Unmasking AI: Informing Authenticity Decisions by Labeling AI-Generated Content

被引：0
|
作者：
Burrus O. [1 ]
Curtis A. [1 ,2 ]
Herman L. [1 ,2 ]
机构：
[1] Adobe, United States
[2] Oxford University, United Kingdom
来源：
Interactions (N.Y.) | 2024年 / 31卷 / 04期
关键词：
Artificial intelligence;
D O I：
10.1145/3665321
中图分类号：
学科分类号：
摘要：
The rapid proliferation of artificial intelligence technologies has ushered in a transformative era in content creation, and with it, shifting perceptions of what makes content authentic. The notion of authenticity (i.e., the accuracy, reliability, and trustworthiness of content) becomes particularly fraught in the context of content made using generative AI (GenAI) tools [[]1] such as DALL-E, ChatGPT, or Adobe Firefly.
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页码：38 / 42
页数：4
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