Generative artificial intelligence（AI）has emerged as a pivotal tool in the creation of science popularization literature; however，its capability in this domain remains subject to skepticism when compared to human authors. To evaluate the sciencepopularization writing competence of generative artificial intelligence，a four-dimensional evaluation framework was developed，comprising readability，engagement，scientific accuracy，and dissemination effectiveness. Using“microbiology”as the thematic focus，sciencepopularization works produced by human creators，DeepSeek，ChatGPT，and ERNIE Bot were systematically examined. The results indicate that both the initial-prompt and deep-prompt versions generated by ChatGPT showed no significant difference in overall scores relative to the human-authored version，with the deep-prompt version exhibiting a significantly superior performance in terms of readability. Moreover，the deep-prompt version of DeepSeek outperformed the human version in the dimensions of engagement and dissemination effectiveness. Notably，evaluators correctly distinguished AI-generated works in less than 55% of cases and showed a tendency to attribute high-scoring works to human creators. These experimental findings suggest that generative artificial intelligence holds the potential to substitute for humanscience popularization creators，thereby prompting the proposal of a novel“human-machine collaborative sciencepopularization creation”model. The study further calls upon the academic community to critically examine the phenomenon of the“Hallucination of Human’s Ability”.