Information in data-driven investigations

Abstract

This paper examines the emerging forms of public surveillance enabled by artificial intelligence, which are reshaping both the epistemology and the normativity of investigative practices. Through predictive techniques and automated data analysis, the function of criminal prevention takes on a proactive and probabilistic structure, thereby challenging the principles of legality, proportionality, and transparency. Starting from a conceptual genealogy of surveillance, the study explores the transition from centralized disciplinary models to decentralized and opaque networked systems. Particular attention is devoted to the European Union’s Artificial Intelligence Act (AI Act), whose systemic implications and regulatory gaps are critically assessed. The paper ultimately proposes a reconceptualization of public surveillance in a constitutional framework, aimed at safeguarding fundamental rights in the digital space in light of the standards developed by the European Parliament’s PEGA Committee.