摘要
数智时代,生成式人工智能(generative artificial intelligence,GAI)已成为全球各界关注的焦点,其展现的大语言模型的涌现能力,引发了信息生态中的诸多乱象。量化评价并优化GAI政策法规,在丰富GAI治理学理化研究、助力提升社会风险治理水平与信息治理效能和推进国家网络空间治理等方面具有现实意义。本文首先剖析了GAI内容引发的信息治理困境,其次,采用PMC指数模型(policy modeling consistency index model)并结合Matlab工具,对全球14项GAI政策法规文本进行量化评价分析。研究发现,政策法规整体一致性水平较高,但仍存在立法行业领域服务类型不明确、可信可控性应用功能受限、技术保障治理范围固化的问题。据此,本文提出技术优化、风险评估、应用部署和国际政策法规交融4个优化层面;针对GAI引发的信息治理困境问题,将敏捷治理细化为智慧服务、可信应用和技术安全三大核心维度,以此作为评价GAI政策法规的标尺;构建了软硬法兼施的灵活方案和场景化分层治理模式的优化框架,并提出了以信息治理为导向的GAI政策法规优化建议。
In the digital and intelligent era,generative artificial intelligence(GAI)has been garnering worldwide attention.The emergence of large language models has triggered many chaotic phenomena in the information ecology.The quantitative evaluation and optimization of GAI policies and regulations have practical significance in promoting the study of GAI governance rationalization,facilitating the enhancement of the level of social risk management and the effectiveness of information governance,and advancing national cyberspace governance.First,this study analyzes the information governance dilemma triggered by GAI content.Second,it employs the policy modeling consistency(PMC)index model method and combines it with the MatLab tool to quantitatively evaluate and analyze the texts of 14 global GAI policies and regulations.The findings reveal that the overall level of consistency of policies and regulations is relatively good,but there are still problems with unclear types of services in legislative industries and areas,restricted application functions of trustworthiness and controllability,and solidification of the scope of technical safeguard governance.Accordingly,this study proposes four optimization dimensions—technology optimization,risk assessment,application deployment,and international policy and regulation integration.Owing to the information governance dilemma triggered by GAI,the study refines agile governance into three core dimensions—intelligent services,trusted applications,and technical security—which serve as a yardstick for evaluating GAI policies and regulations.It constructs an optimization framework of flexible solutions and scenario-based hierarchical governance modes with both soft and hard methods,and proposes an optimization proposal of GAI policies and regulations oriented to information governance.
作者
王旭
刘斌斌
邱均平
Wang Xu;Liu Binbin;Qiu Junping(School of Economics and Management,Yanshan University,Qinhuangdao 066004;Chinese Academy of Science and Education Evaluation,Hangzhou Dianzi University,Hangzhou 310018)
出处
《情报学报》
北大核心
2025年第3期309-324,共16页
Journal of the China Society for Scientific and Technical Information
基金
国家社会科学基金青年项目“面向自主知识体系建构的中国社会科学国际学术话语权评价与提升研究”(24CTQ051)。
关键词
信息治理
生成式人工智能
政策法规
量化评价
PMC指数模型
优化框架
information governance
generative artificial intelligence
policies and regulations
quantitative evaluation
PMC index model
optimization framework
