In this paper, we examine the existing artificial intelligence policy documents in aviation for the following three regions: the United States, the European Union, and China. These global economic leaders were selected for their dominance in economic activity; as a result, their influence on aviation policy direction is a logical assumption. Historically, the aviation industry has always been a first mover in adopting technological advancements. This early adoption offers valuable insights because of its stringent regulations and safety-critical procedures. Consequently, the aviation industry provides an optimal platform to address AI vulnerabilities through its stringent regulations, standardized processes, and certification of new technologies. Our research aims to compare AI regulations across these regions to guide other sectors in shaping effective policies. The findings of our comparative analysis show that there are vastly differing approaches to the application of AI regulations in the aviation sector, thus weakening desired prospects for global cooperation and worsening existing geopolitical tensions. Therefore, we propose a hybrid model approach as a way forward. Under this model, regions maintain their distinctive AI policies but collaborate on high-risk aviation applications through joint working groups, shared safety intelligence, or mutual recognition agreements. This would preserve incentives for innovation but also reduce regulatory friction.
Barr et al. (Wed,) studied this question.