Is this project an undergraduate, graduate, or faculty project?
Graduate
individual
What campus are you from?
Daytona Beach
Authors' Class Standing
graduate
Lead Presenter's Name
Aarohi Srivastava
Faculty Mentor Name
Briana Sobel
Abstract
As artificial intelligence (AI) becomes increasingly integrated into aviation systems, understanding its implications for safety and regulation is critical. This research examines the current state of AI implementation in aviation, exploring both transformative benefits and significant concerns in this high-stakes environment. AI's strengths, including rapid large-scale data processing, predictive capabilities, and pattern recognition, offer substantial operational advantages. However, these benefits must be balanced against key concerns including liability issues, potential loss of pilot competency through over-reliance, the "black box" problem of AI explainability, emergent system behaviors, and training requirements. This project analyzes current regulatory frameworks from major aviation authorities including the FAA, EASA, IATA, and ICAO. Common themes across these frameworks emphasize human oversight, transparency, traceability, continuous risk assessment, and unbiased data usage. This research also examines human-AI interaction dynamics, as well as examples of current implementations of AI in aircrafts and airports. With these guidelines, key recommendations include incremental implementation starting with low-risk applications, comprehensive training programs bridging knowledge gaps between technical experts and operational staff and maintaining human decision-making authority. Future research should address social acceptance, cognitive workload in human-AI teaming, cybersecurity threats, and balancing operational efficiency with innovation in safety-critical aviation environments.
Did this research project receive funding support from the Office of Undergraduate Research.
No
Included in
Artificial Intelligence in Aviation: Benefits, Concerns, and Regulations
As artificial intelligence (AI) becomes increasingly integrated into aviation systems, understanding its implications for safety and regulation is critical. This research examines the current state of AI implementation in aviation, exploring both transformative benefits and significant concerns in this high-stakes environment. AI's strengths, including rapid large-scale data processing, predictive capabilities, and pattern recognition, offer substantial operational advantages. However, these benefits must be balanced against key concerns including liability issues, potential loss of pilot competency through over-reliance, the "black box" problem of AI explainability, emergent system behaviors, and training requirements. This project analyzes current regulatory frameworks from major aviation authorities including the FAA, EASA, IATA, and ICAO. Common themes across these frameworks emphasize human oversight, transparency, traceability, continuous risk assessment, and unbiased data usage. This research also examines human-AI interaction dynamics, as well as examples of current implementations of AI in aircrafts and airports. With these guidelines, key recommendations include incremental implementation starting with low-risk applications, comprehensive training programs bridging knowledge gaps between technical experts and operational staff and maintaining human decision-making authority. Future research should address social acceptance, cognitive workload in human-AI teaming, cybersecurity threats, and balancing operational efficiency with innovation in safety-critical aviation environments.