Сучасні механізми пропагандистських кампаній на базі штучного інтелекту

Автор(и)

  • В. О. Каменчук Навчально-науковий видавничо-поліграфічний інститут, КПІ ім. Ігоря Сікорського, м. Київ, Україна https://orcid.org/0009-0004-4368-4366
  • С. Б. Фіялка Навчально-науковий видавничо-поліграфічний інститут, КПІ ім. Ігоря Сікорського, м. Київ, Україна https://orcid.org/0000-0002-1855-7574

DOI:

https://doi.org/10.20535/2522-1078.2026.1(19).358431

Ключові слова:

штучний інтелект, інформаційні операції, генеративні мовні моделі, дезінформація, когнітивний вплив, алгоритмічне підсилення, таргетована персоналізація

Анотація

Запропоновано огляд сучасних підходів до використання систем штучного інтелекту в пропагандистських практиках у цифровому інформаційному середовищі. Огляд спирається на рецензовані публікації 2024–2026 років у провідних міжнародних наукових виданнях, а також на верифіковані аналітичні звіти національних агентств з протидії дезінформації, незалежних дослідницьких лабораторій і міжнародних парламентських інституцій, що дає змогу окреслити основні механізми ШІ-пропаганди та логіку їхнього функціонування в сучасних умовах.

Для систематизації механізмів запропоновано аналітичну матрицю шести рівнів впливу: когнітивного, поведінкового, мережевого, рівня середовища, мікро- та мезорівня. Показано, що жоден із розглянутих механізмів не обмежується одним рівнем, більшість діють одночасно в кількох вимірах, а їхнє поєднання утворює систему.

Посилання

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A small number of samples can poison LLMs of any size. Anthropic, UK AISI, Alan Turing Institute. 2025. URL: https://www.anthropic.com/research/small­samples­poison (access date: 19.04.2026)

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Igartua J., Rogriguez­Contreras L. Narrative Voice Matters! Improving Smoking Prevention with Testimonial Messages through Identification and Cognitive Processes. International Journal of Environmental Research and Public Health. 2020. Vol. 17, iss. 19. URL: https://doi.org/10.3390/ijerph17197281.

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The spread of low­credibility content by social bots. Nature Communications / C. Shao et al. 2018. Vol. 9, iss. 4787. URL: https://doi.org/10.1038/s41467­018­06930­7.

Engagement, user satisfaction, and the amplification of divisive content on social media / S. Milli et al. PNAS Nexus. 2025. Vol. 4, iss. 3. URL: https://doi.org/10.1093/pnasnexus/pgaf062.

Ganaie N.мA. The role of artificial intelligence in radicalisation, rec­ruit­ment and terrorist propaganda: deconstructing violent extremism and reimagining counterterrorism in contemporary digital ecosystems. Frontiers in Political Science. 2026. Vol. 7. URL: https://doi.org/10.3389/fpos.2025.1718396

Osadchuk R., Buziashvili E. Explainer: the Russian influence operations targeting the 2024 US elections. Digital Forensic Research Lab. 2024. URL: https://dfrlab.org/2024/09/06/how­doppelganger­and­other­russia­linked­operations­target­us­elections/ (access date: 19.04.2026).

Stockwell S. Propaganda by Meme. The impact of generative AI on extremist memes. CETaS. Alan Turing Institute. 2024. URL: https://cetas.turing.ac.uk/publications/propaganda­meme (access date: 19.04.2026).

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REFERENCES

Blatny, J., & Søndergaard, S. (2025). Cognitive warfare. NATO STO. https://www.sto.nato.int/wp-content/uploads/chief-scientist-report-cognitive-warfare-final.pdf

Vassilev, A., et al. (2024). Adversarial machine learning: A taxonomy and terminology of attacks and mitigations. National Institute of Standards and Technology. https://doi.org/10.6028/NIST.AI.100-2e2023

Alber, D. A., et al. (2025). Medical large language models are vulnerable to data-poisoning attacks. Nature Medicine, 31, 618–626. https://doi.org/10.1038/s41591-024-03445-1

Anthropic, UK AISI, & Alan Turing Institute. (2025). A small number of samples can poison LLMs of any size. Anthropic. https://www.anthropic.com/research/small-samples-poison

Salvi, F., et al. (2025). On the conversational persuasiveness of GPT-4. Nature Human Behaviour, 9, 1645–1653. https://doi.org/10.1038/s41562-025-02194-6

Simchon, A., et al. (2024). The persuasive effects of political microtargeting in the age of generative artificial intelligence. PNAS Nexus, 3(2). https://doi.org/10.1093/pnasnexus/pgae035

Schroeder, D. T., et al. (2026). How malicious AI swarms can threaten democracy. Science, 391(6783). https://doi.org/10.1126/science.adz1697

Truong, B. T., et al. (2024). Quantifying the vulnerabilities of the online public square to adversarial manipulation tactics. PNAS Nexus, 3(7). https://doi.org/10.1093/pnasnexus/pgae258

Rutgers University Network Contagion Research Institute. (2024). The botification of the American mind. https://networkcontagion.us/reports/the-botification-of-the-american-mind/

Farcaș, I.-C. (2025). Manufacturing "realities": The impact of AI in the age of disinformation. Revue Internationale Animation, Territoires et Pratiques Socioculturelles. https://doi.org/10.55765/atps.i28.3650

Wack, M., et al. (2025). Generative propaganda: Evidence of AI's impact from a state-backed disinformation campaign. PNAS Nexus, 4(4). https://doi.org/10.1093/pnasnexus/pgaf083

VIGINUM. (2024). Portal Kombat: A structured and coordinated pro-Russian propaganda network. https://www.sgdsn.gouv.fr/files/files/Publications/20240214_NP_SGDSN_VIGINUM_PORTAL-KOMBAT-NETWORK_PART2_ENG_VF.pdf

Sadeghi, M., & Blachez, I. (2025). A well-funded Moscow-based global 'news' network has infected Western artificial intelligence tools worldwide with Russian propaganda. NewsGuard. https://www.newsguardrealitycheck.com/p/a-well-funded-moscow-based-global

Gross, E.-C., & Colson, A. J. M. (2025). AI-slop and political propaganda: The role of AI-generated content in memes and influence campaigns. EON Journal, 6(3). https://doi.org/10.56177/EON.6.3.2025.ART.1

Matz, S. C., et al. (2024). The potential of generative AI for personalized persuasion at scale. Scientific Reports, 14, 4692. https://doi.org/10.1038/s41598-024-53755-0

Alyukov, M., et al. (2025). LLMs grooming or data voids? LLM-powered chatbot references to Kremlin disinformation reflect information gaps, not manipulation. Harvard Kennedy School Misinformation Review. https://doi.org/10.37016/mr-2020-187

Digital Forensic Research Lab. (2026). Pravda in the pipeline: Early evidence of state-adjacent propaganda in AI training data. https://dfrlab.org/2026/04/08/pravda-in-the-pipeline/

Dylan, H., & Grossfeld, E. (2025). Revisionist future: Russia's assault on large language models, the distortion of collective memory, and the politics of eternity. Dialogues on Digital Society, 1(3), 407–412. https://doi.org/10.1177/29768640251377941

Del Vicario, M., et al. (2016). The spreading of misinformation online. Proceedings of the National Academy of Sciences, 113(3), 554–559. https://doi.org/10.1073/pnas.1517441113

Goldstein, A., et al. (2024). How persuasive is AI-generated propaganda? PNAS Nexus, 3(2). https://doi.org/10.1093/pnasnexus/pgae034

Hoekstra, M., Huisman, W., & van der Schee, B. (2026). Catching neutralizations: Identifying neutralization techniques for white-collar crimes in offender statements. Journal of Economic Criminology, 11. https://doi.org/10.1016/j.jeconc.2025.100203

Pacchioni, F., et al. (2025). Generative AI and criminology: A threat or a promise? Exploring the potential and pitfalls in the identification of techniques of neutralization (ToN). PLOS One. https://doi.org/10.1371/journal.pone.0319793

Santus, D., & Bettin, C. (2025). Antisemitism in the algorithmic age: Propaganda, disinformation, and generative AI. Zeitschrift für Religion, Gesellschaft und Politik. https://doi.org/10.1007/s41682-025-00234-6

Igartua, J., & Rodríguez-Contreras, L. (2020). Narrative voice matters! Improving smoking prevention with testimonial messages through identification and cognitive processes. International Journal of Environmental Research and Public Health, 17(19), 7281. https://doi.org/10.3390/ijerph17197281

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Shao, C., et al. (2018). The spread of low-credibility content by social bots. Nature Communications, 9, 4787. https://doi.org/10.1038/s41467-018-06930-7

Milli, S., et al. (2025). Engagement, user satisfaction, and the amplification of divisive content on social media. PNAS Nexus, 4(3). https://doi.org/10.1093/pnasnexus/pgaf062

Ganaie, N. A. (2026). The role of artificial intelligence in radicalisation, recruitment and terrorist propaganda: Deconstructing violent extremism and reimagining counterterrorism in contemporary digital ecosystems. Frontiers in Political Science, 7. https://doi.org/10.3389/fpos.2025.1718396

Osadchuk, R., & Buziashvili, E. (2024). Explainer: The Russian influence operations targeting the 2024 US elections. Digital Forensic Research Lab. https://dfrlab.org/2024/09/06/how-doppelganger-and-other-russia-linked-operations-target-us-elections/

Stockwell, S. (2024). Propaganda by meme: The impact of generative AI on extremist memes. CETaS, Alan Turing Institute. https://cetas.turing.ac.uk/publications/propaganda-meme

Mishra, A., & Karumbaya, V. (2024). A deadly trifecta: Disinformation networks, AI memetic warfare, and deepfakes. Global Network on Extremism & Technology. https://gnet-research.org/2024/02/15/a-deadly-trifecta-disinformation-networks-ai-memetic-warfare-and-deepfakes/

Chang, H.-C., et al. (2024). Generative memesis: AI mediates political memes in the 2024 United States presidential election. arXiv. https://doi.org/10.48550/arXiv.2411.00934

Mihăilescu, M. (2025). Meme warfare in Romania: The manipulation of public consciousness. The Loop, ECPR. https://theloop.ecpr.eu/meme-warfare-in-romania-the-manipulation-of-public-consciousness/

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Опубліковано

2026-06-30

Як цитувати

Каменчук, В. О., & Фіялка, С. Б. (2026). Сучасні механізми пропагандистських кампаній на базі штучного інтелекту. Обрії друкарства, (1(19), 133–152. https://doi.org/10.20535/2522-1078.2026.1(19).358431

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