Apolitical referee or geopolitical actor? How artificial intelligence’s national-origin labels shape credibility in politicized science communication - Junyi Chen; Weixi Zeng; Yi Mou (Public Understanding of Science, 2026)
Amid the politicization of science and the globalization of technological applications, does the national-origin label of artificial intelligence authors affect their perceived credibility? Drawing on the tension between artificial intelligence as an apolitical referee (machine heuristic) and artificial intelligence as a geopolitical actor like humans (social identity theory and computers-are-social-actors paradigm), two online experiments were conducted in China to examine the role of author type (human, artificial intelligence, and human–artificial intelligence hybrid) and national-origin labels in scientific content with varying degrees of politicization. In a highly politicized context, domestic sources were preferred across all author types, with nationalism amplifying this preference. The effect of artificial intelligence’s national-origin label was significant but weaker than that for human authors. In low-politicized contexts, the national-origin label no longer significantly affected artificial intelligence credibility, while foreign humans were perceived as more credible. These findings highlight the intersecting dynamics of scientific politicization and the public politicized understanding of artificial intelligence technology.