Emotion as Media - Opportunities and Myths of AI Video Enabling Mainstream Media’s Youthful Expression and Emotional Communication
- DOI
- 10.2991/978-2-38476-297-2_84How to use a DOI?
- Keywords
- AI Video; Generative Video; Virtual People; Mainstream Media
- Abstract
AI technology has injected new vitality into the field of short videos and promoted the integration of traditional culture and modern audiovisual forms. A series of AI video practices of CCTV stations demonstrates the advantages of AI in cultural communication, and at the same time exposes the problems of technical limitations, loss of meaning, and ethical risks. This paper analyzes the mainstream media’s AI video applications and the opportunities and challenges posed by its youthful expression and emotional communication. To achieve a harmonious symbiosis between technology and culture, it is necessary to adhere to original research, promote the development of AI technology with Chinese cultural characteristics, and continuously explore strategies to solve technical limitations and ethical dilemmas in practice.
- Copyright
- © 2024 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 - Xinyun Zhang PY - 2024 DA - 2024/10/31 TI - Emotion as Media - Opportunities and Myths of AI Video Enabling Mainstream Media’s Youthful Expression and Emotional Communication BT - Proceedings of the 2024 8th International Seminar on Education, Management and Social Sciences (ISEMSS 2024) PB - Atlantis Press SP - 675 EP - 681 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-297-2_84 DO - 10.2991/978-2-38476-297-2_84 ID - Zhang2024 ER -