HAVACILIK ÇALIŞANLARININ YAPAY ZEKA KAYGI DÜZEYLERİNİN DEMOGRAFİK DEĞİŞKENLERE GÖRE İNCELENMESİ

Abstract

Yapay zekanın (YZ) hızlı gelişimi işyerindeki görevler, iş devamlılığı, gizlilik ve etik sorunlar gibi konularda kaygılara yol açmaktadır. Yoğun teknolojinin kullanıldığı havacılık sektöründeki çalışanlar da bu kaygılardan etkilenebilir. Bu çalışmanın amacı, havacılık sektöründeki YZ kaygı düzeylerini incelemek ve bu durumun cinsiyet, eğitim, yaş, tecrübe ve alt sektör gibi faktörlere göre değişip değişmediğini araştırmaktır. Çalışmada tarama yöntemi kullanılmış ve çevrimiçi anket yoluyla havacılık sektöründe çalışan 345 katılımcıdan veri toplanmıştır. Ölçme aracı olarak 5’li Likert derecelendirmesine dayalı YZ kaygı ölçeği kullanılmıştır. Bulgular havacılık sektörü çalışanları arasında orta düzeyde bir kaygı olduğunu (M=2.8047) göstermiştir. YZ sosyoteknik/körlük alt boyutunda kaygı seviyesi (M=3.3775) daha yüksek iken, YZ öğrenme alt boyutunda kaygı seviyesi (M=2.1055) daha düşüktür. Yaş, tecrübe ve alt sektörler arasında kaygı seviyelerinde anlamlı bir istatistiksel farklılık bulunmamıştır; ancak eğitim düzeyine bağlı farklılıklar tespit edilmiştir. Cinsiyet açısından genel olarak YZ kaygısında anlamlı bir farklılık bulunmamakla birlikte, YZ yapılandırma boyutunda anlamlı bir fark gözlemlenmiştir. Havacılık sektöründe YZ’nin gelişimiyle birlikte, çalışanların farklı boyutlardaki kaygılarının ele alınması etkin entegrasyon için önem taşımaktadır. Hızla gelişen YZ teknolojisi göz önüne alındığında, gelecekteki araştırmaların daha detaylı bir yaklaşım benimsemesi ve sektöre özgü varyasyonlar ile her bir havacılık alt sektörünün benzersiz yapı ve ihtiyaçlarını incelemesi önerilmektedir.

Keywords

• Havacılık
• İstihdam
• Teknoloji
• Yapay Zeka
• Yapay Zeka Kaygısı

EXAMINING THE AI ANXIETY LEVELS OF AVIATION EMPLOYEES BASED ON DEMOGRAPHIC VARIABLES

Abstract

The accelerated advancements in Artificial Intelligence (AI) give rise to anxieties regarding workplace tasks, job security, privacy, and ethics, which significantly impact employees in the technology-intensive aviation sector. The aim of the study was to examine the level of AI anxiety among professionals in the aviation sector and to investigate whether it varies based on factors such as gender, education, age, experience, and sub-sector. A survey methodology was employed. An online questionnaire was used to collect data from 345 aviation sector employees. The AI Anxiety Scale, a 5-point Likert-based instrument, was used as the measurement tool. The analysis results indicated that AI anxiety levels among aviation sector employees were moderate (M=2.8047). AI anxiety levels were highest in the sociotechnical/blindness sub-dimension (M=3.3775) and lowest in the AI learning sub-dimension (M=2.1055). No statistically significant differences in anxiety levels were found based on age, experience, or sub-sector, whereas education level showed significant differences. Although general AI anxiety did not significantly vary by gender, a notable difference was observed in AI configuration. As AI evolves in the aviation sector, addressing employee anxieties across sub-dimensions is essential for effective integration. Given the rapid advancements in AI technology, future studies should adopt a more detailed approach, focusing on sector-specific variations and analyzing the unique structures and requirements of each aviation sub-sector.

Keywords

• Artificial Intelligence
• Artificial Intelligence Anxiety
• Aviation
• Employment
• Technology

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