AI-ASSISTED DECISION-MAKING IN PUBLIC SECURITY Opportunities, Vulnerabilities and Professional Training Requirements


Colonel (ret) Professor George-Marius ȚICAL, Ph.D*

Abstract: The integration of artificial intelligence into public security is changing the relationship between data, analysis and professional decision-making. Algorithmic systems can process large volumes of information, identify patterns that are difficult to observe and support risk assessment or resource allocation. However, the same capabilities can produce effects contrary to legality and effectiveness when data are incomplete, models are opaque, results are affected by bias or users place excessive trust in technological recommendations. This article analyses the opportunities and vulnerabilities of AI-assisted decision-making in public security with reference to Regulation (EU) 2024/1689, Europol and FRA documents, and UNICRI–INTERPOL instruments. It argues that human oversight becomes effective only when the operator has the competence, authority and time required to verify and, where appropriate, reject the algorithmic output. As an original contribution, the article proposes the C.O.N.T.R.O.L. professional training model, focused on understanding the system, verifying data provenance, applying the relevant rules, testing the output, assuming responsibility, observing effects and drawing on lessons learned.

Keywords: artificial intelligence; public security; assisted decision-making; human oversight; algorithmic bias; professional training.

DOI       10.56082/annalsarscimilit.2026.3.64

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* “Andrei Șaguna” University, Associated Member of the Academy of Romanian Scientists, Entitled Member of The Academy of National Security Sciences, email: ticalgeorgem@gmail.com

PUBLISHED in

  Annals Academy of Romanian Scientists Series on Military Sciences, 

Volume 18 no 3, 2026


DOAJ, CEEOL

      ISSN Print 2066-7086
ISSN Online 2457-8312