Empathy deficit in algorithmic governance: social and ethical challenges of ai-driven management systems

Abstract

The rapid expansion of artificial intelligence (AI) technologies in management practices is transforming the logic of decision-making by prioritizing automated data processing, formalized evaluation criteria, and predictive algorithms. At the same time, the weakening of the interpersonal dimension of management becomes increasingly evident, especially in areas where decisions carry significant social, ethical, and psychological implications. The predominance of algorithmic models intensifies the risks of declining institutional trust, reduced sensitivity to human needs, and the gradual distancing of management systems from human-centered principles.

The purpose of the article is to examine the consequences of excessive algorithmization of managerial processes and to substantiate the importance of emotional intelligence (EI) as an essential factor for ensuring social adequacy, ethical balance, and accountability in managerial decision-making within digital environments.

The study employed a combination of general scientific and specialized research methods, including system analysis of digital management transformations, structural-logical assessment of human–algorithm interaction, comparative analysis of human and algorithmic decision-making mechanisms, and conceptual modeling of the functional distribution between managers and AI systems.

The findings demonstrate that the predominance of algorithmic mechanisms in management limits the ability of systems to account for emotional, behavioral, and contextual dimensions of managerial situations. It was established that EI contributes not only to the effectiveness of professional interaction but also to maintaining trust, adaptability, and social acceptability of decisions in complex managerial environments. The feasibility of integrated management models was substantiated, where the analytical capabilities of AI are combined with human empathy, moral judgment, and responsible managerial choice.

It was generalized that the complete transfer of managerial functions to algorithmic systems may intensify dehumanization tendencies, increase managerial detachment, and weaken public trust in institutional decisions. The study emphasizes the necessity of preserving the leading role of human decision-makers in strategically and socially significant governance processes even under conditions of advanced digitalization.

Future research should focus on the development of practical models for integrating EI into digital governance systems, assessing the influence of managers’ emotional competence on the effectiveness of AI-supported decisions, and analyzing the efficiency of human-centered approaches in crisis and socially sensitive management situations.