Akademik Veri Yönetim Sistemi
35th EAAP Conference, Athens, Yunanistan, 23 - 26 Eylül 2024, ss.1-8
The objective of this research is to facilitate a more profound understanding of student pilots' attitudes towards artificial intelligence applications in the aviation sector. The study aims to assess pilots' adaptation processes to artificial intelligence technologies and understand potential challenges that may arise during this process. European Union Aviation Safety Agency (EASA) has recently published 'EASA AI Roadmap 2.0' and emphasized that artificial intelligence not only influences the products and services provided by the aviation sector but also triggers the emergence of new business models (EASA, 2023). This roadmap indicates a significant shift towards a new era, emphasizing a human-centric perspective with a focus on the trustworthiness of AI. Artificial intelligence technologies and artificial intelligence investments in the future of the aviation industry are expected to reach 3.7 billion dollars in 2027 (Innova, 2023). Examining this situation, which may also reveal potential usability problems of artificial intelligence-supported cockpit assistant systems, from the perspective of airline pilots, has been identified as a gap in the literature. In the research methodology, a quantitative research method has been designed for data collection from student pilots and pilot candidates through the use of surveys (Charbonnier-Voirin & Roussel, 2012; Schepman & Rodway, 2020; Wang & Wang, 2022). Based on the analysis conducted using the G*Power 3.1.9.7 software (with a significance criterion of 0.05 and a power of 0.95), the sample size was determined to be 126. The research is in the data collection phase (currently 50 student pilots responded).
Innovation of the current study:
In accordance with the 'EASA AI Roadmap 2.0' released by EASA in the year 2023, the fundamental objective outlined within is to 'Develop a human-centric AI trustworthiness framework.' Examining the attitudes of pilot candidates towards artificial intelligence, as they engage with it in the employment processes, by culturally measuring these attitudes, will contribute valuable insights to current research conducted by authorities such as EASA.
The objective of this research is to facilitate a more profound understanding of student pilots' attitudes towards artificial intelligence applications in the aviation sector. The study aims to assess pilots' adaptation processes to artificial intelligence technologies and understand potential challenges that may arise during this process. European Union Aviation Safety Agency (EASA) has recently published 'EASA AI Roadmap 2.0' and emphasized that artificial intelligence not only influences the products and services provided by the aviation sector but also triggers the emergence of new business models (EASA, 2023). This roadmap indicates a significant shift towards a new era, emphasizing a human-centric perspective with a focus on the trustworthiness of AI. Artificial intelligence technologies and artificial intelligence investments in the future of the aviation industry are expected to reach 3.7 billion dollars in 2027 (Innova, 2023). Examining this situation, which may also reveal potential usability problems of artificial intelligence-supported cockpit assistant systems, from the perspective of airline pilots, has been identified as a gap in the literature. In the research methodology, a quantitative research method has been designed for data collection from student pilots and pilot candidates through the use of surveys (Charbonnier-Voirin & Roussel, 2012; Schepman & Rodway, 2020; Wang & Wang, 2022). Based on the analysis conducted using the G*Power 3.1.9.7 software (with a significance criterion of 0.05 and a power of 0.95), the sample size was determined to be 126. The research is in the data collection phase (currently 50 student pilots responded).
Innovation of the current study:
In accordance with the 'EASA AI Roadmap 2.0' released by EASA in the year 2023, the fundamental objective outlined within is to 'Develop a human-centric AI trustworthiness framework.' Examining the attitudes of pilot candidates towards artificial intelligence, as they engage with it in the employment processes, by culturally measuring these attitudes, will contribute valuable insights to current research conducted by authorities such as EASA.