method, we examine binding and soft-law instruments from the European Union, the Council of Europe, the United Kingdom, the United States, Brazil, Colombia and India, checked against official or reliable sources as of 26 October 2026. Three findings emerge. First, transparency duties are mostly addressed to institutions and regulators; the person whose liberty or rights are at stake rarely gets a right to know that AI was used, still less how. Second, human oversight is declared everywhere but engineered almost nowhere, despite strong evidence that nominal review produces automation bias rather than control. Third, remedies are the weakest link: with few exceptions, no instrument attaches a legal consequence to undisclosed or uncritical reliance on AI. We propose a Disclosure–Oversight–Remedy (DOR) framework that scales safeguards to the way AI is used, from auxiliary support to evaluative input, and prohibits determinative use. The framework converts principles into enforceable procedural entitlements and offers a template for legislators, judicial councils and courts.