Abstract: Generative artificial intelligence technology has been embedded in various aspects of social science knowledge production research, not only reshaping the basic process of social science knowledge production, but also leading the intelligent research paradigm to become one of the mainstream research paradigms in the field of social science knowledge production. However, while generative artificial intelligence expands the field of social science knowledge production, it also brings challenges such as unclear data ownership, data bias, data illusion, and data arrogance in the process of processing complex data generation content, eroding the common virtue of social science knowledge production. To enhance the efficiency and quality of generative artificial intelligence in knowledge production, improve the public, fair, objective, and critical character of the social science knowledge production community, and build an ideal collaborative vision of “knowledge co creation, human-machine symbiosis”.