Cleared for Takeoff - Artificial Intelligence Acceptance in Air Traffic Control

Abstract

With the increasing complexity and volume of air traffic, there is growing interest in utilizing artificial intelligence (AI) support to alleviate ATCOs’ workload. Despite this potential, AI adoption in air traffic control (ATC) has been limited, partly due to low user acceptance. This study, grounded in the Technology Acceptance Model (TAM), the AI Acceptance Model (AIAM), and the Technology Acceptance in the Working Environment (TAWE) model, investigates the factors influencing AI acceptance among ATCOs. Using data from an online survey of 83 ATCOS, our model explains 78.5% of the variance in the intention to use AI. Notably, technology trust (TT) and emotion (EM) significantly influence the intention to use AI, with TT mediating the impact of perceived transparency (PT). Findings emphasize the need to address emotional and functional aspects to foster AI acceptance in ATC, marking a crucial step toward its improvement.