Identification of misjudgment cases in artificial intelligence-assisted social insurance declaration and verification
人工智能参与社保申报审核中的误判情形识别

摘要

人工智能在社保申报审核上提高了效率，但是误判问题仍然存在，对审核准确性有影响。对数据质量、算法适配度、模型不足等各方面造成误判的因素进行研究，提出改善数据处理、算法调整、人工和AI配合等方法。经过测试可以得到以下结论，提高数据的质量、增强人工智能系统自适应能力、加强人工审核之间的配合，都是减少误判的因素。随着技术的进步，在社保审核上人工智能将起到更重要的作用，促使智能化的发展。

Abstract

Artificial intelligence has improved the efficiency of social insurance declaration and review, but the problem of misjudgment still exists, which affects the accuracy of review. This paper studies the factors causing misjudgment from the aspects of data quality, algorithm adaptability and model deficiencies, and proposes methods such as improving data processing, adjusting algorithms and coordinating human and AI. Tests show that improving data quality, enhancing the adaptive ability of artificial intelligence systems, and strengthening coordination with manual review can all reduce misjudgment. With technological advances, artificial intelligence will play a more important role in social insurance review and promote the development of intelligent services.