数字赋能与风险规制之衡平:当环境治理遇见通用人工智能

Balancing Digital Empowerment and Risk Regulation:When Environmental Governance Meets General Artificial Intelligence

通用人工智能赋能环境治理是应对环境问题的新途径和新趋势。通用人工智能在智能分析与推理、自主学习与泛化、文本生成与知识更新、信息交互与渗透等方面实现了重大的技术跃迁,能够切实提高环境决策、环境执法以及环境司法的效益,促进环境治理协同。但这一过程也会引发新型治理风险,包括虚假信息生成、技术权力越权、算法偏见以及环境数据泄露等,可能导致环境决策错误、挑战传统环境规制权力、引发环境非正义,甚至威胁生态安全。基于此,既要从宏观层面明确通用人工智能赋能环境治理风险的法律规制向度,树立包容审慎的治理态度,坚持通用人工智能的辅助性地位,并融合敏捷治理范式;也要从微观层面构建风险因应的法律制度,从加强训练数据的内容生态规范化建设、构建公私合作的规制模式、推进发展可解释算法以及构建灵活高效的环境数据安全管理体系等方面健全通用人工智能赋能环境治理的法律规制体系。

The empowerment of general artificial intelligence in environmental governance represents a new approach and a trend in addressing environmental issues.Significant technological advancements in general AI,including intelligent analysis and reasoning,autonomous learning and generalization,text generation and knowledge updates,as well as interactive information penetration,have effectively enhanced the efficiency of environmental decision-making,law enforcement,and judicial processes,fostering collaborative environmental governance.However,this process will also lead to new-type governance risks,including false information generation,technical power overreach,algorithm bias and environmental data breaches,which may lead to erroneous environmental decisions,challenges to traditional environmental regulatory authority,environmental injustice,and even threat of ecological security.Consequently,it is necessary to clarify the legal regulation dimension of the environmental governance risk enabled by general AI from the macro level,establish an inclusive and prudent governance attitude,adhere to the auxiliary status of general AI,and integrate the agile governance paradigm.Simultaneously,it is also necessary to build a risk-responsive legal system from the micro level,and improve the legal regulatory system of general artificial intelligence-enabled environmental governance from the aspects of strengthening the standardization of the content of training data,building the regulation model of public-private cooperation,promoting the development of interpretable algorithms,and building a flexible and efficient environmental data security management system.