人智协同知识创新机制的建模与仿真——基于模拟实验的系统动力学分析  被引量:1

Modeling and Simulation of Human-AI Collaborative Knowledge Innovation Mechanism:System Dynamics Analysis Based on Simulation Experiment

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作  者:张进澳 卢新元[1,2] 孙冰悦 王一洲 Zhang Jin’ao;Lu Xinyuan;Sun Bingyue;Wang Yizhou(School of Information Management,Central China Normal University,Hubei Wuhan 430079;E-Commerce Research Center of Hubei Province,Central China Normal University,Hubei Wuhan 430079)

机构地区:[1]华中师范大学信息管理学院,湖北武汉430079 [2]华中师范大学湖北省电子商务研究中心,湖北武汉430079

出  处:《情报理论与实践》2024年第12期143-153,96,共12页Information Studies:Theory & Application

基  金:国家社会科学基金重点项目“数智时代下AIGC服务模式及生态治理研究”(项目编号:23AGL040);中央高校基本科研业务费资助(优创项目)“融合生成式人工智能的人智协同知识创新机制及提升路径研究”(项目编号:2024CXZZ143)的成果。

摘  要:[目的/意义]随着生成式人工智能加速知识组织与服务变革演化,人智协同知识创新逐渐成为推动知识生成式“涌现”的重要引擎。因此,识别人智协同知识创新机制的核心要素,挖掘其影响关系与作用规律,对进一步提高人智协同知识创新水平具有重要意义。[方法/过程]基于“计算机作为社会行动者”范式,构建了人智协同知识创新的研究框架,并尝试根据模拟实验的知识流动规律设置相关变量参数,对人智协同知识创新机制进行仿真分析。[结果/结论]研究发现,人智协同知识创新系统包括“人类智能”“生成式人工智能”和“任务环境”三个子系统。其中,知识外部化水平和知识解释化水平是通过促进知识转化进一步驱动人智协同知识创新的重要手段,人智信任可以通过调节人智协同水平提高知识创新量,此外,知识创新阈值对人智协同知识创新也具有一定约束作用。[Purpose/significance]In the context of accelerating the transformation of knowledge organization and service,the human-AI(artificial intelligence)collaborative knowledge innovation model has become increasingly prominent,and has become a key engine to promote the“emergence”of knowledge generation.It is essential to identify the core elements of human-AI collabora-tive knowledge innovation and dig out its influence laws and mechanisms to further improve human-AI collaborative knowledge inno-vation.[Method/process]Based on the paradigm of“CASA”,this study constructs a research framework of human-AI collabora-tive knowledge innovation,and attempts to set relevant variable parameters according to the knowledge flow law of the simulation ex-periment to simulate the human-AI collaborative knowledge innovation mechanism.[Result/conclusion]It is found that the knowl-edge innovation system of human-AI collaboration includes three subsystems:human,generative artificial intelligence(GAI),task and environment.Knowledge externalization level and knowledge interpretation level are important means to further drive hu-man-AI collaborative knowledge innovation,human-AI trust can improve the amount of knowledge innovation by adjusting the level of human-AI collaboration.GAI knowledge innovation threshold also constrains human-AI collaborative knowledge innovation.

关 键 词:人工智能生成内容 知识管理 生成式人工智能 人智交互 人智协同 

分 类 号:TP18[自动化与计算机技术—控制理论与控制工程] TP391.9[自动化与计算机技术—控制科学与工程]

 

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