Gauging Algorithmic Justice: Assessing Indonesia’s Readiness to Adopt Predictive Justice in Criminal Law - Gunawan Rena (SEAN Institute, 2026)
This article analyses the normative, institutional, and procedural readiness of Indonesia’s criminal justice system to adopt predictive justice tools, particularly algorithmic risk assessment, as decision‑support in bail, sentencing, and parole. Using a normative juridical and comparative approach, the study examines the compatibility of such tools with fundamental criminal law principles, including legality, individual culpability, presumption of innocence, proportionality, equality before the law, and the right to a fair and transparent trial. It argues that algorithmic, forward‑looking assessments of risk sit in structural tension with a system traditionally grounded in adjudication of past wrongdoing and individual guilt, and may entrench historical bias embedded in criminal justice data. At the same time, the article evaluates Indonesia’s institutional and regulatory infrastructure, identifying serious deficiencies in data quality and governance, legal rules on admissibility and transparency of algorithmic assessments, oversight mechanisms, and technical capacity among legal actors. The study concludes that Indonesia is not yet adequately prepared to integrate predictive justice and that significant reforms are required before such tools can be legitimately employed as subordinate aids rather than drivers of criminal decision‑making.