人工智能赋能中文国际传播的影响、现实瓶颈与优化路径

Artificial Intelligence Empowering International Communication of Chinese: Impacts, Practical Bottlenecks, and Optimization Paths

摘要: 人工智能正推动中文国际传播由资源数字化进一步走向应用智能化，但技术功能的扩展并不等同于传播效能的自然提升。文章以中国知网筛选得到的167篇期刊文献为主要样本，在梳理人工智能赋能中文国际传播发展历程的基础上，借鉴专业生成式人工智能能力框架(P-GenAI-C)的分析思路，考察人工智能对育人模式、传播资源和教师角色的影响，并分析与之相伴的现实瓶颈。研究发现，人工智能推动传播关系由教师–学生二元互动向教师–机器–学生三元协同转变，传播资源由静态供给向动态生成和智能适配演进，教师专业重心由知识传授转向学习设计、过程指导和人文引领；与此同时，教师技术整合与风险治理能力不足、资源供给结构失衡与深度智能化不足、学习者面临输出适配偏差、情感支持不足及主体性弱化等问题仍较为突出。基于上述问题，文章从教师能力与伦理治理、资源精准供给与质量进化、学习者使用准备与人机协同三个层面提出相互对应的优化路径。

Abstract: Artificial intelligence (AI) is moving international dissemination of Chinese beyond resource digitalization toward more intelligent applications, yet expanded technological functionality does not automatically translate into communication effectiveness. Drawing primarily on 167 journal articles screened from CNKI, this study reviews the development of AI-enabled international dissemination of Chinese and uses the Professional GenAI Competence (P-GenAI-C) framework as an analytical reference to examine changes in educational models, communication resources, and teacher roles, together with the practical bottlenecks that constrain them. The review shows that AI is transforming communication relations from dyadic teacher-student interaction to triadic teacher-machine-student collaboration, moving resources from static provision toward dynamic generation and intelligent adaptation, and shifting teachers’ professional focus from knowledge transmission toward learning design, process guidance, and humanistic guidance. At the same time, insufficient technology integration and risk-governance capacity among teachers, imbalanced resource provision and limited deep intelligence, and learner-side problems such as output mismatch, inadequate emotional support, and weakened agency remain salient. Accordingly, the paper proposes matched pathways in three areas: teacher competence and ethical governance, precisely targeted resource provision and quality evolution, and learner preparedness for use and human-machine collaboration.