Yapay Zekâ Enerji Talebinde Çevresel-Fiskal Zaman Tutarsızlığı: Kurumsal Bir Yaklaşım

Yıl 2025, Sayı: Özel Sayı 3, 128 - 153, 31.12.2025

Yıldırım Beyazıt Çiçen

https://doi.org/10.33203/mfy.1836226

Öz

Bu çalışma, yapay zekâ (YZ) temelli teknolojilerin hızla artan enerji talebinin çevresel ve mali etkilerini birlikte değerlendiren özgün bir teorik model geliştirmektedir. Model, YZ altyapısının ekonomik faydalarını, iç ve dış çevresel zararlarını ve kamu bütçesine yansıyan teşvik maliyetlerini tek bir refah fonksiyonu içinde birleştirerek “YZ kaynaklı çevresel–fiskal zaman tutarsızlığı” kavramını formelleştirmektedir. Bulgular, politikacının kısa dönemli YZ faydalarını abartması, enerji teşviklerinin maliyetleri maskelemesi ve uluslararası dışsallıkların sınırlı içselleştirilmesi nedeniyle politik denge enerji düzeyinin toplumsal optimumun üzerinde gerçekleştiğini göstermektedir. Kurumsal kalite arttıkça bu sapma azalmakla birlikte, yapısal parametreler nedeniyle tamamen ortadan kalkmamaktadır. Çalışma, enerji tüketiminin yalnızca teknik bir maliyet unsuru değil; maliye politikası, çevre regülasyonu ve uluslararası iklim iş birliği tarafından şekillenen çok katmanlı bir yönetişim problemi olduğunu ortaya koymaktadır. Son bölümde sürdürülebilir maliye politikaları ve yeşil finans açısından politika önerileri sunulmaktadır.

Anahtar Kelimeler

Yapay zekâ , Enerji talebi , Zaman tutarsızlığı , Kurumsal kalite

AI-Driven Environmental–Fiscal Time Inconsistency in Energy Demand: An Institutional Approach

Öz

This study develops a theoretical model that jointly evaluates the environmental and fiscal implications of the rapidly growing energy demand driven by artificial intelligence (AI) technologies. Integrating the economic benefits of AI, domestic and cross-border environmental damages, and subsidy-related fiscal pressures into a unified welfare framework, the model formalizes the concept of “AI-driven environmental–fiscal time inconsistency”. The results show that political decision-makers systematically choose an energy level above the social optimum due to the overvaluation of short-term AI gains, the masking effect of energy subsidies on true costs, and the limited internalization of international externalities. Although higher institutional quality reduces this deviation, structural parameters prevent its complete elimination. The study demonstrates that AI-related energy consumption is not merely a technical cost issue but a multi-layered governance challenge shaped by fiscal policy, environmental regulation, and global climate cooperation. The paper concludes with policy implications regarding sustainable public finance and green investment frameworks.

Anahtar Kelimeler

Artificial intelligence , Energy demand , Time inconsistency , Institutional quality.

Kaynakça

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