"waiting for Godot: Can Ai Be Fully Regulated?" Between Normative Urgency and Regulatory Inertia
Year: 2026
Type: conference-paper
Abstract: A defining characteristic of contemporary society is the intensive process of digitalization and the widespread use of social media platforms. While communication and information exchange have been significantly enhanced, these platforms simultaneously generate vast amounts of data that may possess considerable security and intelligence value. Consequently, social media has become an important source of information for criminal investigation activities conducted by law enforcement agencies. However, the volume and complexity of data generated on these platforms exceed the capabilities of traditional analytical methods, creating a need for the application of advanced technological solutions.In this context, artificial intelligence (AI) represents a key tool for the automated processing and analysis of large-scale unstructured data sets. The aim of this paper is to examine the potential applications of artificial intelligence in social media analysis for criminal investigation purposes, with particular emphasis on the identification of security threats, behavioral patterns, and criminal networks. Special attention is devoted to the use of contemporary AI-driven methods within the OSINT (Open Source Intelligence) framework, as well as their role in crime prevention, countering extremism, and enhancing the situational awareness of law enforcement agencies.In conclusion, the application of artificial intelligence in social media analysis represents an important direction in the modernization of policing and criminal investigation practices. Nevertheless, its effective implementation requires the establishment of an appropriate legal and ethical framework to ensure a balance between security interests and the protection of fundamental civil rights and freedoms. Keywords: social media, artificial intelligence, OSINT, security threats.
Institution: University of Zagreb
Language: English
Subfield: Health
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7208722209