生成式人工智能视域下的政府场景治理OACHSSCD

The historic convergence of generative artificial intelligence(AI)technology and the continuous optimization of the business environment is driving the gradual realization of human-machine collaboration in government services.In this process,scenario governance has become a key factor determining whether technology can translate into service quality.Drawing on technology empowerment theory and scenario theory,this paper employs a multi-case analysis method to conduct an in-depth examination of the governance outcomes and bottlenecks in four types of scenarios during the process of optimizing the business environment:approval services,market supervision,policy support,and legal guarantees.This paper finds that generative AI technology has a significant empowering effect in government scenario governance,such as optimizing the business environment,and can effectively improve the efficiency of government governance.However,during the practical deployment of the technology,there remain numerous shortcomings,specifically manifested as insufficient adaptability to complex matters,prominent pressure on data security and privacy protection,misalignment between technology iteration and policy development,heightened risks of algorithmic bias,evident technology dependence,weak capacity to resolve complex disputes,and so on.In response to these bottlenecks,this paper proposes measures such as constructing a hierarchical and categorical precision empowerment system,improving collaborative iteration mechanisms,and strengthening risk prevention and control and ethical governance,thereby providing practical references for generative AI to empower the high-quality development of the business environment.