از سیاست‌گذاری تا مسئولیت‌پذیری: مسیر تحول حکمرانی ‏هوش مصنوعی

نوع مقاله : مقاله پژوهشی

نویسنده

استادیار، پژوهشگاه علوم و فرهنگ اسلامی، قم، ایران.‏

10.22081/jislamicgo.2025.70830.1000

چکیده

هوش مصنوعی (AI) به عنوان یک فناوری انقلابی، تحول‌آفرین و برهم‌زننده، در حال دگرگونی دنیا است. حکمرانی هوش مصنوعی و ادغام آن در سیاست عمومی، از موضوعات مهم در بحث‌های امروزی است. استفاده‌ی بالقوه از هوش مصنوعی در چرخه‌ی سیاست عمومی، فرصت‌هایی را برای بهبود فرآیندهای تصمیم‌گیری دولت‌ها فراهم می‌کند. تجزیه و تحلیل انتقادی فناوری‌های هوش مصنوعی در سیاست‌گذاری عمومی برای درک تأثیر آن‌ها بر فرآیندهای تصمیم‌گیری و نابرابری‌های اجتماعی ضروری است. اگرچه ادارات دولتی، بنگاه‌های اقتصادی، سازمان‌های بین‌المللی و سایر طرفین، در حوزه‌ی هوش مصنوعی تلاش کرده‌اند، اما ادغام هوش مصنوعی و حکمرانی هنوز در مراحل اولیه‌ی توسعه قرار دارد. این پژوهش با استفاده از روش توصیفی-تحلیلی، و با هدف مطالعه بر روندها و چارچوب‌های حکمرانی هوش مصنوعی و سیاست‌گذاری عمومی، سعی دارد به بررسی چگونگی بهبود فرآیند و نتایج سیاست‌گذاری با استفاده از هوش مصنوعی بپردازد. هوش مصنوعی می‌تواند به سیاست‌گذاران در شناسایی نیازها، توسعه‌ی برنامه‌ها، پیش‌بینی نتایج و تحلیل اثربخشی سیاست‌ها کمک کند. مطالعات انجام‌شده نشان می‌دهد اسناد سیاستی در سراسر جهان بر پتانسیل هوش مصنوعی برای کمک به دستیابی به اهداف توسعه‌ی پایدار از جمله درمان بیماری‌های مزمن، کاهش تلفات جاده‌ای، مبارزه با تغییرات اقلیمی و پیش‌بینی تهدیدات سایبری کمک می‌کند. هوش مصنوعی نه تنها فرصت‌ها، بلکه خطرات و چالش‌هایی را نیز به همراه دارد. برخی از نگرانی‌ها شامل جابه‌جایی شغلی، سوگیری الگوریتمی، سوء‌استفاده از داده‌ها و تهدیدات امنیتی است. سیاست‌های هوش مصنوعی باید به این چالش‌ها رسیدگی کند و اطمینان حاصل کند که هوش مصنوعی به طور مسئولانه و اخلاقی توسعه و استفاده می‌شود.

کلیدواژه‌ها


عنوان مقاله [English]

The Path of Artificial Intelligence Governance ‎Transformation: From Policymaking to Accountability

نویسنده [English]

  • Ali Mirarab
Assistant Professor, Islamic Sciences and Culture Academy, Qom, Iran.‎ ‎alimirarab@isca.ac.ir
چکیده [English]

Artificial Intelligence (AI), as a revolutionary, transformative, and disruptive technology, is changing the world. AI governance and its integration into public policy are important topics in contemporary discussions. The potential use of AI in the public policy cycle provides opportunities to improve decision-making processes for governments. Critical analysis of AI technologies in public policymaking is essential to understand their impact on decision-making processes and social inequalities. Although government agencies, businesses, international organizations, and other stakeholders have made efforts in the field of AI, the integration of AI and governance is still in the early stages of development. This research, using a descriptive-analytical method, aims to study the trends and frameworks of AI governance and public policymaking, and examines how AI can improve policymaking processes and outcomes. AI can assist policymakers in identifying needs, developing programs, forecasting outcomes, and analyzing policy effectiveness. Studies show that policy documents around the world highlight the potential of AI to help achieve sustainable development goals, such as treating chronic diseases, reducing road fatalities, combating climate change, and predicting cybersecurity threats. AI not only offers opportunities but also brings risks and challenges. Some concerns include job displacement, algorithmic bias, data misuse, and security threats. AI policies must deal with these challenges and ensure that AI is developed and used responsibly and ethically.

کلیدواژه‌ها [English]

  • Artificial Intelligence
  • Public Policy
  • Governance
  • Ethics
  • Global ‎Competition.‎
  1. شیخ‌الاسلامی، خالد. (1398). درآمدی بر حکمرانی هوش مصنوعی. مطالعات سیاسی (گروه بنیادین حکومتی). تهران: مرکز پژوهش‌های مجلس شورای اسلامی.

    محمدی، مهدی؛ کاکاوندی، یوسف؛ شریفیان، امیر؛ محمدی، بهنام. (1399). روندهای حکمرانی هوش مصنوعی. تهران: دانش بنیان فناور.

    Ala-Pietilä, P., & Smuha, N. A. (2021). A framework for global cooperation on artificial intelligence and its governance. Reflections on artificial intelligence for humanity, pp. 237-265.

    Borgogno, O., & Colangelo, G. (2019). Data sharing and interoperability: Fostering innovation and competition through APIs. Computer Law & Security Review, 35(5), p. 105314.

    Borrás, S., & Edler, J. (Eds.). (2014). The governance of socio-technical systems: explaining change. Edward Elgar Publishing.

    Bresnahan, T. F., & Trajtenberg, M. (1995). General purpose technologies ʻengines of growthʼ? Journal of Econometrics 65(1), pp. 83–108.

    https://doi.org/10.1016/0304-4076(94)01598-T.

    Carabantes, M. (2020). Black-box artificial intelligence: an epistemological and critical analysis. AI & Soc (35), pp. 309–317. https://doi.org/10.1007/ s00146-019-00888–w

    Cath, C., Wachter, S., Mittelstadt, B., Taddeo, M., & Floridi, L. (2018). Artificial intelligence and the ‘good society’: the US, EU, and UK approach. Science and engineering ethics, 24, pp. 505-528.

    Chhotray, V., & Stoker, G. (2009). Governance theory and practice. A cross-disciplinary approach. London: Palgrave Macmillan.

    Cihon, P., Maas, M. M., & Kemp, L. (2020). Fragmentation and the Future: Investigating Architectures for International AI Governance. Global Policy, 11(5), pp. 545–556.

    Cotra, A. (2020). Draft report on AI timelines. LessWrong. Retrieved from: https://www.lesswrong.com/posts/KrJfoZzpSDpnrv9va/draft-report-on-ai-timelines.

    Dafoe, A. (2018). AI governance: A research agenda; future of humanity institute. Oxford, UK: University of Oxford.

    De Saille, S. (2015). Innovating innovation policy: the emergence of ‘Responsible Research and Innovation’. Journal of Responsible Innovation, 2(2), pp. 152-168.

    Dignum, V. (2019). Responsible artificial intelligence: how to develop and use AI in a responsible way (Vol. 1). Cham: Springer.

    Ding, J., & Dafoe, A. (2021, June). Engines of power: Electricity, AI, and general-purpose military transformations. arXiv.

    European Commission. (2018a). Artificial intelligence for Europe. Communication COM(2018) 237. Brussels: European Commission.

    European Commission. (2018b). Artificial intelligence: A European perspective. Luxembourg: Publications Office of the European Union.

    Fernandez-Cortez, V., Valle-Cruz, D., & Gil-Garcia, J. R. (2020). Can artificial intelligence help optimize the public budgeting process? Lessons about smartness and public value from the Mexican federal government. 2020 Seventh International Conference on EDemocracy & EGovernment (ICEDEG), pp. 312–315. https://doi.org/10.1109/ICEDEG48599.2020.9096745.

    Galanos, V. (2019). Exploring expanding expertise: artificial intelligence as an existential threat and the role of prestigious commentators, 2014–2018. Technology Analysis & Strategic Management, 31(4), pp. 421-432.

    Garfinkel, B. (2022). The impact of artificial intelligence: A historical perspective. In J. Bullock (Ed.), The Oxford Handbook of AI Governance. Oxford University Press.

    Gasser, U., & Almeida, V. A. (2017). A layered model for AI governance. IEEE Internet Computing, 21(6), pp. 58–62.

    Gritsenko, D., & Wood, M. (2020). Algorithmic governance: A modes of governance approach. Regulation & Governance, 6(1), pp. 45–62.

    Guihot, M., Matthew, A. F., & Suzor, N. P. (2017). Nudging robots: Innovative solutions to regulate artificial intelligence. Vand. J. Ent. & Tech. L, 20, 385.

    Hemphill, T. A. (2016). Regulating nanomaterials: A case for hybrid governance. Bulletin of Science, Technology & Society, 36(4), pp. 219–228.

    Janssen, M., Brous, P., Estevez, E., Barbosa, L. S., & Janowski, T. (2020). Data governance: Organising data for trustworthy artificial intelligence. Government Information Quarterly, 37(3), pp. 101493.

    Katzenbach, C., & Ulbricht, L. (2019). Algorithmic governance. Internet Policy Review 8(4), pp. 1–18.

    Kuhlmann, S., Stegmaier, P., & Konrad, K. (2019). The tentative governance of emerging science and technology—A conceptual introduction. Research policy, 48(5), pp. 1091-1097.

    Kuziemski, M., & Misuraca, G. (2020). AI governance in the public sector: Three tales from the frontiers of automated decision-making in democratic settings. Telecommunications policy, 44(6), 1 p. 01976.

    Lee, K. F. (2018). AI superpowers: China, Silicon Valley, and the new world order. Houghton Mifflin.

    Li, Y., Taeihagh, A., De Jong, M., & Klinke, A. (2021). Toward a commonly shared public policy perspective for analysing risk coping strategies. Risk analysis, 41(3), pp. 519–532. https://doi.org/10.1111/risa.13505

    Mazzucato, M. (2021). Mission economy: A moonshot guide to changing capitalism. London: Allen Lane.

    Mikhaylov, S. J., Esteve, M., & Campion, A. (2018). Artificial intelligence for the public sector: opportunities and challenges of cross-sector collaboration. Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences, 376(2128).

    North, D. C. (1991). Institutions. Journal of Economic Perspectives 5(1), pp. 97–112. http://www.jstor.org/stable/1942704.

    Rabesandratana, T. (2018). “Emmanuel Macron wants France to become a leader in AI and avoid ‘dystopia.” Science (30). https://doi.org/10.1126/science.aat7491

    Rahwan, I. (2018). Society-in-the-loop: Programming the algorithmic social contract. Ethics and Information Technology, 20(1), pp. 5–14.

    1. (1 September 2017). “Whoever leads in AI will rule the world’: Putin to Russian children on Knowledge Day.” Retrieved from:

    https://www.rt.com/news/401731-ai-rule-world-putin/.

    Schwab, K. (2017). The fourth industrial revolution. Crown Currency.

    Somers, J. (2017, April). Torching the modern-day library of Alexandria. The Atlantic. https://www.theatlantic.com/technology/archive/2017/04/the-tragedy-of-google-books/523320/

    Stilgoe, J., Owen, R., & Macnaghten, P. (2020). Developing a framework for responsible innovation. In The Ethics of Nanotechnology, Geoengineering, and Clean Energy (pp. 347-359). Routledge.

    Sun, T. Q., & Medaglia, R. (2019). Mapping the challenges of Artificial Intelligence in the public sector: Evidence from public healthcare. Government Information Quarterly, 36(2), pp. 368-383.

    Taeihagh, A., & Lim, H. S. M. (2019). Governing autonomous vehicles: emerging responses for safety, liability, privacy, cybersecurity, and industry risks. Transport reviews, 39(1), pp. 103-128.

    Taeihagh, A., Ramesh, M., & Howlett, M. (2021). Assessing the regulatory challenges of emerging disruptive technologies. In Regulation & Governance. https://doi.org/10.1111/rego.12392

    Valle-Cruz, D., Criado, J. I., Sandoval-Almazán, R., & Ruvalcaba-Gomez, E. A. (2020). Assessing the public policy-cycle framework in the age of artificial intelligence: From agenda-setting to policy evaluation. Government Information Quarterly, 37(4).

    Valle-Cruz, D., Criado, J. I., Sandoval-Almazán, R., & Ruvalcaba-Gomez, E. A. (2020). Assessing the public policy-cycle framework in the age of artificial intelligence: From agenda-setting to policy evaluation. Government Information Quarterly 37(4), 101509.

    WEF. (25 January 2018). “Theresa May’s Davos address in full.” Retrieved from: https://www.weforum.org/agenda/2018/01/theresa-may-davos-address/.

    Wirtz, B. 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), pp. 818–829.

    Young, M. M., Bullock, J. B., & Lecy, J. D. (2019). Artificial discretion as a tool of governance: a framework for understanding the impact of artificial intelligence on public administration. Perspectives on Public Management and Governance 2(4), pp. 301–313.