EXPLORATION OF THE OPTIMIZATION PATH OF ALGORITHMIC DECISION-MAKING FROM THE PERSPECTIVE OF PUBLIC SERVICE EQUALIZATION: BASED ON THE SURVEY EXPERIENCE OF THE TOURISM BOOM IN NORTHEAST CHINA DURING THE SPRING FESTIVAL

Currently, the reform of the digital administration is imminent. Although traditional decision-making regulation policies can solve most social public problems, it is difficult to achieve the unity of timeliness and accuracy. Algorithmic decision-making is a process of analyzing, processing, and predicting data through computer algorithms to assist humans in making decisions. The rational use of algorithms can improve decision-making efficiency, reduce labor costs, and lower the risk of misjudgment. This paper conducts a multi-dimensional analysis of the internal logical relationship between public service equalization and algorithmic decision-making, continuously adjusts and optimizes the algorithm model, and explores algorithm applications and solutions that are beneficial to the development of public undertakings, thereby optimizing resource allocation. By applying algorithmic decision-making to public service fields such as intelligent transportation systems, medical resource allocation, educational resource optimization, public safety monitoring, social welfare policy formulation, and disaster emergency response, the quality of public services can be improved, the sustainable development of various social fields can be promoted, and the continuous improvement of the lives of the broad masses of the people can be achieved.