What label should be applied to content produced by generative AI?

Abstract

The rise of generative AI has created pressure for content labeling. This paper investigates the public’s understanding of nine potential labels. Participants from the US (N=1056), Mexico (N=1060), Brazil (N=1065), India (N=1038), and China (N=1031) were shown twenty different types of content that varied in the extent to which they were AI-generated, and the extent to which they were misleading. Across countries and demographic subgroups, participants consistently associated “AI Generated,” “Generated with an AI tool,” and “AI manipulated” with AI-generated content, regardless of misleadingness; and associated “Deepfake” and “Manipulated” with mis- leading content, regardless of AI involvement. Interestingly, “Artificial” performed poorly in China due to translation nuances, but performed well on both alignment tasks in the other countries. Finally, we examined self-reported effects of the terms on belief in, and attitudes toward, labeled content. Our study underscores the need for deliberate decision-making regarding the objectives and implementation of generative AI disclosure.

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