DAVLAT BOSHQARUVIDA GIBRID INTELLEKT ASOSIDA METADIALOGIK QAROR QABUL QILISHNI O‘RGANISH

DAVLAT BOSHQARUVIDA GIBRID INTELLEKT ASOSIDA METADIALOGIK QAROR QABUL QILISHNI O‘RGANISH

Authors

  • Mamatraximov Xudoyor Nurmamatovich Inson Resurslarini Rivojlantirish (Human Resource Development)

Keywords:

gibrid intellekt, metadialogik yondashuv, davlat boshqaruvi, qaror qabul qilish, sun’iy intellekt, inson-AI hamkorligi, refleksiv dialog

Abstract

Zamonaviy davlat boshqaruvida sun’iy intellekt texnologiyalarining jadal joriy etilishi qaror qabul qilish jarayonlarini tubdan o‘zgartirmoqda. O‘zbekiston Respublikasining 2030-yilgacha sun’iy intellektni rivojlantirish strategiyasi va tegishli davlat dasturlari davlat idoralarida AI vositalarini keng qo‘llashni nazarda tutadi, ammo inson va AI o‘rtasidagi hamkorlik sifati, xususan, metadialogik refleksiya mexanizmlari yetarli darajada o‘rganilmagan. Ushbu tadqiqot davlat boshqaruvida gibrid intellekt (inson-AI hamkorligi) asosida metadialogik qaror qabul qilish jarayonlarini o‘rganish va O‘zbekiston sharoitida samarali modellar ishlab chiqishni maqsad qiladi. Tadqiqot aralash metodlar (mixed-methods) yondashuviga asoslanadi: miqdoriy bosqichda A/B testing va dialog tahlili (sentiment va semantik modellar yordamida) o‘tkaziladi, sifatli bosqichda esa davlat idoralari xodimlari bilan chuqur intervyu va fokus-guruh suhbatlari olib boriladi. Tadqiqot namunasiga Toshkent va viloyatlardagi davlat organlari (sog‘liqni saqlash, ta’lim, iqtisodiyot va boshqaruv sohalari) xodimlaridan 80–120 nafar mutaxassis jalb qilinadi. Metadialogik jarayonlar maxsus refleksiv indekslar orqali baholanadi, shu bilan birga etika, algoritmik bias va xodimlar malakasi to‘siqlari alohida tekshiriladi. Natijalar shuni ko‘rsatdiki, metadialogik yondashuv gibrid qaror qabul qilish jarayonida sinergiya effekti yaratib, umumiy samaradorlikni 20–35 foizga oshirishi, AI ning xatolari va insonning avtomatlashtirishga haddan tashqari ishonchini (automation bias) sezilarli darajada kamaytirishi mumkin. O‘zbekiston kontekstida asosiy cheklovlar xodimlarning AI bilan ishlash malakasi pastligi, infratuzilma cheklovlari va madaniy-texnologik moslashuv muammolari bo‘lib chiqdi. Shu bilan birga, mavjud davlat strategiyalari va “Besh million sun’iy intellekt yetakchilari” dasturi bu to‘siqlarni bartaraf etish uchun yetarli zamin yaratadi. Tadqiqot davlat boshqaruvida mas’uliyatli va samarali gibrid intellektni joriy etish uchun amaliy yo‘l xaritalari, trening dasturlari va siyosiy tavsiyalar taklif etadi. Ilmiy jihatdan esa metadialogik yondashuvni davlat boshqaruvi kontekstiga moslashtirgan yangi nazariy model ishlab chiqiladi, bu model O‘zbekistonning raqamli transformatsiya va barqaror rivojlanish maqsadlariga, shu jumladan mas’uliyatli AI tamoyillariga muvofiq hissa qo‘shadi.

References

Ahmad, S. et al. (2025) “Green Human Resource Management: Analyzing sustainable practices and organizational impact through a Word2Vec approach,” Green Technologies and Sustainability. KeAi Communications Co. Available at: https://doi.org/10.1016/j.grets.2025.100224.

Bhuvaneswari, E. et al. (2025a) “A human-centered hybrid AI framework for optimizing emergency triage in resource-constrained settings,” Intelligence-Based Medicine, 12. Available at: https://doi.org/10.1016/j.ibmed.2025.100311.

Bhuvaneswari, E. et al. (2025b) “A human-centered hybrid AI framework for optimizing emergency triage in resource-constrained settings,” Intelligence-Based Medicine, 12. Available at: https://doi.org/10.1016/j.ibmed.2025.100311.

Dastur (2025) Besh million sun’iy intellekt yetakchilari. Available at: https://aileaders.uz/.

Oʻzbekiston Respublikasi Prezidentining qarori (2024) Sunʼiy intellekt texnologiyalarini 2030-yilga qadar rivojlantirish strategiyasini tasdiqlash toʻgʻrisida. Available at: https://lex.uz/uz/docs/-7158604 (Accessed: January 26, 2026).

Oʻzbekiston Respublikasi Vazirlar Mahkamasining qarori (2025) 2025-2026-yillarda sunʼiy intellekt texnologiyalari sohasida ustuvor loyihalarni amalga oshirish chora-tadbirlari toʻgʻrisida. Available at: https://lex.uz/docs/-7621993 (Accessed: January 26, 2026).

Przegalinska, A. et al. (2025) “Collaborative AI in the workplace: Enhancing organizational performance through resource-based and task-technology fit perspectives,” International Journal of Information Management, 81. Available at: https://doi.org/10.1016/j.ijinfomgt.2024.102853.

Somabut, A. et al. (2025) “Preparing for the AI era: Science teachers’ readiness and professional development needs for generative AI integration in secondary education,” Social Sciences & Humanities Open, 12, p. 102259. Available at: https://doi.org/10.1016/J.SSAHO.2025.102259.

Úbeda-García, M. et al. (2025a) “Artificial intelligence, knowledge and human resource management: A systematic literature review of theoretical tensions and strategic implications,” Journal of Innovation & Knowledge, 10(6), p. 100809. Available at: https://doi.org/10.1016/J.JIK.2025.100809.

Úbeda-García, M. et al. (2025b) “Artificial intelligence, knowledge and human resource management: A systematic literature review of theoretical tensions and strategic implications,” Journal of Innovation and Knowledge, 10(6). Available at: https://doi.org/10.1016/j.jik.2025.100809.

Vera, C.L. et al. (2026) “Generative AI and the algorithmic workplace: A bibliometric and conceptual analysis of its impact on organisational decision-making and work design,” Journal of Open Innovation: Technology, Market, and Complexity, 12(1), p. 100710. Available at: https://doi.org/10.1016/j.joitmc.2025.100710.

Zaidan, E. et al. (2025) “Hybrid Global Governance for Responsible and Inclusive Artificial Intelligence: Proposing a New Sustainable Development Goal 18,” Technology in Society, p. 103159. Available at: https://doi.org/10.1016/j.techsoc.2025.103159.

Downloads

Published

2026-04-01
Loading...