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