AIGC在公安情报分析与决策应用中的挑战与策略:技术革新与法律框架的协同进化  

Challenges and Strategies of AIGC in Public Security Intelligence Analysis and Decision-Making Applications:Synergistic Evolution of Technological Innovation and Legal Frameworks

作　　者：张承先 陈泓艺 金佳雯 Zhang Chengxian;Chen Hongyi;Jin Jiawen(Nanchang Railway Public Security Bureau,Nanchang 330002;People's Public Security University of China,Beijing100038;ShanghaiPolice College,Shanghai 200000)

机构地区：[1]南昌铁路公安局,南昌330002 [2]中国人民公安大学,北京100038 [3]上海公安学院,上海200000

出　　处：《警学研究》2025年第1期94-104,共11页Police Science Research

摘　　要：随着人工智能技术的不断发展,生成式人工智能已在公安情报领域展现出了巨大的应用潜力。AIGC可以打造搜集、分析、指挥智能情报系统,但也面临AIGC的数据训练集带来的情报工作信息偏见错误、算法“黑箱”带来的情报信息可解释性差、模型漏洞和人为恶意操作带来的敏感数据安全问题、辅助情报指挥工作带来的责任分配等问题。针对以上问题,应从提高训练数据集的专业性与客观性和算法可解释性、多举措加强数据保护、完善算法问责法律体系方面采取应对措施,技术革新与法律框架的协同进化从而提高AIGC在公安情报工作中的应用效能。With the advancement of artificial intelligence technology,generative AI has demonstrated significant application potential in the field of public security intelligence. AIGC can create intelligent systems for intelligence collection,analysis,and command. However,it also faces challenges such as information bias and errors in intelligence work due to AIGC's training datasets,poor interpretability of intelligence information caused by algorithmic “black boxes,”sensitive data security issues arising from model vulnerabilities and malicious human manipulation,and responsibility allocation problems in auxiliary intelligence command work. To address these issues,measures should be taken to enhance the professionalism and objectivity of training datasets,improve algorithmic interpretability,strengthen data protection through multiple approaches,and refine the legal system for algorithmic accountability. The synergistic evolution of technological innovation and legal frameworks will thereby enhance the application efficacy of AIGC in public security intelligence work.

关 键 词：AIGC ChatGPT 公安情报 挑战 策略 

分 类 号：D924.11[政治法律—刑法学]