Artificial Intelligence in Aviation: A Path Analysis

Author(s)

Leila Halawi DBA, Embry-Riddle Aeronautical UniversityFollow
Mark D. Miller Ed.D., Embry-Riddle Aeronautical UniversityFollow
Sam J. Holley Ph.D., Embry-Riddle Aeronautical UniversityFollow

Volume

33

Issue

4

Key words

Artificial Intelligence, technology acceptance model, trust, path analysis, commercial aviation

Abstract

The study applied the Technology Acceptance Model (TAM) to assess trust in artificial intelligence (AI) within the US commercial aviation industry. It found that ease of use and usefulness positively influenced attitudes toward AI, impacting users’ intention to use it. However, perceived usefulness did not significantly affect meaning, purpose, and mood positively correlated with trust in AI. In some cases, higher perceived usefulness led to lower trust, indicating the complexity of trust in AI in aviation. This study highlights the importance of trust in AI and suggests the need for further investigation in the aviation context. It also recommends expanding the framework of trustworthy AI to consider factors like algorithm transparency, explainability, and fairness for a more comprehensive understanding.

Scholarly Commons Citation

Halawi, L., Miller, M. D., & Holley, S. J. (2024). Artificial Intelligence in Aviation: A Path Analysis. Journal of Aviation/Aerospace Education & Research, 33(4). DOI: https://doi.org/10.58940/2329-258X.2061