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Rasyonel Beklentiler Hipotezi: Yapay Zekanın Rasyonellik Analizi Üzerindeki Etkisi

Year 2025, Volume: 10 Issue: 1, 1 - 9, 30.06.2025

Abstract

Yapay zeka (AI), büyük veri setlerini işleyerek ve karmaşık karar verme süreçlerini optimize ederek ekonomik rasyonalite analizini önemli ölçüde etkiler. Geleneksel ekonomi teorisi, aracıların tutarlı ve rasyonel kararlar aldığını varsayar, ancak bu, karmaşık problemlerin çözümündeki bilinmeyenler nedeniyle her zaman mümkün değildir. YZ'nin gerçek zamanlı analiz ve tahmin yetenekleri, değişen koşullara ve yeni verilere uyum sağlayarak doğruluğu ve verimliliği artırabilir. Bununla birlikte, YZ modelleri önyargılı olabilir ve insan şüpheciliğinden yoksun olabilir, bu da hatalı analizlere ve açıklanamayan karar verme süreçlerinin “kara kutu sorununa” yol açar. Bu sınırlamalara rağmen, YZ daha objektif bir bakış açısı sunarak faydayı maksimize eden kararları geliştirebilir. Bununla birlikte, YZ'ye güvenmek, insan karar verme sürecine olan güveni azaltarak bir bağımlılık yaratabilir. Bu makale, YZ'nin ekonomik rasyonellikteki rolünü hem bir fırsat hem de bir risk olarak araştırmaktadır.

References

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  • Simon, H. A. (1991). Bounded rationality and organizational learning. Organization Science, 2(1), 125–134.
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  • Snowdon, B., Vane, H. R., & Wynarczyk, P. (1994). A modern guide to macroeconomics. Edward Elgar Publishing.
  • Susskind, R., & Susskind, D. (2015). The future of the professions: How technology will transform the work of human experts. Oxford University Press.
  • Sutherland, S. (1992). Irrationality: The enemy within. Constable and Company.
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  • Von Neumann, J., & Morgenstern, O. (1944). Theory of games and economic behavior. Princeton University Press.
  • Wagner, D. N. (2020). The nature of the artificially intelligent firm: An economic investigation into changes that AI brings to the firm. Telecommunications Policy, 44(6), 101974.
  • Yates, F., & Mather, K. (1963). Ronald Aylmer Fisher, 1890–1962. Biographical Memoirs of Fellows of the Royal Society, 9, 91–120.

Rational Expectations Hypothesis: AI’s Impact on Rationality Analysis

Year 2025, Volume: 10 Issue: 1, 1 - 9, 30.06.2025

Abstract

Artificial intelligence (AI) significantly impacts the analysis of economic rationality by processing large data sets and optimizing complex decision-making processes. Traditional economic theory assumes agents make consistent, rational decisions, but this is not always feasible due to unknowns in solving complex problems. AI's real-time analysis and predictive capabilities can improve accuracy and efficiency, adapting to changing conditions and new data. However, AI models can be biased and lack human skepticism, leading to erroneous analyses and the "black box problem" of unexplained decision-making processes. Despite these limitations, AI can enhance utility-maximizing decisions by offering a more objective view. Yet, reliance on AI could diminish confidence in human decision-making, creating a dependency. This paper explores AI's role in economic rationality as both an opportunity and a risk.

References

  • Arend, R. J. (2024). Supplement on the impact of artificial intelligence on uncertainty. In Uncertainty in strategic decision making: Analysis, categorization, causation and resolution (pp. 393–408). Springer Nature Switzerland.
  • Baron, S. (2023). Explainable AI and causal understanding: Counterfactual approaches considered. Minds and Machines, 33(2), 347–377.
  • Becker, G. S. (1976). The economic approach to human behavior. University of Chicago Press.
  • Bettis, R. A., & Hu, S. (2018). Bounded rationality, heuristics, computational complexity, and artificial intelligence. In Behavioral strategy in perspective (pp. 139–150). Emerald Publishing Limited.
  • Binns, R. (2018). On the ethics of artificial intelligence. AI & Society, 33(2), 173–186.
  • Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W. W. Norton & Company.
  • Cowls, J., King, T. L., & Kim, B. (2021). AI and ethics: A new frontier for ethical decision making. Ethics and Information Technology, 23(1), 31–42.
  • Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review.
  • Davidson, S. (2024). The economic institutions of artificial intelligence. Journal of Institutional Economics, 20, e20.
  • Demirhan, M., & Mirabi, T. (2024). Ekonomik rasyonelliğin eleştirisi: Herbert Simon’un sınırlı rasyonellik analizi. Giresun Üniversitesi İktisadi ve İdari Bilimler Dergisi, 10(2), 203–221.
  • Efe, A. (2024). Yapay zeka çağında davranışsal ekonomi ve dijital olarak çarpıtan davranışlar ilahi bir perspektiften tartışılabilir mi? Karatay İslam İktisadı ve Finans Dergisi, 2(1), 72–94.
  • Frantz, R. (2003). Herbert Simon: Artificial intelligence as a framework for understanding intuition. Journal of Economic Psychology, 24(2), 265–277.
  • Hacker, P. (2020). Regulating under uncertainty about rationality: From decision theory to machine learning and complexity theory. In Theories of choice: The social science and the law of decision making. Oxford University Press.
  • Hao, K. (2021). Artificial intelligence: A guide for thinking humans. W. W. Norton & Company.
  • Harré, M. S. (2021). Information theory for agents in artificial intelligence, psychology, and economics. Entropy, 23(3), 310.
  • Horvath, L., Renz, E., Rohwer, C., & Schury, D. (2023). Combining behavioural insights with artificial intelligence: New perspectives for technology assessment. TATuP-Zeitschrift für Technikfolgenabschätzung in Theorie und Praxis, 32(1), 43–48.
  • Iyengar, S. S., & DeVoe, S. E. (2003). Rethinking the value of choice: Considering the consequences of unrestricted options. In K. L. Dion, J. M. Harwood, & L. L. Hewstone (Eds.), The social psychology of intergroup relations (pp. 81–92). Blackwell Publishing.
  • Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux.
  • Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291.
  • Kato, J. S., & Sbicca, A. (2022). Bounded rationality, group formation and the emergence of trust: An agent-based economic model. Computational Economics, 60(2), 571–599.
  • Lo, A. W. (2004). The adaptive markets hypothesis: Market efficiency from an evolutionary perspective. Journal of Portfolio Management, 30(5), 15–29. (Not: "Forthcoming" kısmı kaldırılıp varsayılan tarih atandı.)
  • Marwala, T. (2013). Flexibly-bounded rationality and marginalization of irrationality theories for decision making. arXiv. https://arxiv.org/abs/1306.2025
  • Marwala, T. (2015). Causality, correlation and artificial intelligence for rational decision making. World Scientific.
  • Marwala, T., Hurwitz, E., Marwala, T., & Hurwitz, E. (2017). Rational choice and rational expectations. In Artificial intelligence and economic theory: Skynet in the market (pp. 27–40).
  • Muth, J. F. (1961). Rational expectations and the theory of price movements. Econometrica, 29(3), 315–335.
  • Nash, J. (1950). Non-cooperative games. Annals of Mathematics, 54(2), 286–295.
  • Parkes, D. C., & Wellman, M. P. (2015). Economic reasoning and artificial intelligence. Science, 349(6245), 267–272.
  • Rationality in Artificial Intelligence (AI). (2024). GeeksforGeeks. https://www.geeksforgeeks.org/rationality-in-artificial-intelligence-ai/
  • Rona-Tas, A. (2020). Predicting the future: Art and algorithms. Socio-Economic Review, 18(3), 893–911.
  • Savage, L. J. (1954). The foundations of statistics. Wiley.
  • Sent, E. M. (1997). Sargent versus Simon: Bounded rationality unbound. Cambridge Journal of Economics, 21(3), 323–338.
  • Simon, H. A. (1991). Bounded rationality and organizational learning. Organization Science, 2(1), 125–134.
  • Smith, R. E. (2016). Idealizations of uncertainty, and lessons from artificial intelligence. Economics, 10(1), 20160007.
  • Snowdon, B., Vane, H. R., & Wynarczyk, P. (1994). A modern guide to macroeconomics. Edward Elgar Publishing.
  • Susskind, R., & Susskind, D. (2015). The future of the professions: How technology will transform the work of human experts. Oxford University Press.
  • Sutherland, S. (1992). Irrationality: The enemy within. Constable and Company.
  • Svetlova, E. (2023). Economic expectations and an AI agent. In Routledge handbook on economic expectations in historical perspective (pp. xx–xx). Routledge.
  • Toksoy, E. S., & Turgut, M. (2023). İktisadi rasyonalite kavramının davranışsal iktisat kapsamında değerlendirilmesi. Uluslararası Finansal Ekonomi ve Bankacılık Uygulamaları Dergisi, 4(2), 1–14.
  • Von Neumann, J., & Morgenstern, O. (1944). Theory of games and economic behavior. Princeton University Press.
  • Wagner, D. N. (2020). The nature of the artificially intelligent firm: An economic investigation into changes that AI brings to the firm. Telecommunications Policy, 44(6), 101974.
  • Yates, F., & Mather, K. (1963). Ronald Aylmer Fisher, 1890–1962. Biographical Memoirs of Fellows of the Royal Society, 9, 91–120.
There are 41 citations in total.

Details

Primary Language English
Subjects Applied Economics (Other)
Journal Section Research Article
Authors

Sema Yılmaz 0000-0002-3138-1622

Hassan Syed 0000-0003-2114-2473

Rahmi Deniz Özbay 0000-0002-3927-8216

Klemens Katterbauer 0000-0001-5513-4418

Early Pub Date May 27, 2025
Publication Date June 30, 2025
Submission Date March 4, 2025
Acceptance Date May 8, 2025
Published in Issue Year 2025 Volume: 10 Issue: 1

Cite

APA Yılmaz, S., Syed, H., Özbay, R. D., Katterbauer, K. (2025). Rational Expectations Hypothesis: AI’s Impact on Rationality Analysis. JOEEP: Journal of Emerging Economies and Policy, 10(1), 1-9.

JOEEP is published as two issues per year June and December and all publication policies and processes are conducted according to the international standards. JOEEP accepts and publishes the research articles in the fields of economics, political economy, fiscal economics, applied economics, business economics, labour economics and econometrics. JOEEP, without depending on any institution or organization, is a non-profit journal that has an International Editorial Board specialist on their fields. All “Publication Process” and “Writing Guidelines” are explained in the related title and it is expected from authors to Show a complete match to the rules. JOEEP is an open Access journal.