Reconstruction and Integration: The Impact of Artificial Intelligence Generated Content on News Production

Lecture Notes in Education Psychology and Public Media Pub Date : 2024-04-26 DOI:10.54254/2753-7048/50/20240923

Jun Zhang, Yuke Cai, Yanling Xiang, Dapeng Sun

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Abstract

The burgeoning field of Artificial Intelligence Generated Content (AIGC) is garnering widespread attention and discussion across various industries. AIGC, an emerging form of content creation utilizing artificial intelligence, complements traditional content generation paradigms such as Professional Generated Content (PGC) and User Generated Content (UGC). On February 16, 2024, OpenAI officially announced its first text-to-video model - Sora. Sora's capabilities and attributes are sufficient to astonish the world: through text instructions, it can directly output videos up to 60 seconds long. These videos are not simple; they contain highly detailed backgrounds, complex multi-angle shots, and emotionally rich characters, bringing about a revolutionary impact on the news production process. This paper aims to explore the impact of AIGC on the news production process, encompassing aspects of news gathering, writing, and distribution. It also examines the opportunities and risks associated with AIGC's multimodal and large model characteristics. Furthermore, the paper proposes strategies to mitigate risks in AIGC news production from user, technological, and management perspectives, providing insights and contemplations for news producers and practitioners.

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重建与整合：人工智能生成的内容对新闻制作的影响

人工智能生成内容（AIGC）这一新兴领域正在引起各行各业的广泛关注和讨论。人工智能生成内容（AIGC）是一种利用人工智能进行内容创作的新兴形式，是对专业生成内容（PGC）和用户生成内容（UGC）等传统内容生成模式的补充。2024 年 2 月 16 日，OpenAI 正式发布了其首个文本到视频模型--Sora。Sora 的能力和属性足以令世人震惊：通过文本指令，它可以直接输出长达 60 秒的视频。这些视频并不简单，它们包含高度精细的背景、复杂的多角度镜头和情感丰富的人物，给新闻制作流程带来了革命性的影响。本文旨在探讨 AIGC 对新闻制作流程的影响，包括新闻采集、写作和发布等方面。本文还探讨了 AIGC 的多模态和大模型特征所带来的机遇和风险。此外，论文还从用户、技术和管理角度提出了降低 AIGC 新闻制作风险的策略，为新闻制作者和从业人员提供了启示和思考。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Lecture Notes in Education Psychology and Public Media

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