AI Trustworthiness and Student Pilots: Exploring Attitudes, Anxieties, and Adaptation Performance
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Date
2025
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier B.V.
Open Access Color
GOLD
Green Open Access
No
OpenAIRE Downloads
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Publicly Funded
No
Abstract
This research explores the attitudes of student pilots toward artificial intelligence (AI) applications within the aviation sector, with a focus on their adaptation processes and potential challenges. The recent release of the "EASA AI Roadmap 2.0"by the European Union Aviation Safety Agency (EASA) underscores the growing impact of AI on aviation, driving the emergence of new business models and emphasizing a human-centric approach to AI integration within the aviation industry. This study addresses a significant gap in the literature by examining student pilots' perspectives on AI, specifically focusing on AI trustworthiness, attitudes, anxieties, and adaptation performance. The study utilizes a quantitative research approach, collecting data from 150 student pilots through surveys. Preliminary results from 106 respondents indicate varied attitudes toward AI, with significant implications for AI-supported cockpit assistant systems and the broader aviation industry. The study sample consisted of 106 (Mage = 23.6, SDage= 4.64; 79% male) student pilots from of university pilot training departments and various flight school in Turkey. Collected data were analyzed on SPSS 29. The study revealed that Sociotechnical Blindness AI anxiety is a significant predictor of general attitudes toward AI among student pilots. This finding suggests that higher levels of anxiety related to the perceived complexity and potential unintended consequences of AI are associated with more positive general attitudes toward AI. The findings emphasize the need for a human-centric approach to AI integration, highlighting the importance of trust, transparency, and adaptive training in the successful adoption of AI technologies in aviation. © 2024 The Authors. Published by ELSEVIER B.V.
Description
Keywords
Adaptive Performance, AI Anxiety, AI Trustworthiness, Artificial Intelligence, Student Pilots
Fields of Science
Citation
WoS Q
N/A
Scopus Q
Q3

OpenCitations Citation Count
N/A
Source
Transportation Research Procedia -- 35th Conference of the European Association of Aviation Psychology, EAAP 2024 -- 23 September 2024 through 26 September 2024 -- Athens -- 209643
Volume
88
Issue
Start Page
234
End Page
242
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Scopus : 0
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