SÜRDÜRÜLEBİLİR KALKINMADA YAPAY ZEKANIN ROLÜ: AMAÇLAR İÇİN ETKİN POLİTİKA FORMASYONU

Öz

Küresel iklim krizinin hız kazanmasıyla birlikte sürdürülebilirlik kavramı, kalkınma yaklaşımında yerini edinmiştir. Sürdürülebilir kalkınma, etkin kaynak yönetimi, verimlilik, toplumsal ve çevresel değerleri öncüllerken, sorumlu üretimden cinsiyet eşitsizliğine kadar değişen geniş bir yelpazede birçok hedefin gerçekleşmesini amaçlar. Bu bağlamda Birleşmiş Milletler, uluslararası arenada kabul görmüş on yedi ana amaç belirlemiştir. Bu amaçlara ulaşmak üzere birçok politika aksiyonu benimsenmiş olmakla birlikte değişen dünya koşullarında ortaya çıkan yeni dinamikler, politika formasyonunu da hızla değiştirmektedir. Bu dinamiklerden en önemlisi ise hiç şüphesiz Dördüncü Sanayi Devrimi’nin ana bileşenlerinden biri olan ‘Yapay Zeka’dır. Yapay Zeka, bilgi toplama ve topladığı bilgiyi işleyerek insan gibi öğrenme ve problem çözme yeteneklerine sahip, makinelerin insansı görevleri gerçekleştirmelerine imkan tanıyan ve yeni girdi koşullarına uyum sağlamalarını mümkün kılan sistemdir. Ancak yapay zekanın sürdürülebilir kalkınma amaçları açısından kullanım alanları, yararları, zararlı olabileceği durumlar ve sosyoekonomik politika formasyonunu hangi yönlerde etkilediği konusundaki tartışmaların henüz sınırlı kaldığı görülmektedir. Bu çalışmada, yapay zekanın sürdürülebilir kalkınma amaçları ile ilişkisi, yararlı kullanım alanları, potansiyel riskleri ve önemli meydan okuma alanları ele alınırken, sosyoekonomik politika formasyonundaki yerinin nasıl olması gerektiğine yönelik değerlendirmelerde de bulunulmaktadır. Tüm bu tartışmaların bütüncül bir bakış açısıyla literatürde ilk kez ele alınıyor olması noktasında, çalışmanın ilgili literatüre katkı yapması hedeflenmektedir.

Anahtar Kelimeler

• Yapay Zeka
• Sürdürülebilir Kalkınma
• Politika Formasyonu

THE ROLE OF ARTIFICIAL INTELLIGENCE IN SUSTAINABLE DEVELOPMENT: EFFECTIVE POLICY FORMATION FOR ACHIEVING THE GOALS

Öz

The concept of sustainability made its ground in the development approach as the global climate crisis accelerated. While sustainable development prioritizes effective resource management, efficiency, social and environmental values, it aims to achieve many goals in a wide range ranging from responsible production to gender inequality. In this manner, the United Nations has determined seventeen globally recognized Sustainable Development Goals (SDGs). Although many policy actions have been adopted to achieve these goals, new dynamics emerging in changing world conditions are also rapidly changing policy formation. One of the most important of these dynamics is undoubtedly 'Artificial Intelligence' (AI), which is one of the main components of the Fourth Industrial Revolution. Artificial Intelligence is a system that has human-like learning and problem-solving abilities by collecting data and processing the information, allowing machines to perform human-like tasks and enabling them to adapt to new input conditions. However, it seems that discussions on the areas of use of artificial intelligence in terms of sustainable development goals, its benefits, its potential risks, and its effects on socioeconomic policy formation are still limited. In this study, while the relationship of artificial intelligence with sustainable development goals, its beneficial areas of use, potential risks and important challenge areas are discussed, evaluations are also made regarding its place within the framework of socioeconomic policy formation. As all these discussions are discussed for the first time in the literature from a holistic perspective, the study aims to contribute to the relevant literature.

Anahtar Kelimeler

• Artificial Intelligence
• Sustainable Development
• Policy Formation

Kaynakça

1. Abbass, H. A. (2019). Social integration of artificial intelligence: Functions, automation allocation logic and human-autonomy trust. Cognitive Computation, 11(2), 159–171. https://doi.org/10.1007/s12559-018-9619-0
2. Ahadi, N., Zanjanab, A. G., Sorooshian, S., Monametsi, G., Virutamesen, P., Wongpreedee, K., Deebhijarn, S. ve Taghipour, A. (2023). The outlook of ChatGPT, an AI-based tool adoption in Academia: Applications, challenges, and opportunities. TENCON 2023 - 2023 IEEE Region 10 Conference (TENCON). (Ss. 15-20).
3. Al Badi, F. K., Alhosani, K. A., Jabeen, F., Stachowicz-Stanusch, A., Shehzad, N. ve Amann, W. (2022). Challenges of AI adoption in the UAE healthcare. Vision: The Journal of Business Perspective, 26(2), 193 – 207. https://doi.org/10.1177/0972262920988398
4. Al-Emran, M. ve Griffy-Brown, C. (2023). The role of technology adoption in sustainable development: Overview, opportunities, challenges, and future research agendas. Technology in Society, 73 (102240), 1 – 6. https://doi.org/10.1016/j.techsoc.2023.102240
5. Alpaydın, E. (2013). Yapay öğrenme. Boğaziçi Üniversitesi Yayınevi.
6. Amankwah-Amoah, J. ve Lu, Y. (2024). Harnessing AI for business development: A review of drivers and challenges in Africa. Production Planning & Control, 35(13), 1551 – 1560. https://doi.org/10.1080/09537287.2022.2069049
7. Arslan, K. (2020). Eğitimde yapay zeka ve uygulamaları. Batı Anadolu Eğitim Bilimleri Dergisi, 11(1), 71 – 88.
8. Aylak, B. L., Oral, O. ve Yazıcı, K. (2021). Yapay zeka ve makine öğrenmesi tekniklerinin lojistik sektöründe kullanımı. El-Cezeri Fen ve Mühendislik Dergisi, 8(1), 74 – 93. https://doi.org/10.31202/ecjse.776314

9. BM. (2025a). The 17 goals. https://sdgs.un.org/goals (Erişim Tarihi: 29.01.2025).
10. BM. (2025b). Transforming our world: the 2030 Agenda for Sustainable Development. https://sdgs.un.org/2030agenda (Erişim Tarihi: 30.01.2025).
11. BM. (2025c). Promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levels. https://sdgs.un.org/goals/goal16 (Erişim Tarihi: 03.06.2025).
12. Brooks, C., Gherhes, C. ve Vorley, T. (2020). Artificial intelligence in the legal sector: Pressures and challenges of transformation. Cambridge Journal of Regions, Economy and Society, 13, 135–152. https://doi.org/10.1093/cjres/rsz026
13. Campion, A., Gasco-Hernandez, M., Jankin Mikhaylov, S., ve Esteve, M. (2022). Overcoming the challenges of collaboratively adopting artificial intelligence in the public sector. Social Science Computer Review, 40(2), 462-477. https://doi.org/10.1177/0894439320979953
14. Carrasquilla-Diaz, L., Luque-Pisciotti, A. ve Lagos-Gonzalez, E. (2024). AI adoption in Colombian legal practice: Challenges and opportunities. Procedia Computer Science, 241, 508 – 513.
15. Debnath, R., Creutzig, F., Sovacool, B. K. ve Shuckburgh, E. (2023). Harnessing human and machine intelligence for planetary-level climate action. NPJ Climate Action, 2(20). https://doi.org/10.1038/s44168-023-00056-3
16. Dünya Bankası. (2024). Pathways out of the polycrisis. World Bank Group. https://www.worldbank.org/en/publication/poverty-prosperity-and-planet (Erişim Tarihi: 03.06.2025).
17. Dünya Bankası. (2021). Hernssing artificial intelligence for development in the post-COVID-19 era: A review of national AI strategies and policies. Analytical Insights, Note 4 Washington, D.C.: World Bank Group. http://documents.worldbank.org/curated/en/487931621237422984/Harnessing-Artificial-Intelligence-for-Development-on-the-Post-COVID-19-Era-A-Review-of-National-AI-Strategies-and-Policies (Erişim Tarihi: 26.01.2025).
18. FAO. (2024). The state of food security and nutrition in the World 2024. https://openknowledge.fao.org/items/ebe19244-9611-443c-a2a6-25cec697b361 (Erişim Tarihi: 03.06.2025).
19. Guan, J. (2019). Artificial intelligence in healthcare and medicine: Promises, ethical challenges and governance. Chinese Medical Sciences Journal, 34(2), 76–83. https://doi.org/10.24920/003611
20. Hameed, M., Sharqi, S.S. ve Yaseen, Z.M. (2017). Application of artificial intelligence (AI) techniques in water quality index prediction: A case study in tropical region, Malaysia. Neural Computing & Application 28 (Suppl 1), 893–905. https://doi.org/10.1007/s00521-016-2404-7
21. Hill, T. (2018). How artificial intelligence is reshaping the water sector. Water Finance & Management. https://waterfm.com/artificial-intelligence-reshaping-water-sector/ (Erişim Tarihi: 02.02.2025).
22. Hossin, Md. S., Ulfy, M. A., Ali, I. ve Karim, Md. W. (2021). Challenges in adopting artificial intelligence (AI) in HRM practices: a study on Bangladesh perspective. International Fellowship Journal of Interdisciplinary Research, 1(1), 66 – 73. https://doi.org/10.5281/zenodo.4480245
23. Huyugüzel Kışla, G. Ş., İnce Yenilmez, M. ve Türkcan, B. (2022). Sürdürülebilirlik ve döngüsel ekonomi: pandemi sonrası dönem için öngörüler ve politika önerileri. Editörler: N. Merve Hamzaoğlu ve İsmail Ertek. Sürdürülebilir Kalkınma ve Ekonomi. İstanbul Kültür Üniversitesi Yayınları. Ss. 368 – 378.
24. Kuglitsch, M.M., Pelivan, I., ve Ceola, S. (2022). Facilitating adoption of AI in natural disaster management through collaboration. Nat Commun, 13, 1579. https://doi.org/10.1038/s41467-022-29285-6
25. Kurtuluş, Ö. (2023). Yapay zeka hangi alanlarda kullanılıyor? TÜBİTAK Bilim Genç https://bilimgenc.tubitak.gov.tr/makale/yapay-zeka-hangi-alanlarda-kullaniliyor (Erişim Tarihi: 01.02.2025)
26. Lamberti, M. J., Wilkinson, M., Donzanti, B. A., Wohlhieter, G. E., Parikh, S., Wilkins, R. G., ve Getz, K. (2019). A study on the application and use of Artificial Intelligence to support drug development. Clinical Therapeutics, 41(8), 1414–1426. https://doi.org/10.1016/j.clinthera.2019.05.018
27. Lant, K. (2018). Clean water AI puts prevention of waterborne disease in the palm of your hand. Environmental Monitor. https://www.fondriest.com/news/clean-water-ai-puts-prevention-waterborne-disease-palm-hand.htm (Erişim Tarihi: 02.02.2025).
28. McDougall, R. J. (2019). Computer knows best? The need for value-flexibility in medical AI. Journal of Medical Ethics, 45(3), 156–160. https://doi.org/10.1136/medethics-2018-105118
29. Mhlanga, D. (2021). Artificial intelligence in the industry 4.0, and its impact on poverty, innovation, infrastructure development, and the sustainable development goals: Lessons from emerging economies? Sustainability, 13(11), 5788. https://doi.org/10.3390/su13115788
30. Necula, S-C. (2023). Assessing the potential of artificial intelligence in advancing clean energy technologies in Europe: a systematic review. Energies, 16(22), 7633. https://doi.org/10.3390/en16227633
31. Neethirajan, S. (2024). Net zero dairy farming—advancing climate goals with big data and artificial intelligence. Climate, 12(2), 15. https://doi.org/10.3390/cli12020015
32. OECD. (2022a). OECD framework for the classification of AI systems. OECD Digital Economy Papers No. 323. https://oecd.ai/en/ai-publications/framework-classification (Erişim Tarihi: 01.02.2025).
33. OECD. (2022b). Measuring the environmental impacts of artificial intelligence compute and applications – the AI footprint. OECD Digital Economy Papers No. 341. https://oecd.ai/en/ai-publications/ai-footprint (Erişim Tarihi: 02.02.2025).
34. OECD. (2022c). The effects of AI on the working lives of women. https://www.oecd.org/en/publications/the-effects-of-ai-on-the-working-lives-of-women_14e9b92c-en.html (Erişim Tarihi: 02.02.2025).
35. OECD. (2024). Assessing potential future artificial intelligence risks, benefits and policy imperatives. OECD Artificial Intelligence Papers No. 27. https://oecd.ai/en/ai-publications/futures (Erişim Tarihi: 01.02.2025).
36. PWC. 2019. Sizing the prize: What’s the real value of AI for your business and how can you capitalise? https://www.pwc.com/gx/en/issues/analytics/assets/pwc-ai-analysis-sizing-the-prize-report.pdf (Erişim Tarihi: 26.01.2025).
37. Reddy, S. (2018). Use of artificial intelligence in healthcare delivery. In T. F. Heston (Eds.), eHealth-Making health care smarter. IntechOpen.
38. Russell, S., Dewey, D., ve Tegmark, M. (2015). Research priorities for robust and beneficial artificial intelligence. AI Magazine, 36(4), 105–114. https://doi.org/10.1609/aimag.v36i4.2577
39. Schrader, D. E. ve Ghosh, D. Proactively protecting against the singularity: ethical decision making in AI. In IEEE Security & Privacy, 16(3), 56-63. https://doi.org/10.1109/MSP.2018.2701169
40. Silvestro, D., Goria, S., Sterner, T. ve Antonelli, A. (2022). Improving biodiversity protection through artificial intelligence. Nature Sustainability, 5, 415 – 424. https://doi.org/10.1038/s41893-022-00851-6
41. Sun, T. Q., ve Medaglia, R. (2019). Mapping the challenges of artificial intelligence in the public sector: Evidence from public healthcare. Government Information Quarterly, 36(2), 368–383. https://doi.org/10.1016/j.giq.2018.09.008
42. Terzi, İ., Özgüven, M. M., Altaş, Z. ve Uygun, T. (2019). Tarımda yapay zeka kullanımı. International Erciyes Agriculture, Animal & Food Sciences Conference. Kayseri, Türkiye.
43. Thesmar, D., Sraer, D., Pinheiro, L., Dadson, N., Veliche, R., ve Greenberg, P. (2019). Combining the power of Artificial Intelligence with the richness of healthcare claims data: Opportunities and challenges. PharmacoEconomics, 37(6), 745–752. https://doi.org/10.1007/s40273-019-00777-6
44. Türkcan, B. (2024). Sustainable urban tourism from the perspectives of overtourism and smart tourism: a systematic literature review. Journal of Travel and Tourism Research, 25, 112 – 156.
45. Türkcan, B., Bucak, Ç., Huyugüzel Kışla, G. Ş., Yurteri Kösedağlı, B. ve Kışla, T. (2024). Sürdürülebilir kalkınma bağlamında ekonomik karmaşıklığın cinsiyet eşitsizliğine etkisi: panel veri analizleri. Bilgi Sosyal Bilimler Dergisi, 26(1), 23 – 64. https://doi.org/10.54838/bilgisosyal.1401773
46. UNDP. (2021). United Nations development programme strategic plan 2022 – 2025. https://strategicplan.undp.org/ (Erişim Tarihi: 30.01.2025).
47. UNDP. (2025). What are the Sustainable Development Goals? https://www.undp.org/sustainable-development-goals (Erişim Tarihi: 31.01.2025).
48. UNEP. (2025). Goal 6: Clean water and sanitation. https://www.unep.org/topics/sustainable-development-goals/why-do-sustainable-development-goals-matter/goal-6 (Erişim Tarihi: 03.06.2025).
49. UNESCO. (2025). Monitoring SDG 4: Quality education. https://www.unesco.org/gem-report/en/quality (Erişim Tarihi: 03.06.2025).
50. Wamba, S. ., Queiroz, M. M., Guthrie, C. ve Braganza, A. (2022). Industry experiences of artificial intelligence (AI): Benefits and challenges in operations and supply chain management. Production, Planning & Control, 33(16), 1493 – 1497. https://doi.org/10.1080/09537287.2021.1882695
51. Wang, K.; Zhao, Y.; Gangadhari, R.K. ve Li, Z. (2021). Analyzing the adoption challenges of the internet of things (IoT) and artificial intelligence (AI) for smart cities in China. Sustainability, 13, 10983. https://doi.org/10.3390/su131910983
52. Yıldız, A. (2022). Finans alanında yapay zeka teknolojisinin kullanımı: sistematik literatür incelemesi. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi. 52, 47 – 66. https://doi.org/10.30794/pausbed.1089134
53. Yiğitcanlar, T., Li, R. Y. M., Inkinen, T. ve Paz, A. (2022). Public perceptions on application areas and adoption challenges of AI in urban services. Emerging Science Journal, 6(6), 1199-1236. https://doi.org/10.28991/ESJ-2022-06-06-01
54. Yoshida, H. ve İnce Yenilmez, M. (2022). Artificial intelligence and the future of work in Japan. International Journal of Contemporary Economics and Administrative Sciences, 12(2), 784 – 798. https://doi.org/10.5281/zenodo.7513559