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هوش مصنوعی و مسئولیت در داوری تغییرات اقلیمی | ||
| مدل سازی و مدیریت آب و خاک | ||
| مقاله 4، دوره 5، ویژه نامه: تغییر اقلیم و تاثیر آن بر آب و خاک، 1404، صفحه 49-61 اصل مقاله (683.12 K) | ||
| نوع مقاله: Special issue on "Climate Change and Effects on Water and Soil" | ||
| شناسه دیجیتال (DOI): 10.22098/mmws.2025.17643.1611 | ||
| نویسندگان | ||
| Jawad Abdulmonam Yaheya1؛ Rajha M. Shehab2؛ Rafid Ali Laftah Hamad3؛ Jassim Mohamed Brieg4؛ Al-Sarraf Nazar Mostafa Jawad5؛ عطا امینی* 6 | ||
| 1Al-Turath University, Baghdad | ||
| 2Al-Mansour University College, Baghdad 10067, Iraq | ||
| 3Al-Rafidain University College Baghdad 10064, Iraq | ||
| 4Madenat Alelem University College, Baghdad 10006, Iraq | ||
| 5Al-Rafidain University College, Baghdad 10064, Iraq | ||
| 6مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی کردستان | ||
| چکیده | ||
| Artificial intelligence (AI) offers valuable opportunities to improve analytical processing of complex datasets, enhance predictive capabilities, and streamline procedural tasks. In the field of arbitration, these advantages translate into increased efficiency, particularly in complex and data-heavy cases such as those involving climate change liability. However, the decentralized and rapidly evolving nature of AI raises critical concerns about accountability, the allocation of liability, and transparency, areas where existing legal systems are still largely unprepared. This research explores the application of AI in the arbitration of climate change liability. It focuses on the transformative impact of AI tools on decision-making processes, examines how responsibility is shared among developers, users, and arbitration institutions, and discusses the ethical and regulatory implications of AI integration. Data shows a rising trend in the use of AI in arbitration. In the early stages, only 4–8% of cases employed simple AI technologies, primarily for document review. However, with the development of advanced machine learning algorithms and legal tech platforms, the proportion of AI-assisted cases has increased significantly. By 2018–2019, around 40% of arbitration cases incorporated predictive modeling tools, reflecting growing confidence in AI’s ability to detect patterns, predict outcomes, and support arbitrators in delivering fair and informed awards. To harness AI’s benefits responsibly, stakeholders must prioritize transparency, adopt international regulatory standards, and address ethical concerns such as bias and accountability. Establishing clear guidelines for AI use in arbitration will be essential to ensure fairness, maintain public trust, and manage the evolving legal landscape surrounding artificial intelligence. | ||
| کلیدواژه‌ها | ||
| هوش مصنوعی؛ داوری؛ مسئولیت؛ اخلاق؛ چارچوب‌های مقرراتی؛ کاهش سوگیری | ||
| مراجع | ||
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References Alizamir, M., Wang, M., Adnan Ikram, R. M., Kim, S., Ahmed, K. O., & Heddam, S. (2024). Developing an efficient explainable artificial intelligence approach for accurate reverse osmosis desalination plant performance prediction: Application of SHAP analysis. Engineering Applications of Computational Fluid Mechanics, 18(1), 2422060. doi: 10.1080/19942060.2024.2422060 Amini, A., Ali, T. M., Ghazali, A. H. B., & Huat, B. K. (2009). Adjustment of peak streamflows of a tropical river for urbanization. American Journal of Environmental Sciences, 5(3), 285–294. doi: 10.3844/ajessp.2009.285.294 Bakošová, L. (2020). Ethical and legal aspects of the use of artificial intelligence in health and nursing care. Studia Iuridica Cassoviensia, 8. doi: 10.33542/SIC2020-2-01 Chattopadhyay, S., & Edwards, D. R. (2016). Long-term trend analysis of precipitation and air temperature for Kentucky, United States. Climate, 4(1), 10. doi: 10.3390/cli4010010 Čerka, P., Grigienė, J., & Sirbikytė, G. (2015). Liability for damages caused by artificial intelligence. Computer Law & Security Review, 31(3), 376–389. doi: 10.1016/j.clsr.2015.03.008 Cerf, M., Matz, S.C. & MacIver, M.A. Participating in a climate futures market increases support for costly climate policies. Nat. Clim. Chang. 13, 511–512 (2023). doi: 10.1038/s41558-023-01677-6 Cheong, S.-M., Sankaran, K., & Bastani, H. (2022). Artificial intelligence for climate change adaptation. WIREs Data Mining and Knowledge Discovery, 12(5), e1459. doi: 10.1002/widm.1459 Danila Kirpichnikov, A. P., Grebneva, Y., & Okagbue, H. (2020). Criminal liability of the artificial intelligence. E3S Web of Conferences, 159, 04025. doi: 10.1051/e3sconf/202015904025 Dhar, P. (2020). The carbon impact of artificial intelligence. Nature Machine Intelligence, 2(8), 423–425. doi: 10.1038/s42256-020-0219-9 Diab, M. F. S. (2024). Criminal liability for artificial intelligence and autonomous systems. American Journal of Society and Law, 3(1), 14–18. doi: 10.54536/ajsl.v3i1.2481 Esmaeili, S., Bahrami, J., & Kamali, B. (2024). The contributions of natural and anthropogenic climate change on water resources reduction in Zarrinehroud basin of Lake Urmia. Advances in Civil Engineering and Environmental Science, 1(1), 1–14. doi: 10.22034/acees.2024.195339 Gharibreza, M., Nasrollahi, A., Afshar, A., Amini, A., & Eisaei, H. (2018). Evolutionary trend of the Gorgan Bay (southeastern Caspian Sea) during and post the last Caspian Sea level rise. Catena, 166, 339–348. doi: 10.1016/j.catena.2018.04.016 Gouiffès, L., & Ordonez, M. (2022). Climate change in international arbitration, the next big thing? Journal of Energy & Natural Resources Law, 40(2), 203–224. doi: 10.1080/02646811.2021.1959158 Halder, B., Chatterjee, P., Rana, B., Bandyopadhyay, J., Pande, C. B., Ahmed, K. O., Elkhrachy, I., Radwan, N. (2024). Delineating the climate change impacts on urban environment along with heat stress in the Indian tropical city. Physics and Chemistry of the Earth, 136, 103745. doi: 10.1016/j.pce.2024.103745 Hamza, A., Hama, B. H., Karim, M. M., & Ahmed, K. (2024). Water quality assessment for Qaladze Water Treatment Plant, Sulaymaniyah Governorate, Kurdistan Region, Iraq. Advances in Civil Engineering and Environmental Science, 1(1), 15–24. doi: 10.22034/acees.2024.464631.1004 Huntingford, C., Jeffers, E. S., Bonsall, M. B., Christensen, H. M., Lees, T., & Yang, H. (2019). Machine learning and artificial intelligence to aid climate change research and preparedness. Environmental Research Letters, 14(12), 124007. doi: 10.1088/1748-9326/ab4e55 Hussein, A.-K. J., Assaf, A. M., Mansour, A. F., & Jalal, B. K. (2024). Legal liability arising from artificial intelligence activities. Journal of Ecohumanism, 3(6), 338–346. doi: 10.62754/joe.v3i6.4006 Kārkliņš, J. (2020). Artificial intelligence and civil liability. Journal of the University of Latvia. Law, (13), 164–183. doi: 10.22364/jull.13.10 Malhoutra, A., & Ahmad, F. (2022). Artificial intelligence and international arbitration. Journal of Law Studies, 27(2), 258–281. doi: 10.14210/nej.v27n2.p258-281 Maliha, G., Gerke, S., Cohen, I. G., & Parikh, R. B. (2021). Artificial intelligence and liability in medicine: Balancing safety and innovation. The Milbank Quarterly, 99(3), 629–647. doi: 10.1111/1468-0009.12504 Moghayedi, A., Michell, K., & Awuzie, B. O. (2024). Analysis of the drivers and barriers influencing artificial intelligence for tackling climate change challenges. Smart and Sustainable Built Environment. Advance online publication. doi: 10.1108/SASBE-05-2024-0148 Saklani, N., & Bade, K. (2024). Footprints of artificial intelligence in climate change. International Journal for Research in Applied Science and Engineering Technology, 12(IV), 4972–4975. doi: 10.22214/ijraset.2024.61023 Nordgren, A. (2023). Artificial intelligence and climate change: Ethical issues. Journal of Information, Communication and Ethics in Society, 21(1), 1–15. doi: 10.1108/JICES-11-2021-0106 Nurakhmetova, G. G., Saparbekova, Z. S., & Suleimenova, S. Z. (2024). Prospects for the use of artificial intelligence in arbitration. Bulletin of L.N. Gumilyov Eurasian National University. Law Series, 147(2), 188–197. doi: 10.32523/2616-6844-2024-147-2-188-197 Othman Ahmed, K., & Ahmed Hussein, T. (2022). Contemporary trends toward environmental issues in the Kurdistan Region of Iraq. Prace i Studia Geograficzne. Sookyoung, L. (2024). A study on civil liability of artificial intelligence. Minsa Beophak, 107, 225–261. Simlinger, F., & Mayer, B. (2023). Allocating Climate Responsibility in International Arbitration. Climate Law Journal, 13(1), 45–68. doi: 10.1163/18786561-13010003
Sukanya, S., & Joseph, S. (2022). Climate change impacts on water resources: An overview. Visualization Techniques for Climate Change With Machine Learning and Artificial Intelligence, 55-76. doi: 10.1016/B978-0-323-99714-0.00008-X Stein, A. L. (2020). Artificial intelligence and climate change. Energy Engineering (Energy) eJournal. Talebian, S., Golkarieh, A., Eshraghi, S., Naseri, M., & Naseri, S. (2025). Artificial intelligence impacts on architecture and smart built environments: A comprehensive review. Advances in Civil Engineering and Environmental Science, 2(1), 45–56. doi: 10.22034/acees.2025.488106.1013 Varvaštian, S., & Kalunga, F. K. (2020). Transnational corporate liability for environmental damage and climate change: Reassessing access to justice after Vedanta v. Lungowe. Transnational Environmental Law, 9, 323–345. Wang, R., Li, L., Gentine, P., Zhang, Y., Chen, J., Chen, X., Chen, L., Ning, L., Yuan, L., & Lü, G. (2022). Recent increase in the observation-derived land evapotranspiration due to global warming. Environmental Research Letters, 17(2), 024020. doi: 10.1088/1748-9326/ac4291 Yahya, B. M. (2023). Studying the global climate changes using artificial intelligence: An overview. Al-Rafidain Engineering Journal (AREJ), 28(2), 296–309. doi: 10.33899/rengj.2023.137503.1222 | ||
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