INTERNATIONAL JOURNAL OF HUMANITIES AND SOCIAL SCIENCES (IJHSS)

Ethical Risk and Pathway of AIGC Cross-Modal Content Generation Technology

E-ISSN: 3435-6457

P-ISSN: 8654-3552

DOI: https://iigdpublishers.com/article/542

This study analyses the core technologies underlying AI-generated cross-modal content (AIGC), identifying data, algorithms, and computing power as the fundamental pillars supporting AIGC operation. And data are recognized as the underlying logic driving AI's continuous development and the source of ethical issues within AIGC. By integrating Gilbert Hottois' concept of technological accompaniment, this research incorporates multiple stakeholders to dissolve the binary opposition between humans and machines. This study explores pathways to scientifically and positively advance AIGC technologies at the micro, medium, and macro levels. It advocates for human‒machine symbiosis, enhances the frequency and potential of users' digital interactions, improves their understanding and autonomy in applications, and promotes digital literacy in the intelligent era. Additionally, it emphasizes the importance of government-led initiatives and global dialog to establish a multistakeholder regulatory framework and conventions, aiming to create a more harmonious human‒machine community with a shared future.

Keyword(s) Human‒Machine Communication; AIGC Cross-Modal Content Generation Technology; Technology Accompaniment; Human‒Machine Community with a Shared Future.
About the Journal VOLUME: 10, ISSUE: 1 | April 2025
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Ling Jiang & Yiting Zhang

Zhan, X., Li, B., & Sun, J. (2023). Scenario-based application and development opportunities of AIGC in the context of digital intelligence integration. Journal of Library and Information Knowledge 01: 75-85+55. DOI: 10.13366/j.dik.2023.01.075. 


China Academy of Information and Communications Technology (2022) Artificial Intelligence White Paper. Available at: http://www.caict.ac.cn/kxyj/qwfb/bps/202204/P020220412613255124271.pdf (accessed 10 July 2023). 


Liu, H., Chen, J., Li, L., Bao, B., Li, Z., Liu, J., & Nie, L. (2023). Cross-modal representation and generation technology. Chinese Journal of Image and Graphics 06: 1608-1629. DOI: 10.11834/jig.230035. 


Peng, L. (2023a). AIGC and the new survival characteristics of the intelligent era. Nanjing Social Sciences 05: 104-111. DOI: 10.15937/j.cnki.issn1001-8263.2023.05.011. 


Peng, L. (2024). Human actors in intelligent communication. Journal of Northwest Normal University (Social Science Edition) 61(04): 25-35. DOI: 10.16783/j.cnki.nwnus.2024.04.003. 

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