Preventive psychological preparation of judges for the implementation of artificial intelligence systems: prevention of automation bias in the context of the "Digital Court" concept in the Republic of Uzbekistan

<p style="text-align: justify;"><strong>Context and relevance.</strong> The global digitalization of justice actualizes the problem of psychological readiness of the judicial corps to work with artificial intelligence systems. Large-scale judicial and legal reforms in the Republic of Uzbekistan, initiated by His Excellency President Sh.M. Mirziyoyev since 2016, have reached a qualitatively new stage with the adoption of Presidential Decrees No. UP-140 and No. UP-141 dated August 21, 2025, which laid the legal foundation for the "Digital Court" concept and the creation of the Academy of Justice. Automation bias represents a critical risk to the objectivity of judicial decisions in the context of AI technology implementation. <strong>Objective.</strong> To develop a scientifically-based model of preventive psychological preparation of judges for working with AI systems within the framework of implementing the "Digital Court" concept in the Republic of Uzbekistan. <strong>Hypothesis.</strong> Preventive psychological preparation, integrated into the educational programs of the Academy of Justice, forms critical thinking when interacting with AI systems and reduces automation bias risks while maintaining judges' professional autonomy. <strong>Methods and materials.</strong> Comprehensive analysis of legal acts of the Republic of Uzbekistan, systematic review of international research on automation bias in legal practice, development of a theoretical model of judges' psychological readiness factors for working with AI systems based on decision-making theories and professional identity. <strong>Results.</strong> Key psychological factors were identified: cognitive (critical thinking), motivational (professional autonomy), emotional (anxiety management). A three-stage preparation model was developed: awareness of automation bias risks, development of critical evaluation skills for AI recommendations, formation of sustainable interaction patterns. Integration mechanisms into Academy of Justice programs were proposed. <strong>Conclusions.</strong> A preventive approach to psychological preparation of judges is strategically significant for justice quality. Integration of automation bias prevention programs into Academy of Justice activities will ensure the formation of a competitive judicial corps ready for effective use of AI technologies while maintaining critical thinking and professional responsibility.</p>

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