Yapay Zeka Sistemleri ve İnsan İşbirliğinin Psikolojik, Sosyal ve Eğitsel Etkileri

Abstract

Yapay zekâ (YZ) sistemlerinin ve YZ destekli robotların işbirliğine dayalı insan çalışma ortamlarına entegrasyonu, çok yönlü psikolojik, sosyal ve eğitsel etkilere yol açmıştır. Bu çalışma, PRISMA 2020 yönergeleri doğrultusunda yürütülen sistematik bir literatür derlemesi sunmakta ve 2019–2025 yılları arasında yayımlanan hakemli çalışmaları sentezlemektedir. İlgili çalışmalar, Scopus, Web of Science ve Google Scholar veri tabanlarında yapılan taramalarla belirlenmiştir. Derlemenin amacı, insan–YZ işbirliğinin ruh sağlığı, duygusal dayanıklılık ve bilişsel dinamikler üzerindeki etkilerini incelemektir. Disiplinlerarası literatüre dayanan analizde; teknostres, otomasyon yorgunluğu, bilişsel aşırı yüklenme, algoritmik kaygı, aşırı güven ve sorumluluk belirsizliği gibi temel olgular ele alınmaktadır. Bulgular, YZ’nin opaklığı, otomasyon yoğunluğu, antropomorfik ve duygusal tasarım özellikleri ile insan merkezli sistem tasarımının, kullanıcıların psikolojik tepkilerini şekillendirmede belirleyici rol oynadığını göstermektedir. İyi tasarlanmış YZ sistemleri bilişsel verimliliği ve iş tatminini artırma potansiyeline sahipken, insan faktörlerini göz ardı eden entegrasyonlar artan kaygı, tükenmişlik ve işten kopma ile ilişkilendirilmektedir. Bu bağlamda çalışma, sürdürülebilir insan–YZ işbirliğini desteklemek amacıyla şeffaflık, açıklanabilirlik ve kullanıcı otonomisini önceleyen insan merkezli bir yaklaşımın benimsenmesinin önemini vurgulamaktadır.

Keywords

• İnsan-YZ işbirliği
• Teknostres
• Otomasyon yorgunluğu
• Bilişsel yük
• Eğitsel Yapay Zeka

Psychological, Social, and Educational Impacts of Artificial Intelligence Systems and Human Collaboration

Abstract

The integration of artificial intelligence (AI) systems and AI-enabled robots into collaborative human work environments has led to innumerable psychological, social, and educational impacts. This study presents a systematic literature review, synthesising peer-reviewed research published between 2019-2025 in accordance with the PRISMA 2020 guidelines. Relevant studies were identified through searches of Scopus, Web of Science, and Google Scholar. The review aims to examine the mental health, emotional resilience, and cognitive dynamics of human–AI collaboration. Drawing on interdisciplinary literature, the analysis addresses key phenomena such as technostress, automation fatigue, cognitive overload, algorithmic anxiety, overreliance, and ambiguity of responsibility. The findings indicate that factors including AI opacity, the intensity of automation, anthropomorphic and affective design features, and human-centred system design play a decisive role in shaping users’ psychological responses. While well-designed AI systems demonstrate the potential to enhance cognitive efficiency and job satisfaction, poorly integrated implementations are associated with increased anxiety, burnout, and disengagement. Overall, the review highlights the importance of adopting a human-centred approach in AI applications, prioritising transparency, explainability, and user autonomy to support sustainable human–AI collaboration.

Keywords

• Human–AI collaboration
• Technostress
• Automation fatigue
• Cognitive load
• Educational Artificial Intelligence.

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