Jurisdiction in the Age of Artificial Intelligence: Rethinking Criminal Liability Across Algorithmic Borders
ABSTRACT
The rapid integration of artificial intelligence (AI) into everyday technologies has fundamentally altered the nature of criminal activity and its regulation. Unlike traditional crimes anchored in physical territories, AI-driven offences often operate across decentralized digital environments, challenging the conventional principles of criminal jurisdiction. This shift raises a critical question: how can legal systems attribute criminal liability when harmful outcomes are produced by autonomous or semi-autonomous algorithms functioning beyond geographical boundaries?
This paper examines the growing inadequacy of territorial jurisdiction in addressingAI-enabled crimes, including deepfake fraud, autonomous system failures, and algorithmicmanipulation. It argues that existing legal frameworks struggle to assign responsibilityamongdevelopers, deployers, and users, thereby creating a “liability gap” that weakensaccountability. Additionally, the opaque nature of AI systems further complicates evidentiarystandards and enforcement mechanisms across jurisdictions. By introducing the concept of“algorithmic borders,” the paper proposes a rethinking of jurisdiction based not solelyonphysical territory but on data flows, system control, and functional impact. It furtherhighlights the tension between traditional state sovereignty and the rise of decentralized, AI-driven digital ecosystems, which increasingly challenge the authority of nation-statesinregulating transnational crimes. In response, the paper advocates for a hybrid model of shared jurisdiction combined with AI-specific liability principles to effectively address thesee merging challenges.
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