Штучний інтелект у виборчому процесі: нові виміри кіберзагроз і кібербезпеки
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Анотація
Актуальність. У сучасному цифровому середовищі штучний інтелект дедалі частіше використовують як інструмент політичної комунікації, а також як засіб здійснення, нерідко деструктивного, впливу на виборців. Вибори, як один із ключових механізмів функціонування демократичних суспільств, трансформуються у складні, багатокомпонентні системи, вразливі до психологічних маніпуляцій. Генеративні моделі штучного інтелекту, здатні створювати переконливі тексти, аудіо- та відеоматеріали, стають новим викликом для безпеки виборчих кампаній, оскільки забезпечують масштабоване створення дезінформації і deepfake-контенту, спрямованого на конкретні групи виборців. Крім того, моделі опрацювання природної мови і системи предиктивної аналітики на основі великих масивів даних можуть використовуватися для мікротаргетингу політичних повідомлень. Це не лише суперечить етичним нормам, а й підриває принципи рівного доступу до інформації для всіх учасників виборчого процесу. Алгоритми, які визначають емоційний стан виборців, здатні підвищувати ефективність політичної реклами, але водночас призводять до маніпулювання емоційними станами, що спричинює викривлене сприйняття реальності.
Мета: дослідити основні сфери можливостей і загроз, які створює штучний інтелект у контексті виборчого процесу, та окреслити можливі підходи до стримування пов’язаних із цим загроз.
Результати. Проаналізовано психологічні і технологічні аспекти потенційного впливу технологій штучного інтелекту на політичні процеси, зокрема виборчі. Показано, що штучний інтелект породжує якісно нові кіберзагрози, здатні критично дестабілізувати виборчі процеси в різних країнах. Досліджено як деструктивний, так і конструктивний потенціал штучного інтелекту в контексті виборчих кампаній, проаналізовано сучасні тенденції використання ШІ в політичних цілях з урахуванням як технологічних інструментів впливу, так і методів захисту від новітніх загроз. Запропоновано основні стратегії протидії зловживанню штучним інтелектом у виборчих процесах, зокрема в нормативно-правовій, кібербезпековій та освітній сферах, із конкретизацією можливих заходів та прикладами їх реалізації, релевантними для сучасної України.
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Як цитувати
Старовойтенко, О. (2025). Штучний інтелект у виборчому процесі: нові виміри кіберзагроз і кібербезпеки. Проблеми політичної психології, 17(31). https://doi.org/10.33120/popp-Vol17-Year2025-194
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Chiu, M. (2023). Combating AI-powered disinformation: Taiwan's evolving legal response. Journal of Digital Law and Policy, 7(2), 65–83. https://doi.org/10.1016/j.jdlp.2023.07.005
Cabinet of Ministers of Ukraine. (2020). Concept of Artificial Intelligence Development in Ukraine. https://zakon.rada.gov.ua/laws/show/1556-2020-р#Text
Council of Europe. (2024). Framework Convention on Artificial Intelligence, Human Rights, Democracy and the Rule of Law. https://www.coe.int/en/web/artificial-intelligence
Creemers, R. (2022). AI regulation and electoral integrity: A comparative legal approach. Journal of Law and Artificial Intelligence, 1(2), 43–62. https://doi.org/10.2139/ssrn.4088532
Dubois, J., & Girard, M. (2024). Synthetic media and electoral disinformation in France. French Journal of Political Risk, 7(1), 25–38.
European Commission. (2023). Digital Services Act and Electoral Resilience. https://digital-strategy.ec.europa.eu
Ferrara, E., Varol, O., Davis, C., Menczer, F., & Flammini, A. (2016). The rise of social bots. Communications of the ACM, 59(7), 96–104.
Flaxman, S., Goel, S., & Rao, J. M. (2016). Filter bubbles, echo chambers, and online news consumption. Public Opinion Quarterly, 80(S1), 298–320.
Frantsuz, A. Y., Stepanenko, N. V., & Shevchenko, A. E. (2023). The problem of artificial intelligence in the electoral process. Legal Bulletin, (9), 71–76. https://doi.org/10.31732/2708-339X-2023-09-71-76
Friedman, A., Lau, T., & McCabe, M. (2023). Regulating deepfakes in U.S. elections: State-level responses and federal proposals. Harvard Journal of Law & Technology, 37(1), 122–145.
Funke, D., Flamini, D., & Wardle, C. (2021). Building media literacy hubs: Community-based strategies in the fight against misinformation. Journal of Media Literacy Education, 13(1), 45–62. https://doi.org/10.23860/JMLE-2021-13-1-5
Giannoulakis, S., & Tsapatsoulis, N. (2022). A framework for detecting disinformation using machine learning. Journal of Information Warfare, 21(2), 34–49.
Giannoulakis, S., & Tsapatsoulis, N. (2022). Real-time fake news detection in social media: A hybrid deep learning approach. Journal of Information Security and Applications, 65, 103136. https://doi.org/10.1016/j.jisa.2022.103136
Hajli, N., et al. (2021). Big data and AI in politics: Implications for democracy. Journal of Business Research, 124, 707–715.
Haman, M., et al. (2024). Artificial intelligence in political communication: Ethical and practical challenges. AI and Society, in press.
Hao, K., et al. (2022). Deep deceptions: AI-driven disinformation and threats to democracy. AI & Society, 37(4), 765–778.
Haman, M., & Školník, M. (2024). Who would chatbots vote for? Political preferences of ChatGPT and Gemini in the 2024 European Union elections. arXiv preprint, arXiv:2409.00721. https://arxiv.org/abs/2409.00721
Hartmann, M., et al. (2020). Trust in algorithmic decision-making in political contexts. Information, Communication & Society, 23(4), 556–573.
Hartmann, J., Schwenzow, J., & Witte, M. (2023). The political ideology of conversational AI: Converging evidence on ChatGPT's pro-environmental, left-libertarian orientation. arXiv preprint, arXiv:2301.01768. https://arxiv.org/abs/2301.01768
IFES Ukraine. (2024). Adapting EU Artificial Intelligence Regulations for Electoral Processes: A Path for Ukraine. https://www.ifesukraine.org/wp-content/uploads/2024/09/ifes-artificial-intelligence-eng-5.pdf
Isaak, J., & Hanna, M. J. (2018). User data privacy: Facebook, Cambridge Analytica, and privacy protection. Computer, 51(8), 56–59.
Islam, M., Jiang, M., & Chen, Y. (2024). AI-enabled cyber attacks: Risks for democratic institutions. International Journal of Cyber Security and Digital Forensics, 13(2), 97–111. https://doi.org/10.5121/ijcsdf.2024.13207
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Kalsnes, B., & Larsson, A. O. (2021). Social media literacy and digital citizenship: An analysis of Nordic educational initiatives. Nordic Journal of Digital Literacy, 16(3), 138–155. https://doi.org/10.18261/issn.1891-943x-2021-03-02
Keller, D. (2022). The DSA and the future of platform governance. European Law Journal, 28(3), 356–374. https://doi.org/10.1111/eulj.12341
Kosinski, M., Stillwell, D., & Graepel, T. (2013). Private traits and attributes are predictable from digital records of human behavior. Proceedings of the National Academy of Sciences, 110(15), 5802–5805. https://doi.org/10.1073/pnas.1218772110
Kurashov, O. (2024). Artificial intelligence technology in Ukraine’s electoral system: Implementation prospects. Visegrad Journal on Human Rights, (3), 128–134. https://doi.org/10.61345/1339-7915.2024.3.18journal-vjhr.sk+1Ukrainian Scientific Periodicals+1
Kuznetsova, E., Makhortykh, M., Vziatysheva, V., Stolze, M., Baghumyan, A., & Urman, A. (2025). In generative AI we trust: Can chatbots effectively verify political information? Journal of Computational Social Science, 8(1), 1–31. https://doi.org/10.1007/s42001-024-00338-8IDEAS/RePEc+1SpringerLink+1
Lazer, D. M., Baum, M. A., Benkler, Y., Berinsky, A. J., Greenhill, K. M., Menczer, F., ... & Zittrain, J. L. (2018). The science of fake news. Science, 359(6380), 1094–1096. https://doi.org/10.1126/science.aao2998
Lee, J., & Park, H. (2023). Virtual candidates and real campaigns: AI avatars in South Korean politics. Technopolitica, 4(1), 45–61.
Lee, Y. J. (2022). Integrating AI literacy into K-12 education: The Taiwan model. International Journal of Educational Technology in Higher Education, 19, 58. https://doi.org/10.1186/s41239-022-00359-3
Lysetskyi, Y. M., & Starovoitenko, O. O. (2024). Secure software development. In Proceedings of the XIII International Scientific and Practical Conference “Social Ways of Training Specialists in the Social Sphere and Inclusive Education” (pp. 339–343). Prague, Czech Republic.
Martínez, L., & Gil, F. (2024). AI and electoral campaigns in Latin America. Latin American Political Studies, 18(1), 34–49.
Muravska, Y., & Slipchenko, T. (2024). Legal regulation of artificial intelligence in Ukraine and in the world. Actual Problems of Law, 1, 188. https://doi.org/10.35774/app2024.01.188
Nguyen, T. T., Nguyen, C. M., Nguyen, D. T., Nguyen, D. T., & Nahavandi, S. (2022). Blockchain-based solution for detecting deepfake videos. Future Generation Computer Systems, 134, 85–98. https://doi.org/10.1016/j.future.2022.03.005
Osavul. (2024). AI-powered disinformation analytics platform. Retrieved from https://osavul.com
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