Algorithmic Pressure and Psycho-Emotional Risk Among Airport Employees: A Two-Level Mamdani Fuzzy Model

This study revealed that the growing use of intelligent algorithms in air transport and airport management alters the workload of airport employees and creates new psycho-emotional risks. High information-flow density, opaque algorithmic solutions, discrepancies between digital instructions and the actual situation, and limited professional autonomy and responsibility for process safety were identified as the main sources of psycho-emotional stress, particularly among airport employees exposed to algorithmic management and digital monitoring. These factors were found to jointly reduce personnel concentration and situational awareness, slow decision-making, increase professional stress, and raise the likelihood of erroneous actions. Proposed solutions for reducing psycho-emotional stress arising from aviation human–AI interaction were analyzed using results from past and ongoing projects in Europe, Singapore, and China. The feasibility of alleviating the psycho-emotional risks experienced by airport employees through self-adaptive technologies for algorithmic air transport management was substantiated. These technologies include explainable algorithmic recommendations, adaptive workload distribution, maintenance of human control, monitoring for signs of overload, and a regulated ability to deviate from control algorithms when the operational situation changes. The findings can guide the design of human-centered cognitive-adaptive management systems for airport operations and help develop organizational measures to preserve the professional well-being of aviation personnel.