Specificities of Criminal Liability in Offenses Committed Using Artificial Intelligence Technologies

The technological advancements of recent years have led to the emergence of numerous offenses commonly referred to in legal scholarship as artificial intelligence (AI) crimes. Advanced AI systems have endowed certain modern technological devices with exceptional capabilities, to the extent that they can autonomously make decisions in various situations much like human beings.This study aims, first, to examine the arguments supporting the recognition of criminal liability for AI-related crimes; second, to explore the arguments opposing such recognition; and third, to define the scope of criminal liability in relation to AI crimes. The research concludes with several key findings, most notably that the rapid expansion of AI technologies has given rise to many associated crimes not yet addressed by existing criminal legislation, which remains underdeveloped in this regard. Furthermore, contemporary criminal laws tend to affirm that only human beings can bear criminal responsibility. Criminal liability is thus limited to natural persons, excluding inanimate objects or animals. Since it is the human who programs and operates the AI system to commit crimes, it is the human who bears criminal responsibility for the AI's unlawful actions regardless of the purpose or intent behind those actions, whether for amusement, experimentation, or otherwise.

Authors

Publication Details

Journal
AL-Qadisiya Journal For Law and Political Sciences
Published
2025-12-01
DOI
https://doi.org/10.63677/jqlap.2025.160369.1352
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

Specificities of Criminal Liability in Offenses Committed Using Artificial Intelligence Technologies

خالد الخاقاني
AL-Qadisiya Journal For Law and Political Sciences
Indonesian Legal and Regulatory Studies
article

Specificities of Criminal Liability in Offenses Committed Using Artificial Intelligence Technologies

خالد الخاقاني
article en

Abstract

The technological advancements of recent years have led to the emergence of numerous offenses commonly referred to in legal scholarship as artificial intelligence (AI) crimes. Advanced AI systems have endowed certain modern technological devices with exceptional capabilities, to the extent that they can autonomously make decisions in various situations much like human beings.This study aims, first, to examine the arguments supporting the recognition of criminal liability for AI-related crimes; second, to explore the arguments opposing such recognition; and third, to define the scope of criminal liability in relation to AI crimes. The research concludes with several key findings, most notably that the rapid expansion of AI technologies has given rise to many associated crimes not yet addressed by existing criminal legislation, which remains underdeveloped in this regard. Furthermore, contemporary criminal laws tend to affirm that only human beings can bear criminal responsibility. Criminal liability is thus limited to natural persons, excluding inanimate objects or animals. Since it is the human who programs and operates the AI system to commit crimes, it is the human who bears criminal responsibility for the AI's unlawful actions regardless of the purpose or intent behind those actions, whether for amusement, experimentation, or otherwise.

AL-Qadisiya Journal For Law and Political SciencesVol. 16(Issue: 2 part 2)
Peace, Justice and strong institutions
Openalex Percentile: Top 7%
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.