Greenation International Journal of Law and Social Sciences
Vol. 4 No. 3 (2026): (GIJLSS) Greenation International Journal of Law and Social Sciences (July - Au

Hybrid Criminal Liability Based on Risk-Based Approach in Artificial Intelligence-Based Crimes in Indonesia

Mohammad Erfan (Universitas Boyolali, Jawa Tengah, Indonesia.)
Nanik Sutarni (Universitas Boyolali, Jawa Tengah, Indonesia.)
Ananda Megha Wiedhar Saputri (Universitas Boyolali, Jawa Tengah, Indonesia.)
Sri Budi Raharjo (Universitas Boyolali, Jawa Tengah, Indonesia.)



Article Info

Publish Date
22 Aug 2026

Abstract

The development of Artificial Intelligence (AI) has introduced new challenges in criminal law, particularly regarding criminal liability in technology-based crimes. AI systems capable of operating semi-autonomously blur the relationship between the perpetrator, the act, and culpability, rendering the conventional fault-based principle of geen straf zonder schuld increasingly inadequate. This study aims to analyze the existing Indonesian criminal law framework governing AI-related crimes and to formulate an ideal model of criminal liability in response to such developments. This research employs a normative juridical method with statutory and conceptual approaches. The findings indicate that current regulations in Indonesia remain limited and have not comprehensively addressed the complexity of AI-based crimes. Accordingly, this study proposes a hybrid criminal liability model based on a risk-based approach, integrating strict liability, vicarious liability, and risk-based accountability as mechanisms for proportional responsibility distribution without recognizing AI as a legal subject. This model is expected to contribute to the reform of criminal law toward a more adaptive, responsive, and just legal system in addressing AI-related crimes.

Copyrights © 2026






Journal Info

Abbrev

GIJLSS

Publisher

Subject

Law, Crime, Criminology & Criminal Justice Social Sciences

Description

Greenation International Journal of Law and Social Sciences (GIJLSS) is a journal that uses a blind peer-review model that can be accessed online. GIJLSS aims to publish a journal containing quality articles that will be able to contribute thoughts from theoretical and empirical perspectives for the ...