Human Error and Artificial Intelligence Interaction in Occupational Safety
17th AHFE International Conference Istanbul, Turkey, July 20-24, 2026, İstanbul, Türkiye, 20 - 24 Temmuz 2026, cilt.227, sa.2272026, ss.142-149, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Cilt numarası: 227
- Doi Numarası: 10.54941/ahfe1007926
- Basıldığı Şehir: İstanbul
- Basıldığı Ülke: Türkiye
- Sayfa Sayıları: ss.142-149
- Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
- İstanbul Ticaret Üniversitesi Adresli: Evet
Özet
The study begins with a brief overview of the concept of artificial intelligence, which is now closely affecting individuals, social life, and all sectors. It then examines the development process of artificial intelligence, its areas of application, and the impact of the Internet of Things technology—which is increasingly being integrated into new applications—on the new generation of humans. It also emphasizes the importance of adopting a hybrid approach that combines machines’ automation power with humans’ethical, intuitive, and contextual competencies for a sustainable and reliable future. Artificial intelligence, which has been rapidly accepted in professional work life and personal life, has created risks and problems both in specific sectors and in individuals’private lives, alongside its effects of simplifying life and increasing quality in every area. Despite concerns that human behaviour inherently carries greater risk than machine behaviour, analyses of errors made by artificial intelligence and errors made by humans reveal that, despite commonalities, the types, probabilities, effects, and consequences of these two types of errors differ significantly. For example, it is believed that the current capabilities of artificial intelligence technologies are insufficient to meet certain critical human competencies. It is seen that human-specific qualities such as ethical evaluation, contextual analysis, creative problem solving, and strategic reasoning cannot be fully performed by artificial intelligence. The biggest challenge facing artificial intelligence stems from the fact that a significant percentage of the data on which AI systems rely comes from humans. Such data is largely the result of the irrationality and subjectivity of people acting in their own self-interest. Human errors can be skill-based, rule-based, or knowledge-based. Skill-based errors are application errors, while the other two are planning-based. Studies show that most human errors are skill-based, such as carelessness and inattention, and are more likely to be detected. As a result, artificial intelligence should continue to be a complement in areas where the human factor is critically important and should maintain its indispensability. The proportion of human error is much greater than the proportion of artificial intelligence errors. And fundamentally, the source of artificial intelligence errors is human error. To mitigate their effects, investments are needed to improve error detection for both types of errors. As both humans and machines evolve, the likelihood of new errors emerging increases, while the likelihood of old errors persisting decreases, necessitating adequate risk management efforts.