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Yapay Zeka Yoksulluğu Bitirebilir mi? Yoksulluğun Azaltılmasında Yapay Zekanın Rolü

Year 2024, Volume: 8 Issue: 2, 38 - 52
https://doi.org/10.70989/scd.1484258

Abstract

Yapay zeka, hem söylem hem de eylem olarak gündelik hayatımızın bir parçası haline gelmiştir. Teknolojik gelişmeler, küresel ekonominin iyileşmesinde önemli bir rol oynamaktadır. Yoksulluk, bu gelişmeler kapsamında, en azından çok temel ihtiyaçların karşılanması noktasında oransal olarak azalmış olsa da, dünyanın en kronik ve önemli sorunlarından biri olmaya devam etmektedir. Bu çalışmada, yoksullukla mücadelede yapay zekanın rolü ele alınmaktadır. Bu bağlamda mikrofinans, tarım, sağlık ve eğitim gibi çeşitli alanlarda yapay zekanın yoksullukla mücadelede oynadığı roller detaylı bir şekilde incelenmektedir. Yapay zekanın bu alanda önemli işlevler gördüğü ve göreceği vurgulanmakla birlikte, bu katkının veya rolün kaçınılmaz ve zorunlu olmayabileceği; siyasi faktörler ve evrenimizin biyofiziksel sınırları gibi şartların da kritik bir rol oynadığına dikkat çekilmektedir.

Ethical Statement

Etik izin gerektirecek bir çalışma değildir.

Supporting Institution

yoktur.

References

  • Alpaydin, E. (2020). Introduction to machine learning. MIT press.
  • Ashta, A., & Herrmann, H. (2021). Artificial intelligence and fintech: An overview of opportunities and risks for banking, investments, and microfinance. Strategic Change, 30(3), 211-222.
  • Bacastow, T. S., & Bellafiore, D. (2009). Redefining geospatial intelligence. American Intelligence Journal, 27(1), 38-40.
  • Bennington-Castro, J. (2017). “AI Is a Game-Changer in the Fight Against Hunger and Poverty. Here’s Why,” NBC News. https://www.nbcnews.com/mach/tech/ai-game-changerfight-against-hunger-poverty-here-s-why-ncna774696
  • Blain, L. (2024, March 01). Elon Musk: AI will run out of electricity and transformers in 2025., https://newatlas.com/technology/elon-musk-ai/
  • Case, A., & Kraftman, L. (2024). Health inequalities. Oxford Open Economics, 3(Supplement_1), i499-i528.
  • Cheng, X. et al (2021). Pursuing sustainable development goals: a review of renewable energy and poverty alleviation nexus. Environmental Development, 40, 100679.
  • Chowdhary, K. R. (2020). Fundamentals of artificial intelligence. New Delhi: Springer India.
  • Coelho, A.L.d.F., de Oliveira, T.F., Netto, M.N. (2022). Platforms, Applications, and Software. In: Marçal de Queiroz, D., M. Valente, D.S., de Assis de Carvalho Pinto, F., Borém, A., Schueller, J.K. (Eds.) Digital Agriculture. Springer, Cham. https://doi.org/10.1007/978-3-031-14533-9_15
  • DeLay, N., Mintert, J., & Thompson, N. (2021). Farm Data Collection and Software Adoption in Commercial Scale US Corn-Soybean Farms. In Western Economics Forum (Vol. 19, No. 2, pp. 12-19).
  • Dellosa, J. T., & Palconit, E. C. (2021, September). Artificial Intelligence (AI) in renewable energy systems: A condensed review of its applications and techniques. In 2021 IEEE International Conference on Environment and Electrical Engineering and 2021 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe) (pp. 1-6). IEEE.
  • Derrick, M. (2024). AI Critical to Success of Energy Sector, says Goldman Sachs. Energy Magazine. https://energydigital.com/articles/ai-critical-to-success-of-energy-sector-says-goldman-sachs Dormehl, L. (2017, April 24). To feed a growing population, scientists want to unleash AI on agriculture. Digital Trends. Retrieved from https://www.digitaltrends.com/cool-tech/future-of-food-carnegie-mellon-farming-project/
  • Engstrom, R., Hersh, J., & Newhouse, D. (2022). Poverty from space: Using high resolution satellite imagery for estimating economic well-being. The World Bank Economic Review, 36(2), 382–412. https://doi.org/10.1093/wber/lhab015
  • Forbes. (2024). Billionaires. Forbes. https://www.forbes.com/billionaires/ Głogowski, A. (2022). Systemic and cyber risk: the two monsters of financial system. In Digital Finance and the Future of the Global Financial System (pp. 199-212). Routledge.
  • González-Eguino, M. (2015). Energy poverty: An overview. Renewable and Sustainable Energy Reviews, 47, 377–385. doi:10.1016/j.rser.2015.03.013
  • Goralski, M. A., & Tan, T. K. (2022). Artificial Intelligence and Poverty Alleviation: Emerging Innovations and Their Implications for Management Education and Sustainable Development, The International Journal of Management Education (20:3), Elsevier, p. 100662. https://doi.org/10.1016/J.IJME.2022.100662
  • Grimmer, J., Roberts, M. E., & Stewart, B. M. (2021). Machine learning for social science: An agnostic approach. Annual Review of Political Science, 24, 395-419.
  • Guo, J., & Li, B. (2018). The application of medical artificial intelligence technology in rural areas of developing countries. Health equity, 2(1), 174-181.
  • Hanna, N. (2018) A role for the state in the digital age, Journal of Innovation and Entrepreneurship, Vol. 7, 5. 10.1186/s13731-018-0086-3.
  • He, J., Baxter, S. L., Xu, J., Xu, J., Zhou, X., & Zhang, K. (2019). The practical implementation of artificial intelligence technologies in medicine. Nature medicine, 25(1), 30-36.
  • Hall, O., Dompae, F., Wahab, I., & Dzanku, F. M. (2023). A review of machine learning and satellite imagery for poverty prediction: Implications for development research and applications. Journal of International Development, 35(7), 1753–1768.
  • Hickel, J. (2016). The true extent of global poverty and hunger: Questioning the good news narrative of the Millennium Development Goals. Third World Quarterly.
  • Holmes, W., & Tuomi, I. (2022). State of the art and practice in AI in education. European Journal of Education, 57, 542–570. https://doi.org/10.1111/ejed.12533
  • Hr, Ananya; Majhi, Siddharth; Mukherjee, Arindam; and Bala, Pradip Kumar, "Artificial Intelligence and Poverty Alleviation: A Review" (2022). ACIS 2022 Proceedings. 78. https://aisel.aisnet.org/acis2022/78 IBM. (2023, August). Generative AI for the Energy Industry: IBM Industry Point-of-View International Energy Agency (IEA). (2024). Electricity 2024: Analysis and forecast to 2026, https://iea.blob.core.windows.net/assets/18f3ed24-4b26-4c83-a3d28a1be51c8cc8/Electricity2024-Analysisandforecastto2026.pdf
  • Javaid, M., Haleem, A., Khan, I. H., & Suman, R. (2023). Understanding the potential applications of Artificial Intelligence in Agriculture Sector. Advanced Agrochem, 2(1), 15-30.
  • Jean N, Burke M, Xie M, Davis WM, Lobell DB, Ermon S. (2016). Combining satellite imagery and machine learning to predict poverty. Science, 353(6301), 790-794.
  • Jiawei, H., & Kamber, M. (2006). Data mining: concepts and techniques. Amsterdam: Elsevier.
  • Kardashev, N. S. (1964). Transmission of Information by Extraterrestrial Civilizations. Soviet Astronomy, 8 (2).
  • Kaushik, R., Kant, R., & Christodoulides, M. (2023). Artificial intelligence in accelerating vaccine development-current and future perspectives. Frontiers in Bacteriology, 2, 1258159.
  • Kelleher, J. D., & Tierney, B. (2018). Data science. MIT press.
  • Khanna, M. (2021). Digital transformation of the agricultural sector: pathways, drivers and policy implications. Applied Economic Perspectives and Policy, 43(4), 1-22
  • Kirby, R. (2024), Artificial intelligence and health care. Trends Urology & Men Health, 15: 1-1. https://doi.org/10.1002/tre.971
  • Kumar, P., Singh, A., Rajput, V. D., Yadav, A. K. S., Kumar, P., Singh, A. K., & Minkina, T. (2022). Role of artificial intelligence, sensor technology, big data in agriculture: next-generation farming. In Bioinformatics in Agriculture (pp. 625-639). Academic Press.
  • Lee, D., & Yoon, S. N. (2021). Application of artificial intelligence-based technologies in the healthcare industry: Opportunities and challenges. International journal of environmental research and public health, 18(1), 271.
  • Lopes, M.A., Martins, H. and Correia, T. (2024), Artificial intelligence and the future in health policy, planning and management. Int J Health Plann Mgmt, 39: 3-8.
  • Lu, C.-H. (2021). The impact of artificial intelligence on economic growth and welfare. Journal of Macroeconomics, 69, 103342.
  • Maxim Pinkovskiy, Xavier Sala-i-Martin. (2016). Lights, Camera … Income! Illuminating the National Accounts-Household Surveys Debate. The Quarterly Journal of Economics, 131(2), 579–631. https://doi.org/10.1093/qje/qjw003
  • Milana, C., & Ashta, A. (2020). Microfinance and financial inclusion: Challenges and opportunities. Strategic Change, 29(3), 257-266.
  • Milana, C., & Ashta, A. (2021). Artificial intelligence techniques in finance and financial markets: A survey of the literature. Strategic Change, 30(3), 189–209.
  • 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, 5788. https://doi.org/10.3390/su13115788
  • Monkiewicz, J. (2022). Financial supervision in digital age: innovations and data abundance. In Digital Finance and the Future of the Global Financial System (pp. 213-225). Routledge.
  • Moro-Visconti, R. (2021). MicroFinTech: expanding financial inclusion with cost-cutting innovation. Palgrave Macmillan.
  • NTV. (2024, August 28). Vergi rekortmenleri belli oldu. NTV. https://www.ntv.com.tr/ntvpara/vergi-rekortmenleri-belli-oldu,_Xv_ixmK6UO3bbvSjD6oaQ Onedio. (2024, August 28). İlk kez bir yerli oyun şirketinin sahibi vergi rekortmeni oldu: Mert Gür kimdir? Onedio. https://onedio.com/haber/ilk-kez-bir-yerli-oyun-sirketinin-sahibi-vergi-rekortmeni-oldu-mert-gur-kimdir-1242756
  • OECD (2023). Health at a Glance 2023: OECD Indicators, OECD Publishing, Paris.
  • Oliveira, R. C. D., & Silva, R. D. D. S. E. (2023). Artificial intelligence in agriculture: benefits, challenges, and trends. Applied Sciences, 13(13), 7405.
  • Ratajczak, M. (2022). The state in the era of Digital Revolution and digital finance. In Digital Finance and the Future of the Global Financial System (pp. 93-108). Routledge.
  • Redhu, N. S., Thakur, Z., Yashveer, S., & Mor, P. (2022). Artificial intelligence: a way forward for agricultural sciences. In Bioinformatics in Agriculture (pp. 641-668). Academic Press.
  • Riep, C. B. (2017). Making markets for low-cost schooling: The devices and investments behind Bridge International Academies. Globalisation, Societies and Education, 15(3), 352-366.
  • Roy, A. (2015). Microfinance. Wiley Encyclopedia of Management, 1–3.
  • Sakthivel, V., Pravakar, D., & Prakash, P. (2024). Harnessing the Power of Artificial Intelligence and Data Science. In Advancement of Data Processing Methods for Artificial and Computing Intelligence (pp. 305-327). River Publishers.
  • Schwab K (2017) The fourth industrial revolution. The Crown Publishing Group, New York City, NY
  • Singh, V.P., Bansal, R. and Singh, R. (2023). Big-Data Analytics: A New Paradigm Shift in Micro Finance Industry. In Advances in Data Science and Analytics (eds M. Niranjanamurthy, H.K. Gianey and A.H. Gandomi). https://doi.org/10.1002/9781119792826.ch12
  • Smith, M.J. (2020). Getting value from artificial intelligence in agriculture. Anim. Prod. Sci. 60, 46.
  • Subeesh, A., & Mehta, C. R. (2021). Automation and digitization of agriculture using artificial intelligence and internet of things. Artificial Intelligence in Agriculture, 5, 278-291.
  • Sundsøy, P., Bjelland, J., Reme, B. A., et al. (2016). Deep learning applied to mobile phone data for individual income classification. In A. Petrillo, A. Nikkhah, & E. P. Edward (Eds.), Proceedings of the 2016 international conference on artificial intelligence: Technologies and applications. Amsterdam: Atlantic Press
  • Tegmark, M. (2018). Life 3.0: Being human in the age of artificial intelligence. Vintage.
  • The World Bank. (2023). Agriculture and Food. Retrieved from https://www.worldbank.org/en/topic/agriculture/overview#1
  • Turiel, A. (2024). Petro-Kıyamet: Küresel Enerji Krizi Nasıl Çözüle(meye)cek?, çev. Saliha Nifüler, T. İş Bankası Kültür Yayınları
  • Umbach, F. (2018). Energy security in a digitalized world and its geostrategic implications. Konrad Adenauer Stiftung.
  • Wagstaff, A. (2002). Poverty and health sector inequalities. Bulletin of the world health organization, 80, 97-105.
  • Wang, X., & Zhang, X. (2020). Towards 2030–China’s Poverty Alleviation and Global Poverty Governance. Springer Nature.
  • Zhang, W., Lei, T., Gong, Y., Zhang, J., & Wu, Y. (2022). Using Explainable Artificial Intelligence to Identify Key Characteristics of Deep Poverty for Each Household. Sustainability, 14(16), 9872.
  • Zhang, L., Ling, J., & Lin, M. (2022). Artificial intelligence in renewable energy: A comprehensive bibliometric analysis. Energy Reports, 8, 14072-14088.

Can AI Finish Poverty? The Role of Artificial Intelligence in Poverty Alleviation

Year 2024, Volume: 8 Issue: 2, 38 - 52
https://doi.org/10.70989/scd.1484258

Abstract

Artificial intelligence has become an integral part of our daily lives, both in discourse and action. Technological developments play a significant role in the recovery of the global economy. Although poverty has decreased proportionally in terms of meeting basic needs due to these advancements, it remains one of the most chronic and significant issues in the world. This study examines the role of artificial intelligence in the fight against poverty. It explores the various roles artificial intelligence plays in microfinance, agriculture, health, and education. While the study emphasizes that artificial intelligence has important functions in this area, it also notes that its contribution may not be inevitable or mandatory; factors such as political conditions and biophysical limits of our planet also play a critical role.

References

  • Alpaydin, E. (2020). Introduction to machine learning. MIT press.
  • Ashta, A., & Herrmann, H. (2021). Artificial intelligence and fintech: An overview of opportunities and risks for banking, investments, and microfinance. Strategic Change, 30(3), 211-222.
  • Bacastow, T. S., & Bellafiore, D. (2009). Redefining geospatial intelligence. American Intelligence Journal, 27(1), 38-40.
  • Bennington-Castro, J. (2017). “AI Is a Game-Changer in the Fight Against Hunger and Poverty. Here’s Why,” NBC News. https://www.nbcnews.com/mach/tech/ai-game-changerfight-against-hunger-poverty-here-s-why-ncna774696
  • Blain, L. (2024, March 01). Elon Musk: AI will run out of electricity and transformers in 2025., https://newatlas.com/technology/elon-musk-ai/
  • Case, A., & Kraftman, L. (2024). Health inequalities. Oxford Open Economics, 3(Supplement_1), i499-i528.
  • Cheng, X. et al (2021). Pursuing sustainable development goals: a review of renewable energy and poverty alleviation nexus. Environmental Development, 40, 100679.
  • Chowdhary, K. R. (2020). Fundamentals of artificial intelligence. New Delhi: Springer India.
  • Coelho, A.L.d.F., de Oliveira, T.F., Netto, M.N. (2022). Platforms, Applications, and Software. In: Marçal de Queiroz, D., M. Valente, D.S., de Assis de Carvalho Pinto, F., Borém, A., Schueller, J.K. (Eds.) Digital Agriculture. Springer, Cham. https://doi.org/10.1007/978-3-031-14533-9_15
  • DeLay, N., Mintert, J., & Thompson, N. (2021). Farm Data Collection and Software Adoption in Commercial Scale US Corn-Soybean Farms. In Western Economics Forum (Vol. 19, No. 2, pp. 12-19).
  • Dellosa, J. T., & Palconit, E. C. (2021, September). Artificial Intelligence (AI) in renewable energy systems: A condensed review of its applications and techniques. In 2021 IEEE International Conference on Environment and Electrical Engineering and 2021 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe) (pp. 1-6). IEEE.
  • Derrick, M. (2024). AI Critical to Success of Energy Sector, says Goldman Sachs. Energy Magazine. https://energydigital.com/articles/ai-critical-to-success-of-energy-sector-says-goldman-sachs Dormehl, L. (2017, April 24). To feed a growing population, scientists want to unleash AI on agriculture. Digital Trends. Retrieved from https://www.digitaltrends.com/cool-tech/future-of-food-carnegie-mellon-farming-project/
  • Engstrom, R., Hersh, J., & Newhouse, D. (2022). Poverty from space: Using high resolution satellite imagery for estimating economic well-being. The World Bank Economic Review, 36(2), 382–412. https://doi.org/10.1093/wber/lhab015
  • Forbes. (2024). Billionaires. Forbes. https://www.forbes.com/billionaires/ Głogowski, A. (2022). Systemic and cyber risk: the two monsters of financial system. In Digital Finance and the Future of the Global Financial System (pp. 199-212). Routledge.
  • González-Eguino, M. (2015). Energy poverty: An overview. Renewable and Sustainable Energy Reviews, 47, 377–385. doi:10.1016/j.rser.2015.03.013
  • Goralski, M. A., & Tan, T. K. (2022). Artificial Intelligence and Poverty Alleviation: Emerging Innovations and Their Implications for Management Education and Sustainable Development, The International Journal of Management Education (20:3), Elsevier, p. 100662. https://doi.org/10.1016/J.IJME.2022.100662
  • Grimmer, J., Roberts, M. E., & Stewart, B. M. (2021). Machine learning for social science: An agnostic approach. Annual Review of Political Science, 24, 395-419.
  • Guo, J., & Li, B. (2018). The application of medical artificial intelligence technology in rural areas of developing countries. Health equity, 2(1), 174-181.
  • Hanna, N. (2018) A role for the state in the digital age, Journal of Innovation and Entrepreneurship, Vol. 7, 5. 10.1186/s13731-018-0086-3.
  • He, J., Baxter, S. L., Xu, J., Xu, J., Zhou, X., & Zhang, K. (2019). The practical implementation of artificial intelligence technologies in medicine. Nature medicine, 25(1), 30-36.
  • Hall, O., Dompae, F., Wahab, I., & Dzanku, F. M. (2023). A review of machine learning and satellite imagery for poverty prediction: Implications for development research and applications. Journal of International Development, 35(7), 1753–1768.
  • Hickel, J. (2016). The true extent of global poverty and hunger: Questioning the good news narrative of the Millennium Development Goals. Third World Quarterly.
  • Holmes, W., & Tuomi, I. (2022). State of the art and practice in AI in education. European Journal of Education, 57, 542–570. https://doi.org/10.1111/ejed.12533
  • Hr, Ananya; Majhi, Siddharth; Mukherjee, Arindam; and Bala, Pradip Kumar, "Artificial Intelligence and Poverty Alleviation: A Review" (2022). ACIS 2022 Proceedings. 78. https://aisel.aisnet.org/acis2022/78 IBM. (2023, August). Generative AI for the Energy Industry: IBM Industry Point-of-View International Energy Agency (IEA). (2024). Electricity 2024: Analysis and forecast to 2026, https://iea.blob.core.windows.net/assets/18f3ed24-4b26-4c83-a3d28a1be51c8cc8/Electricity2024-Analysisandforecastto2026.pdf
  • Javaid, M., Haleem, A., Khan, I. H., & Suman, R. (2023). Understanding the potential applications of Artificial Intelligence in Agriculture Sector. Advanced Agrochem, 2(1), 15-30.
  • Jean N, Burke M, Xie M, Davis WM, Lobell DB, Ermon S. (2016). Combining satellite imagery and machine learning to predict poverty. Science, 353(6301), 790-794.
  • Jiawei, H., & Kamber, M. (2006). Data mining: concepts and techniques. Amsterdam: Elsevier.
  • Kardashev, N. S. (1964). Transmission of Information by Extraterrestrial Civilizations. Soviet Astronomy, 8 (2).
  • Kaushik, R., Kant, R., & Christodoulides, M. (2023). Artificial intelligence in accelerating vaccine development-current and future perspectives. Frontiers in Bacteriology, 2, 1258159.
  • Kelleher, J. D., & Tierney, B. (2018). Data science. MIT press.
  • Khanna, M. (2021). Digital transformation of the agricultural sector: pathways, drivers and policy implications. Applied Economic Perspectives and Policy, 43(4), 1-22
  • Kirby, R. (2024), Artificial intelligence and health care. Trends Urology & Men Health, 15: 1-1. https://doi.org/10.1002/tre.971
  • Kumar, P., Singh, A., Rajput, V. D., Yadav, A. K. S., Kumar, P., Singh, A. K., & Minkina, T. (2022). Role of artificial intelligence, sensor technology, big data in agriculture: next-generation farming. In Bioinformatics in Agriculture (pp. 625-639). Academic Press.
  • Lee, D., & Yoon, S. N. (2021). Application of artificial intelligence-based technologies in the healthcare industry: Opportunities and challenges. International journal of environmental research and public health, 18(1), 271.
  • Lopes, M.A., Martins, H. and Correia, T. (2024), Artificial intelligence and the future in health policy, planning and management. Int J Health Plann Mgmt, 39: 3-8.
  • Lu, C.-H. (2021). The impact of artificial intelligence on economic growth and welfare. Journal of Macroeconomics, 69, 103342.
  • Maxim Pinkovskiy, Xavier Sala-i-Martin. (2016). Lights, Camera … Income! Illuminating the National Accounts-Household Surveys Debate. The Quarterly Journal of Economics, 131(2), 579–631. https://doi.org/10.1093/qje/qjw003
  • Milana, C., & Ashta, A. (2020). Microfinance and financial inclusion: Challenges and opportunities. Strategic Change, 29(3), 257-266.
  • Milana, C., & Ashta, A. (2021). Artificial intelligence techniques in finance and financial markets: A survey of the literature. Strategic Change, 30(3), 189–209.
  • 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, 5788. https://doi.org/10.3390/su13115788
  • Monkiewicz, J. (2022). Financial supervision in digital age: innovations and data abundance. In Digital Finance and the Future of the Global Financial System (pp. 213-225). Routledge.
  • Moro-Visconti, R. (2021). MicroFinTech: expanding financial inclusion with cost-cutting innovation. Palgrave Macmillan.
  • NTV. (2024, August 28). Vergi rekortmenleri belli oldu. NTV. https://www.ntv.com.tr/ntvpara/vergi-rekortmenleri-belli-oldu,_Xv_ixmK6UO3bbvSjD6oaQ Onedio. (2024, August 28). İlk kez bir yerli oyun şirketinin sahibi vergi rekortmeni oldu: Mert Gür kimdir? Onedio. https://onedio.com/haber/ilk-kez-bir-yerli-oyun-sirketinin-sahibi-vergi-rekortmeni-oldu-mert-gur-kimdir-1242756
  • OECD (2023). Health at a Glance 2023: OECD Indicators, OECD Publishing, Paris.
  • Oliveira, R. C. D., & Silva, R. D. D. S. E. (2023). Artificial intelligence in agriculture: benefits, challenges, and trends. Applied Sciences, 13(13), 7405.
  • Ratajczak, M. (2022). The state in the era of Digital Revolution and digital finance. In Digital Finance and the Future of the Global Financial System (pp. 93-108). Routledge.
  • Redhu, N. S., Thakur, Z., Yashveer, S., & Mor, P. (2022). Artificial intelligence: a way forward for agricultural sciences. In Bioinformatics in Agriculture (pp. 641-668). Academic Press.
  • Riep, C. B. (2017). Making markets for low-cost schooling: The devices and investments behind Bridge International Academies. Globalisation, Societies and Education, 15(3), 352-366.
  • Roy, A. (2015). Microfinance. Wiley Encyclopedia of Management, 1–3.
  • Sakthivel, V., Pravakar, D., & Prakash, P. (2024). Harnessing the Power of Artificial Intelligence and Data Science. In Advancement of Data Processing Methods for Artificial and Computing Intelligence (pp. 305-327). River Publishers.
  • Schwab K (2017) The fourth industrial revolution. The Crown Publishing Group, New York City, NY
  • Singh, V.P., Bansal, R. and Singh, R. (2023). Big-Data Analytics: A New Paradigm Shift in Micro Finance Industry. In Advances in Data Science and Analytics (eds M. Niranjanamurthy, H.K. Gianey and A.H. Gandomi). https://doi.org/10.1002/9781119792826.ch12
  • Smith, M.J. (2020). Getting value from artificial intelligence in agriculture. Anim. Prod. Sci. 60, 46.
  • Subeesh, A., & Mehta, C. R. (2021). Automation and digitization of agriculture using artificial intelligence and internet of things. Artificial Intelligence in Agriculture, 5, 278-291.
  • Sundsøy, P., Bjelland, J., Reme, B. A., et al. (2016). Deep learning applied to mobile phone data for individual income classification. In A. Petrillo, A. Nikkhah, & E. P. Edward (Eds.), Proceedings of the 2016 international conference on artificial intelligence: Technologies and applications. Amsterdam: Atlantic Press
  • Tegmark, M. (2018). Life 3.0: Being human in the age of artificial intelligence. Vintage.
  • The World Bank. (2023). Agriculture and Food. Retrieved from https://www.worldbank.org/en/topic/agriculture/overview#1
  • Turiel, A. (2024). Petro-Kıyamet: Küresel Enerji Krizi Nasıl Çözüle(meye)cek?, çev. Saliha Nifüler, T. İş Bankası Kültür Yayınları
  • Umbach, F. (2018). Energy security in a digitalized world and its geostrategic implications. Konrad Adenauer Stiftung.
  • Wagstaff, A. (2002). Poverty and health sector inequalities. Bulletin of the world health organization, 80, 97-105.
  • Wang, X., & Zhang, X. (2020). Towards 2030–China’s Poverty Alleviation and Global Poverty Governance. Springer Nature.
  • Zhang, W., Lei, T., Gong, Y., Zhang, J., & Wu, Y. (2022). Using Explainable Artificial Intelligence to Identify Key Characteristics of Deep Poverty for Each Household. Sustainability, 14(16), 9872.
  • Zhang, L., Ling, J., & Lin, M. (2022). Artificial intelligence in renewable energy: A comprehensive bibliometric analysis. Energy Reports, 8, 14072-14088.
There are 63 citations in total.

Details

Primary Language English
Subjects Sociology (Other)
Journal Section Derleme Makaleler
Authors

Murat Kaçer 0000-0001-6076-3403

Early Pub Date December 20, 2024
Publication Date
Submission Date May 15, 2024
Acceptance Date November 6, 2024
Published in Issue Year 2024 Volume: 8 Issue: 2

Cite

APA Kaçer, M. (n.d.). Can AI Finish Poverty? The Role of Artificial Intelligence in Poverty Alleviation. Sosyal Çalışma Dergisi, 8(2), 38-52. https://doi.org/10.70989/scd.1484258
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