Reconstruction of News Communication Subjects Based on Strong Artificial Intelligence Technology: Potential Overlap and Industrial Syndrome
- DOI
- 10.2991/978-2-38476-444-0_12How to use a DOI?
- Keywords
- news communication; generative artificial intelligence; news risk; AI governance; news crisis
- Abstract
Artificial intelligence is developing in the field of news dissemination, integrating into the entire process from content creation to verification. It has become the core of content creation, driving the transformation of information dissemination from personalized to customized and enhancing the experiential aspects of content presentation, as well as the rise of the “AI governance AI” model. However, its rapid development has also sparked concerns, leading to crises in digital trust, the expansion of platform power, weakening of realistic reflection capabilities, and failures in governance. Therefore, focusing on the protection of privacy and copyright, being vigilant against the excessive use of deep faking technologies, exploring new methods of “AI governance AI,” and adhering to humanistic principles have become the core of addressing risks associated with generative artificial intelligence.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yuanze Liu PY - 2025 DA - 2025/07/10 TI - Reconstruction of News Communication Subjects Based on Strong Artificial Intelligence Technology: Potential Overlap and Industrial Syndrome BT - Proceedings of the 3rd International Conference on Language and Cultural Communication (ICLCC 2025) PB - Atlantis Press SP - 90 EP - 97 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-444-0_12 DO - 10.2991/978-2-38476-444-0_12 ID - Liu2025 ER -