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Article . 2024 . Peer-reviewed
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Article . 2024
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Az MI-fordulat: hogyan használja fel az Europol a mesterséges intelligenciát a súlyos szervezett bűnözés és a terrorizmus elleni küzdelemben

Authors: Valér Dános;

Az MI-fordulat: hogyan használja fel az Europol a mesterséges intelligenciát a súlyos szervezett bűnözés és a terrorizmus elleni küzdelemben

Abstract

Aim: The aim of this article is to highlight the importance of leveraging Artificial Intelligence (AI) in law enforcement to combat serious organised crime and terrorism, while ensuring responsible and accountable use of AI tools through collaboration and knowledge-sharing among European law enforcement agencies. Methodology: The study uses a descriptive methodology to describe the development and cooperation process through which the Innovation Lab contributes to the innovation development and knowledge sharing of Europol and its member countries. Findings: With the increasing volume and speed of investigative data, AI has emerged as a promising solution to help law enforcement agencies process and analyse large and complex datasets. Europol has been at the forefront of developing and sharing AI tools with its Member States, ensuring their responsible and accountable use. The integration of Artificial Intelligence (AI) in law enforcement investigations has been found to significantly enhance the efficiency and effectiveness of crime fighting, particularly in processing and analysing large and complex datasets. Value: The article highlights the importance of collaboration and knowledge-sharing among law enforcement agencies to keep pace with AI advancements and prevent criminal abuse of these technologies.

Keywords

340, bűnüldözés, államigazgatás általában, Innovációs Központ, mesterséges intelligencia (MI), JF20-2112, Europol, JF Political institutions (General) / politikai intézmények, Political institutions and public administration (General), 650, K Law (General) / jogtudomány általában

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
gold