Tamamlayıcı Rekabetçilik: Yapay Zekâ Çağında Teknolojik İşsizlik Problemi ve Bir İstihdam Politikası Önerisi

Year 2024, Issue: 19, 59 - 78, 31.05.2024

Yahya Algül

https://doi.org/10.29157/etusbed.1390993

Abstract

Teknolojik işsizlik, Sanayi Devrimi'nden bu yana tartışılagelen bir konu olmuştur. Son yıllarda bu sorun makine öğrenmesi ve yapay zekâ teknolojilerindeki hızlı ilerlemelerle tekrar gündeme gelmiştir. Fakat, Sanayi Devrimi döneminin aksine, günümüzdeki yapay zekâ kaynaklı işsizlik olgusu farklıdır. Sanayi Devrimi dönemindeki işsizlik, temel ve basit işlerin otomasyonundan kaynaklanıyordu. Fakat, daha önceleri makinelerin becerebileceğinden çok daha karmaşık olan işleri dahi otomatikleştiren yapay zekâ teknolojisiyle birlikte teknolojik işsizlik olgusu daha da karmaşıklaşmıştır. Bu durum, yapay zekâ destekli makinelerin yeni durumlarda öğrenme ve uyum sağlama yeteneğinden kaynaklanmaktadır. Sonuç olarak, bu yeni gelişmeler ışığında, son yüzyılda uygulananlardan farklı bir istihdam politikası ihtiyacı doğmaktadır. Bu çalışmada, "Tamamlayıcı Rekabetçilik" olarak adlandırılan yeni bir politika önerisi geliştirilmiştir. Bu öneri, yapay zekayı sadece olumlu veya olumsuz olarak basit bir şekilde kategorize etmekten kaçınan bir yaklaşım benimsemektedir. Bunun yerine, sektörler arasındaki farklılıklar göz önüne alınırken, firmaların yapay zekâ tercihlerini de dikkate alan ve teknolojik ilerlemeyi destekleyici bir yaklaşım benimsenmiştir. Bu yaklaşım, literatürde sıkça görüldüğü gibi meslekleri ve yetenekleri gerekliliği veya gereksizliği şeklinde sınıflandırmanın ötesine geçerek istihdam politikalarını yapay zekâ çağının evrilen ihtiyaçlarıyla uyumlu hale getirmeyi amaçlar

Keywords

Yapay Zeka, Makine Öğrenmesi, Teknolojik İşsizlik, İstihdam Politikası

Complementary Competitiveness: Crafting an Employment Policy to Address Technological Unemployment in The Age of Artificial Intelligence

Abstract

Technological unemployment has been a concern since the Industrial Revolution. Approximately two centuries later, this issue has reemerged with the rapid advancements in machine learning and artificial intelligence technologies (AI). In contrast to the Industrial Revolution era, the unemployment caused by AI in the present age is different. Unlike earlier times, where unemployment primarily resulted from automating basic manual labor, the current challenge arises from AI automating tasks that were previously considered too complex for machines to handle. This is due to the capacity of AI-powered machines to learn and adapt to new situations. As a result, the evolving job market necessitates a different approach to employment policies compared to those applied over the last century. In this study, a new policy suggestion referred to as "Complementary Competitiveness" is discussed, taking a nuanced stance, avoiding simplistic categorizations of AI as purely beneficial or detrimental. Instead, it concentrates on formulating an employment strategy that distinguishes between sectors, taking into account firms resaons’ of AI preferences, all while not impeding technological progress. This approach seeks to align employment policies with the evolving needs of the AI age, which goes beyond the conventional binary classification of professions and competencies as necessary or obsolete as it seen in the literature.

Keywords

Artificial Intelligence, Machine Learning, Technological Unemployment, Employment policy

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