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n7mfh_v1 Beyond Black Boxes and Biases: Advancing Artificial Intelligence in Sentencing Abstract: This study explores the potential integration of artificial intelligence (AI) in the Indonesian legal system to enhance the consistency of sentencing in the context of corruption offences. We examine the role of AI as a judicial assistant within the framework of the Indonesian Supreme Court's 2020 Sentencing Guidelines for the Law on the Eradication of Criminal Acts of Corruption. We argue that the structured nature of the corruption sentencing guidelines—which include a stepwise approach and the ternary categorisation of sentencing factors—presents a unique opportunity to address the many criticisms and challenges concerning the use of AI in sentencing. Specifically, we suggest that AI could be a valuable tool for assisting judges in delivering more consistent sentences for corruption offences. Our objective is not to advocate for the immediate adoption of AI but to stimulate discussion on novel strategies for the application of AI in sentencing. 2025-03-15T02:47:47.198046 2025-03-25T04:16:42.509219 2025-03-24T20:06:33.306429     lawarchive 1 accepted 1 1 https://doi.org/10.31219/osf.io/n7mfh_v1 CC-By Attribution 4.0 International Artificial Intelligence; Criminal Law; Law and Technology; Machine Learning; Sentencing; Sentencing consistency ["Artificial Intelligence", "Criminal Law", "Law and Technology", "Machine Learning", "Sentencing", "Sentencing consistency"] Armin Alimardani [{"id": "8a3rq", "name": "Armin Alimardani", "index": 0, "orcid": "0000-0002-5580-4239", "bibliographic": true}] Armin Alimardani Law; Science and Technology Law; Criminal Law [{"id": "65047462c666880012ba225a", "text": "Law"}, {"id": "65047475c666880012ba25b9", "text": "Science and Technology Law"}, {"id": "65047475c666880012ba25be", "text": "Criminal Law"}] https://osf.io/download/67d4ea6ce90267294da72689 0       null   2025-04-09T21:06:20.362363
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