Communications in Humanities Research ISSN: 2753-7072
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Research Article

Government, Enterprises, and Public Opinion: Influencing Factors Driving the Evolution of AI Value Alignment Agenda

Zhiwen HeSouthwest University of Political Science and Law*

* Corresponding author: [email protected]

Abstract

Since the release of ChatGPT in November 2022, generative artificial intelligence (AIGC) has rapidly penetrated all fields of civil applications. This process has broken the traditional paradigm that AI research, development and feedback were confined to laboratories, turning the vast public opinion arena into a critical testing ground for AI value alignment. This study focuses on the critical policy window from March 2023 (concurrent release of Ernie Bot and GPT-4) to August 15 (official implementation), and examines how public opinion, through the mechanism of "reverse agenda setting", cooperates with government regulation to promote AI value alignment and technological adaptation. Using co-occurrence network analysis and quadratic assignment procedure (QAP) regression model, this study empirically tests the keyword networks of Sina Weibo users, official accounts of AI enterprises and policy texts of the Cyberspace Administration of China. The findings show that: Public forcing mechanism: In the early stage of policy making, public opinion significantly predicts the government agenda (β=0.216, p<0.001). Limitations of government regulation: The government transforms fragmented public opinion into structured policies by screening issues such as "security". Tripartite governance paradigm: After government intervention, the explanatory power of the model is significantly improved (R²=0.488), forming a closed loop of "public initiation—government regulation—enterprise framing". This study theoretically expands network agenda setting (NAS) theory by extending the research subject from the traditional "media-public" duality to the "public-government-enterprise" tripartite interactive structure.

Keywords: Public Opinion; AI Value Alignment; Network Agenda Setting; Reverse Agenda Setting; AI Risk Management
Published: July 22, 2026
DOI: 10.54254/2753-7064/2026.35420
Volume: CHR Vol.116
pp. 121-130
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References

  1. Jaung, W. (2026). Does AI value the environment? Evaluation of AI value alignment.Technological Forecasting & Social Change, 225, 124550.
  2. Novotny, M., Weber, W., Kern, C., & Kreuter, F. (2025). Measuring public opinion towards artificial intelligence: Development and validation of a general AI attitude short scale.AI & Society. Advance online publication. 1–33.
  3. Qi, W., Pan, J., Lyu, H., & Luo, J. (2024). Excitements and concerns in the post-ChatGPT era: Deciphering public perception of AI through social media analysis.Telematics and Informatics, 92, 102158.
  4. Moriniello, F., Martí Testón, A., Muñoz, A., Silva Jasaui, D., Gracia, L., & Solanes, J. E. (2024). Exploring the relationship between the coverage of AI in WIRED magazine and public opinion using sentiment analysis.Applied Sciences, 14(5).
  5. Zhang, Y. (2026). Challenges and optimization paths of media discourse in the context of we-media.Journal of News Research, 17(4), 14–19.
  6. Wen, H. (2025). The impact of we-media on the news communication pattern of traditional media.China Newspaper Industry, (18), 64–65.
  7. Liu, M., & Liu, L. (2025). Research on government public opinion guidance mechanism and credibility construction in the new media environment.International Public Relations, (20), 152–154.
  8. Xu, P. (2024). Analysis of reverse agenda setting from the perspective of actor-network theory: Taking the “landlord inspecting damage with a lamp” incident in Jiangxi as an example.Journalism & Communication, (18), 25–27.
  9. Triantantyllopoulos, L., Paxinou, E., Tzanoulinou, D., Verykios, V. S., & Kalles, D. (2026). The value alignment problem in advisory AI: A systematic literature review.AI and Ethics, 6(1), 147.
  10. Huang, L. T. L., Papyshev, G., & Wong, J. K. (2024). Democratizing value alignment: From authoritarian to democratic AI ethics.AI and Ethics, 5(1), 1–8.
  11. Watson, E., Viana, T., Zhang, S., Sturgeon, B., & Petersson, L. (2024). Towards an end-to-end personal fine-tuning framework for AI value alignment.Electronics, 13(20), 4044.
  12. Peterson, M., & Gärdenfors, P. (2023). How to measure value alignment in AI.AI and Ethics, 4(4), 1493–1506.
  13. Schuster, N., & Kilov, D. (2025). Moral disagreement and the limits of AI value alignment: A dual challenge of epistemic justification and political legitimacy.AI & Society, 40(8), 1–15.