qainarQainar Journal of Social ScienceQainar Journal of Social Science2958-72122958-7220Q University10.58732/2958-7212-2025-4-64-81qainar-494Research ArticleСтатьиИскусственный интеллект как фактор укрепления устойчивости национальной безопасности: опыт СингаппураArtificial Intelligence as a Tool of National Security Resilience: Evidence from Singaporehttps://orcid.org/0009-0000-6921-9359АзатбековаА.AzatbekovaA.

бакалавр

Алматы, Казахстан

Aigerim Azatbekova, Bachelor

Almaty, Kazakhstan

a.azatbekova@gmail.comhttps://orcid.org/0009-0003-5639-9073СерикбаеваЗ.SerikbayevaZ.

бакалавр

Алматы, Казахстан

Zere Serikbayeva, Bachelor

Almaty, Kazakhstan

zereserikbaeva1@gmail.comhttps://orcid.org/0000-0001-7563-2254НышанбаевН.NyshanbayevN.

PhD, доцент

Алматы, Казахстан

Nurbolat Nyshanbayev, PhD, Associate Professor

Almaty, Kazakhstan

n.nyshanbayev@turan-edu.kzУниверситет ТуранКазахстанTuran UniversityKazakhstan202509012026446481Copyright © Азатбекова А., Серикбаева З., Нышанбаев Н., 20262026Азатбекова А., Серикбаева З., Нышанбаев Н.Azatbekova A., Serikbayeva Z., Nyshanbayev N.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.journal-kainar.kz/jour/article/view/494

В условиях ускоренной цифровизации и расширения применения искусственного интеллекта (ИИ) в критически важных секторах возрастает значимость формирования эффективных моделей управления искусственным интеллектом (далее – ИИ), ориентированных на обеспечение устойчивости национальной безопасности. Целью данного исследования является анализ рискориентированного подхода к управлению искусственным интеллектом в Сингапуре и оценка его вклада в укрепление устойчивости национальной безопасности в период 2020–2025 гг. Методологической основой исследования послужили качественный анализ нормативностратегических документов, сравнительный институциональный анализ, а также тематическое кодирование инструментов управления ИИ с позиций теории риск-ориентированного регулирования. Результаты исследования показывают, что сингапурская модель управления ИИ основана на сочетании «мягкого» регулирования, технической верификации и межсекторального взаимодействия, что позволяет минимизировать риски, связанные с киберугрозами, уязвимостью критической инфраструктуры и снижением общественного доверия, без ограничения инновационной активности. В 2023–2024 гг. уровень внедрения ИИ среди малых и средних предприятий увеличился более чем в три раза, а среди крупных компаний — более чем на 18 п.п. Доля работников, использующих ИИ-инструменты в профессиональной деятельности, достигла почти 74%, что свидетельствует о глубокой интеграции ИИ в социально-экономические процессы. Практическая значимость работы состоит в возможности адаптации сингапурской модели при разработке национальных систем управления ИИ в странах с высокой степенью цифровизации, включая Казахстан. 

In the context of accelerated digitalization and the expansion of the use of artificial intelligence (hereinafter – AI) in critical sectors, the importance of forming effective AI management models focused on ensuring the sustainability of national security is increasing. The purpose of this study is to analyze the risk-based approach to artificial intelligence management in Singapore and assess its contribution to strengthening national security resilience in the period 2020-2025. The methodological basis of the study was a qualitative analysis of regulatory and strategic documents, comparative institutional analysis, as well as thematic coding of AI management tools from the perspective of riskbased regulation theory. The results of the study show that Singapore's AI management model is based on a combination of "soft" regulation, technical verification, and intersectoral collaboration, which minimizes the risks associated with cyber threats, vulnerability of critical infrastructure, and reduced public trust, without limiting innovation activity. In 2023-2024, the level of AI adoption among small and medium—sized enterprises increased by more than three times, and among large companies - by more than 18 percentage points. The share of employees using AI tools in their professional activities has reached almost 74%, which indicates the deep integration of AI into socio-economic processes. The practical significance of the work lies in the possibility of adapting the Singapore model in the development of national AI management systems in countries with a high degree of digitalization, including Kazakhstan.

искусственный интеллектнациональная безопасностьрегулированиеумные технологиисоциальная устойчивостьсоциальный довериеСингапурArtificial IntelligenceNational SecurityRegulationSmart TechnologySocial SustainabilitySocial TrustSingaporeReferencesAllahrakha, N. (2024). UNESCO's AI Ethics Principles: Challenges and Opportunities. International Journal of Law and Policy, 2(9), 24-36. https://doi.org/10.59022/ijlp.225Allahrakha, N. (2024). UNESCO's AI Ethics Principles: Challenges and Opportunities. International Journal of Law and Policy, 2(9), 24-36. https://doi.org/10.59022/ijlp.225Bartneck, C., Lütge, C., Wagner, A., & Welsh, S. (2021). An introduction to ethics in robotics and AI (p.117). Springer Nature.Bartneck, C., Lütge, C., Wagner, A., & Welsh, S. (2021). An introduction to ethics in robotics and AI (p.117). Springer Nature.Bernd, W. W., Weyerer, J. C., & Sturm, B. J. (2020). The dark sides of artificial intelligence: An integrated AI governance framework for public administration. International Journal of Public Administration, 43(9), 818–829. https://doi.org/10.1080/01900692.2020.1749851Bernd, W. W., Weyerer, J. C., & Sturm, B. J. (2020). The dark sides of artificial intelligence: An integrated AI governance framework for public administration. International Journal of Public Administration, 43(9), 818–829. https://doi.org/10.1080/01900692.2020.1749851Cheng, J., & Zeng, J. (2022). Shaping AI’s Future? China in Global AI Governance. Journal of Contemporary China, 32, 794 - 810. https://doi.org/10.1080/10670564.2022.2107391Cheng, J., & Zeng, J. (2022). Shaping AI’s Future? China in Global AI Governance. Journal of Contemporary China, 32, 794 - 810. https://doi.org/10.1080/10670564.2022.2107391Cohen, T., & Suzor, N.P. (2024). Contesting the public interest in AI governance. Internet Policy Review, 13(3). https://doi.org/10.14763/2024.3.1794Cohen, T., & Suzor, N.P. (2024). Contesting the public interest in AI governance. Internet Policy Review, 13(3). https://doi.org/10.14763/2024.3.1794Floridi, L., Holweg, M., Taddeo, M., Amaya Silva, J., Mökander, J., & Wen, Y. (2022). capAIA Procedure for Conducting Conformity Assessment of AI Systems in Line with the EU Artificial Intelligence Act. Available at SSRN 4064091. https://doi.org/10.2139/ssrn.4064091Floridi, L., Holweg, M., Taddeo, M., Amaya Silva, J., Mökander, J., & Wen, Y. (2022). capAIA Procedure for Conducting Conformity Assessment of AI Systems in Line with the EU Artificial Intelligence Act. Available at SSRN 4064091. https://doi.org/10.2139/ssrn.4064091Infocomm Media Development Authority (IMDA). (2022). Annex B: Background on Singapore’s AI governance work.Infocomm Media Development Authority (IMDA). (2022). Annex B: Background on Singapore’s AI governance work.Infocomm Media Development Authority (IMDA). (2023). AI Verify Foundation: Technical overview and assurance framework.Infocomm Media Development Authority (IMDA). (2023). AI Verify Foundation: Technical overview and assurance framework.Kriebitz, A., Max, R., & Lütge, C. (2022). The German Act on Autonomous Driving: why ethics still matters. Philosophy & Technology, 35(2), 1-13. https://doi.org/10.1007/s13347-022-00526-2Kriebitz, A., Max, R., & Lütge, C. (2022). The German Act on Autonomous Driving: why ethics still matters. Philosophy & Technology, 35(2), 1-13. https://doi.org/10.1007/s13347-022-00526-2Kumar, S., & Narayanan, A. (2021). Human-centric AI governance in Asia. AI & Society. Lütge, C., & Uhl, M. (2021). Business Ethics: An Economically Informed Perspective. Oxford University Press, USAKumar, S., & Narayanan, A. (2021). Human-centric AI governance in Asia. AI & Society. Lütge, C., & Uhl, M. (2021). Business Ethics: An Economically Informed Perspective. Oxford University Press, USAMorley, J., Floridi, L., Kinsey, L., & Elhalal, A. (2019). From What to How: An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Practices. Science and Engineering Ethics, 26, 2141 - 2168. https://doi.org/10.1007/s11948-019-00165-5Morley, J., Floridi, L., Kinsey, L., & Elhalal, A. (2019). From What to How: An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Practices. Science and Engineering Ethics, 26, 2141 - 2168. https://doi.org/10.1007/s11948-019-00165-5OECD. (2020). Singapore’s model framework to balance innovation and trust in AI. OECD.AI Policy Observatory. Retrieved September 22, 2025, from https://oecd.ai/en/wonk/singapores-model-framework-to-balance-innovation-and-trust-in-aOECD. (2020). Singapore’s model framework to balance innovation and trust in AI. OECD.AI Policy Observatory. Retrieved September 22, 2025, from https://oecd.ai/en/wonk/singapores-model-framework-to-balance-innovation-and-trust-in-aPersonal Data Protection Commission (PDPC). (2020). Model AI governance framework (2nd ed.).Personal Data Protection Commission (PDPC). (2020). Model AI governance framework (2nd ed.).Personal Data Protection Commission (PDPC). (2020). Singapore’s approach to AI governance.Personal Data Protection Commission (PDPC). (2020). Singapore’s approach to AI governance.Radu, R. (2021). Steering the governance of artificial intelligence: National strategies in perspective. Policy and Society, 40(2), 178–193. https://doi.org/10.1080/14494035.2021.1929728Radu, R. (2021). Steering the governance of artificial intelligence: National strategies in perspective. Policy and Society, 40(2), 178–193. https://doi.org/10.1080/14494035.2021.1929728Smart Nation Singapore. (2023). National AI Strategy 2.0: AI for the public good, for Singapore and the world. Government of Singapore. https://file.go.gov.sg/nais2023.pdfSmart Nation Singapore. (2023). National AI Strategy 2.0: AI for the public good, for Singapore and the world. Government of Singapore. https://file.go.gov.sg/nais2023.pdfTaddeo, M., Ziosi, M., Tsamados, A., Gilli, L., & Kurapati, S. (2022). Artificial intelligence for national security: The predictability problem. Centre for Digital Ethics (CEDE) Research Paper No. Forthcoming.Taddeo, M., Ziosi, M., Tsamados, A., Gilli, L., & Kurapati, S. (2022). Artificial intelligence for national security: The predictability problem. Centre for Digital Ethics (CEDE) Research Paper No. Forthcoming.Wirtz, B. W., Weyerer, J. C., & Kehl, I. (2022). Governance of artificial intelligence: A risk and guideline-based integrative framework. Government Information Quarterly, 39, 101685. https://doi.org/10.1016/j.giq.2022.101685Wirtz, B. W., Weyerer, J. C., & Kehl, I. (2022). Governance of artificial intelligence: A risk and guideline-based integrative framework. Government Information Quarterly, 39, 101685. https://doi.org/10.1016/j.giq.2022.101685Yerlikaya, S., & Erzurumlu, Y.Ö. (2021). Artificial Intelligence in Public Sector: A Framework to Address Opportunities and Challenges. Studies in computational intelligence, 935, 201-216. https://doi.org/10.1007/978-3-030-62796-6_11Yerlikaya, S., & Erzurumlu, Y.Ö. (2021). Artificial Intelligence in Public Sector: A Framework to Address Opportunities and Challenges. Studies in computational intelligence, 935, 201-216. https://doi.org/10.1007/978-3-030-62796-6_11

The authors declare that there are no conflicts of interest present.