发表机构
Real Good AI（Real Good AI）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对现有AI内容披露仅依赖二元分类或技术水印的不足，提出REAL评级框架，通过六级量表披露AI在创作与体验中的参与程度，并详述其跨模态应用方法。
AI 中文摘要
生成式人工智能已日益融入数字媒体，并更普遍地融入公众频繁互动的生产工作流程中。当前的内容来源标准与披露方法通常依赖二元分类，仅区分完全由人类创作的内容与由人工智能生成的内容，或依赖于缺乏面向用户清晰度的技术性水印。然而，根据人工智能在最终产品的创作与消费中的不同使用方式，存在截然不同的风险与结果。因此，我们提出了报告的人工智能参与水平（REAL）评级框架，该框架通过引入一个六级量表（0级至5级）来解决这些问题，该量表披露了人工智能在产品创作和用户体验中的参与程度。本文详细阐述了REAL评级系统的结构性方法论，以及其在文本、图像、音频、视频和软件产品中应用的具体细节。
英文摘要
Generative artificial intelligence has become increasingly incorporated into digital media and more generally into production workflows with which the public frequently interacts. Current provenance standards and disclosure methods frequently rely on binary categorizations, differentiating only between entirely human-authored and AI-generated content, or depend on technical watermarking that lacks user-facing clarity. However, there are very different risks and outcomes depending on the different uses of AI in the creation and consumption of end products. Therefore, we propose the Reported Engagement with AI Level (REAL) Rating framework which addresses these concerns by introducing a six-tier scale (Levels 0-5) that discloses the extent of AI involvement in both product creation and user experience. This paper details the structural methodology of the REAL Rating system and the specifics of its application across text, image, audio, video, and software products.
