Tripartite Evolutionary Game and Simulation Analysis of AI Integration into Knowledge-Sharing Platforms

With the advancement of science and technology, artificial intelligence has progressively integrated into people’s daily economic lives, becoming a hot topic across various industries. However, due to the public’s negative attitude towards AI, many Internet industries related to public attitudes have taken a cautious stance. This study explores an evolutionary game model involving three parties within knowledge-sharing platforms: internet knowledge-sharing platform enterprises, knowledge providers, and AI service providers. Using Zhihu as a case study, it analyses optimal decision-making under the dual pressures of economic efficiency and public discontent. By constructing the model, the research finds that for AI service providers, collaboration with platform enterprises consistently represents the optimal decision. Public discontent is inversely proportional to knowledge providers’ likelihood of adopting AI. This study examines the decision-making process for integrating AI within knowledge-sharing platform enterprises, treating public discontent as a key influencing factor within the model. It provides a reference for future decision-making processes in similar industries when confronting public discontent regarding AI-related issues.