DAVLAT BOSHQARUVIDA ALGORITMIK QARORLAR TA’SIRIDA FUQAROLARNING HUQUQLARINI TA’MINLASHNING HUQUQIY KAFOLATLARI

Авторы

  • Shohruh Ochilov Toshkent davlat yuridik universiteti

Ключевые слова:

algoritmik qaror qabul qilish, sun’iy intellekt, davlat boshqaruvi, shaffoflik, tushuntirish mumkinligi, algoritmik tarafkashlik, inson nazorati, konstitutsiyaviy huquqlar

Аннотация

Maqolada davlat boshqaruvida sun’iy intellekt va texnologiyalarga asoslangan qaror qabul qilishda algoritmlarining o‘rni, afzalliklari hamda ularni qo‘llash bilan bog‘liq huquqiy va axloqiy muammolar tahlil qilinadi. Tadqiqot doirasida algoritmik qarorlarning shaffofligi va tushuntirilishi, ma’muriy tartib-taomillarda adolat va hisobdorlikni ta’minlash, algoritmik tarafkashlik va kamsitishning oldini olish, shuningdek, insonning avtomatlashtirilgan tizimlar xulosalariga ortiqcha ishonishi bilan bog‘liq muammolar o‘rganiladi. Mazkur masalalar xalqaro tajriba misolida yoritilib, davlat boshqaruvida algoritmlardan foydalanish jarayonida qonuniylik, inson huquqlarini himoya qilish va davlat organlarining mas’uliyatini ta’minlashga qaratilgan huquqiy mexanizmlarni takomillashtirish bo‘yicha ilmiy-amaliy takliflar ishlab chiqiladi.

Скачивания

Данные по скачиваниям пока не доступны.

Биография автора

  • Shohruh Ochilov, Toshkent davlat yuridik universiteti

    Yoshlar masalalari va sportni ommalashtirish boshqarmasi xodimi

Библиографические ссылки

[1] Rechtbank Den Haag. ECLI:NL:RBDHA:2020:865 https://uitspraken.rechtspraak.nl/details?id=ECLI:NL:RBDHA:2020:1878

[2] https://en.wikipedia.org/wiki/Non-ministerial_government_department

[3] Kroll, “Accountable Algorithms,” 633–705.

[4] Yeung, “Algorithmic Regulation,” 505–23

[5] Brent Mittelstadt, “Principles Alone Cannot Guarantee Ethical AI,” Nature Machine Intelligence 1, no. 11 (2019): 501–07, https://doi.org/10.1038/s42256-019-0114-4.

[6] Binns, Reuben. “Fairness in Machine Learning: Lessons from Political Philosophy.” Proceedings of the 2018 Conference on Fairness, Accountability, and Transparency 81, 2018: 149–59.

[7] Violations Impact Police Data, Predictive Policing Systems, and Justice.” New York University Law Review Online 94, 2019: 192–233.

[8] Danielle Keats Citron and Frank Pasquale, “The Scored Society: Due Process for Automated Predic-tions,” Washington Law Review 89, no. 1 (2014): 24

[9] The Income Compliance Program, known as Robodebt, ended in November 2019. We’ve refunded people who paid money back on robodebts. https://www.servicesaustralia.gov.au/information-about-robodebt?context=60271

[10] https://lex.uz/uz/docs/8008401

[11] Sandra Wachter et al., “Why a Right to Explanation of Automated Decision-Making Does Not Exist in the General Data Protection Regulation,” International Data Privacy Law 7, no. 2 (2017): 76–99, https://doi.org/10.1093/idpl/ipx005.

[12] Lilian Edwards and Michael Veale, “Slave to the Algorithm? Why a ‘Right to an Explanation’ Is Prob-ably Not the Remedy You Are Looking For,” Duke Law & Technology Review 16, no. 1 (2017): 38–40.

Опубликован

2026-08-25