Causative-Victim Tracing for Integrative Criminal Policy on AI Deepfake Face and Voice Crimes in Indonesia

Muhammad Abdul Azis; Pujiyono

doi:10.31599/krtha.v20i2.5666

Authors

Muhammad Abdul Azis Universitas Diponegoro
Pujiyono Universitas Diponegoro

DOI:

https://doi.org/10.31599/krtha.v20i2.5666

Keywords:

AI deepfake, Causative-Victim Tracing, integralistic criminal law, biometric identity, victim protection

Abstract

This study aims to analyze the weaknesses of Indonesia’s criminal law policy in responding to facial and voice AI deepfakes, and to formulate Causative-Victim Tracing as an application of integralistic criminal law policy. The method used is normative juridical research with conceptual, statutory, case, and limited comparative approaches. The findings show that deepfake regulation remains partial because it is fragmented across the Personal Data Protection Law, the Electronic Information and Transactions Law, the Criminal Code, and the Law on Sexual Violence Crimes. These instruments can address certain acts, but they have not yet understood deepfake as a sequence of crime involving biometric data, AI technology, layered actors, platform distribution, digital evidence, and recurring harm to victims. This study offers Causative-Victim Tracing to connect the tracing of data sources, technology, actors, platforms, and evidentiary obstacles with the mapping of victims, forms of harm, protection, and recovery from the earliest stage.

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