AI-driven manipulative technologies and the evolution of transport threats: a risk-based assessment

Shola Shekili ()
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Shola Shekili: National Aviation Academy of Azerbaijan

Journal of Transportation Security, 2025, vol. 18, issue 1, No 8, 10 pages

Abstract: Abstract Background The increasing integration of artificial intelligence (AI) into communication, surveillance, and transport systems has generated concern regarding its potential misuse for ideological radicalization and behavioral manipulation. While no documented cases of AI-facilitated terrorist attacks have occurred to date, international agencies have begun issuing early-warning assessments regarding emerging digital risks in critical infrastructure sectors. Methods This article conducts a multidisciplinary synthesis of international threat reports and early alert frameworks from organizations such as ICAO, Europol, UNOCT, and OSCE. It develops a conceptual framework linking manipulative AI technologies—such as adaptive chatbots, algorithmic echo chambers, and generative personas—with potential vectors of behavioral infiltration in the transportation domain. Results The study identifies a dual-risk trajectory: (1) external radicalization of lone actors through personalized ideological conditioning, and (2) internal manipulation of insiders via deceptive or coercive AI stimuli. These patterns are mapped against transportation-specific vulnerabilities, particularly in aviation and metro environments. Conclusion Although AI-based terrorist attacks have not materialized operationally, the convergence of psychological influence and transport-access technologies requires urgent attention. A forward-looking risk typology is proposed to support early detection, personnel screening, and system-wide resilience in the face of AI-augmented behavioral threats.

Keywords: Artificial intelligence; Transport security; Behavioral manipulation; Radicalization; Insider threats; Aviation risk; International risk assessments (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s12198-025-00300-3

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