Google is preparing a system to label all AI-generated content
English The company will integrate the C2PA standard into many of its services and systems, including advertising

- September 18, 2024
- Updated: July 1, 2025 at 10:57 PM

Google has announced the implementation of a content authentication technology in its products. Over the coming months, the company will integrate the Coalition for Content Provenance and Authenticity (C2PA) standard into its search, advertising, and potentially YouTube services. The new measure aims to help users differentiate between images created by humans and those generated by artificial intelligence.
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Subscribe (it's FREE) ►Developed by a consortium of tech companies since 2019, the C2PA technology aims to combat the growing amount of AI-generated content, allowing the tracking of content origins and its editing history through metadata. At Google, it will be integrated into features like “About this image” in search, Circle to Search and Lens, showing information about whether an image has been edited with AI.
Laurie Richardson, Vice President of Trust and Safety at Google, acknowledged the challenges of establishing content provenance in such a vast digital environment. “There is no magic solution for all online content,” she stated, while emphasizing the importance of collaborating with other industry players to create sustainable solutions.

With this initiative, Google aligns with other AI transparency measures, such as SynthID, a watermarking technology created by Google DeepMind. The C2PA standard will also be implemented in Google’s advertising systems as part of its transparency policies. In the long term, it could extend to platforms like YouTube, especially for content captured by webcam.
However, the adoption of this technology is not without problems. Many devices and editing tools are still not compatible with C2PA, making it difficult to maintain metadata. Additionally, AI image generators would need to adapt to include this information, which could exclude open-source models.
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