Intelligent systems as a tool for solving the problem of subjectivity in input data

Abstract

The use of intelligent systems to mitigate the subjectivity of input data represents a promising direction in the development of artificial intelligence. Training models on objective datasets enables the formation of an internal “map of regularities” within the system, which can subsequently be used for the evaluation, restoration, or cleansing of incomplete and subjective data. This creates a foundation for improving calculation accuracy, reducing the influence of the human factor, and ensuring the stability of decisions even under conditions of limited reliable observations.