AI Agents for Counter-Extremism: Deployment Frameworks for Covert and Overt Digital Deradicalization

This article analyzes strategies for deploying AI agents to counter online extremism, focusing on digital radicalization in Islamic contexts.It assesses technical feasibility, legal constraints (including the EU AI Act), ethical concerns, and theological implications.Drawing on recent case studies-such as ISIS's 2023 AI propaganda guide and the shift of extremist content to gaming platforms-it highlights the dangers of definitional confusion around terms like "Keyboard Jihad," which may lead to misidentifying legitimate Islamic discourse.The study evaluates three AI deployment models: overt analytical agents, direct engagement agents, and covert engagement agents.It concludes that transparent, community-partnered models-especially those offering authentic theological guidance-are the most effective and ethically sound.These models help fill gaps in Islamic knowledge that extremists exploit, while avoiding the legal and strategic pitfalls of covert influence operations, which violate current EU AI regulations.The article recommends a three-track strategy: immediate use of overt analytical agents with safeguards; piloting direct engagement agents through community and theological consultation; and halting covert operations until explicitly authorized by law.Rooted in the Islamic legal principle of maslaha (public interest), the framework prioritizes authenticity, transparency, and respect for democratic values in counterextremism efforts.

Authors

Publication Details

Journal
International Journal of Artificial Intelligence and Machine Learning
Published
2025-07-25
DOI
https://doi.org/10.51483/ijaiml.5.2.2025.23-42
Primary Topic
Terrorism, Counterterrorism, and Political Violence
Type
article
Field-Weighted Citation Impact
0.00
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article

AI Agents for Counter-Extremism: Deployment Frameworks for Covert and Overt Digital Deradicalization

Aadil Bouhlaoui
International Journal of Artificial Intelligence and Machine Learning
Terrorism, Counterterrorism, and Political Violence
article

AI Agents for Counter-Extremism: Deployment Frameworks for Covert and Overt Digital Deradicalization

Aadil Bouhlaoui
article en

Abstract

This article analyzes strategies for deploying AI agents to counter online extremism, focusing on digital radicalization in Islamic contexts.It assesses technical feasibility, legal constraints (including the EU AI Act), ethical concerns, and theological implications.Drawing on recent case studies-such as ISIS's 2023 AI propaganda guide and the shift of extremist content to gaming platforms-it highlights the dangers of definitional confusion around terms like "Keyboard Jihad," which may lead to misidentifying legitimate Islamic discourse.The study evaluates three AI deployment models: overt analytical agents, direct engagement agents, and covert engagement agents.It concludes that transparent, community-partnered models-especially those offering authentic theological guidance-are the most effective and ethically sound.These models help fill gaps in Islamic knowledge that extremists exploit, while avoiding the legal and strategic pitfalls of covert influence operations, which violate current EU AI regulations.The article recommends a three-track strategy: immediate use of overt analytical agents with safeguards; piloting direct engagement agents through community and theological consultation; and halting covert operations until explicitly authorized by law.Rooted in the Islamic legal principle of maslaha (public interest), the framework prioritizes authenticity, transparency, and respect for democratic values in counterextremism efforts.

International Journal of Artificial Intelligence and Machine LearningVol. 5(2)
Openalex Percentile: Top 71%
Terrorism, Counterterrorism, and Political Violence
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AI Agents for Counter-Extremism: Deployment Frameworks for Covert and Overt Digital Deradicalization — Aadil Bouhlaoui · International Journal of Artificial Intelligence and Machine Learning (2025) | TGRS Research Map | TGRS