AI-Induced Fatalities: A Criminal Law Perspective from Indonesia and International Perspective

<div class="WordSection1"><div class="WordSection1"><p><em>The rapid development of AI has raised legal challenges, particularly when AI causes harm or even death. This study analyses criminal liability in AI cases from the perspectives of Indonesian and international law, with a primary case study focusing on the death of a teenager resulting from interaction with an AI chatbot. The study aims to examine whether traditional principles of criminal liability (actus reus and mens rea) can be applied to AI and evaluate the readiness of the Indonesian legal system to manage AI-related cases. The research adopts a qualitative approach with doctrinal, comparative, and interdisciplinary analyses. The findings indicate that AI cannot fulfil the element of mens rea. Thus, criminal liability must be transferred to the actors behind AI, such as developers or service providers, through vicarious liability mechanisms. Comparatively, some jurisdictions, such as the European Union, have adopted a risk-based approach to regulate AI, while Indonesia still faces a legal vacuum. This study suggests that legal reforms are needed, including the establishment of a special category of liability for AI, mandatory risk assessment, and harmonising international regulations. Therefore, a responsive legal framework can be established to protect individual rights and ensure the responsible development of AI.</em></p></div></div>

Authors

Publication Details

Journal
Yustisia Jurnal Hukum
Published
2025-08-13
DOI
https://doi.org/10.20961/yustisia.v14i2.101636
Primary Topic
Indonesian Legal and Regulatory Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI-Induced Fatalities: A Criminal Law Perspective from Indonesia and International Perspective

Vicko Taniady
Yustisia Jurnal Hukum
Indonesian Legal and Regulatory Studies
article

AI-Induced Fatalities: A Criminal Law Perspective from Indonesia and International Perspective

Vicko Taniady
article en

Abstract

<div class="WordSection1"><div class="WordSection1"><p><em>The rapid development of AI has raised legal challenges, particularly when AI causes harm or even death. This study analyses criminal liability in AI cases from the perspectives of Indonesian and international law, with a primary case study focusing on the death of a teenager resulting from interaction with an AI chatbot. The study aims to examine whether traditional principles of criminal liability (actus reus and mens rea) can be applied to AI and evaluate the readiness of the Indonesian legal system to manage AI-related cases. The research adopts a qualitative approach with doctrinal, comparative, and interdisciplinary analyses. The findings indicate that AI cannot fulfil the element of mens rea. Thus, criminal liability must be transferred to the actors behind AI, such as developers or service providers, through vicarious liability mechanisms. Comparatively, some jurisdictions, such as the European Union, have adopted a risk-based approach to regulate AI, while Indonesia still faces a legal vacuum. This study suggests that legal reforms are needed, including the establishment of a special category of liability for AI, mandatory risk assessment, and harmonising international regulations. Therefore, a responsive legal framework can be established to protect individual rights and ensure the responsible development of AI.</em></p></div></div>

Yustisia Jurnal HukumVol. 14(2)
Openalex Percentile: Top 73%
Indonesian Legal and Regulatory Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.