Enabling ethical AI research through provenance disclosure

Truepic worked with researchers from the Affective Computing group at MIT Media Lab to add secure, cryptographic provenance to over 30 deepfake videos.
AI Research example

OUR PURPOSE

Secure disclosure for ethical AI research

Safe, scalable research is critical to understanding the impacts of generative AI and synthetic media. As research on generative AI and synthetic media grows, content transparency can help researchers inform participants and add lasting attribution to synthetic content. This kind of cryptography-powered disclosure and attribution helps to reduce the risks of synthetic media being taken out of context after it is used in academic research.

sign C2PA example

Sign each image and video

Truepic worked with researchers from the Affective Computing group at MIT Media Lab to add secure, cryptographic provenance to over 30 deepfake videos.

display C2PA example

Display provenance details

The research team used provenance to debrief participants in their study and ensure these synthetic media files were traceable back to their institution.

C2PA STANDARD

Transparency for a growing field of study and innovation

Using the C2PA open standard, the researchers were able to disclose and attribute the AI-generated videos they had shown to participants during the experiment. Correct attribution, sealed into each video file, helps reduce the risk that videos used in an experiment will be taken out of context.

HOW IT WORKS

A first-of-its kind example. A growing best practice.

Integrate and display Content Credentials on your platform. With Truepic, you can embed, sign, and showcase verified media, ensuring transparency and trust in every piece of content you present.

Customizable

Everything needed for implementing C2PA, from image creation to content credential verification and display.

Attribution

With transparent, tamper-evident content provenance data, research institutions can ensure that synthetic content is correctly attributed and traceable, back to them.

Interested in learning more? We’d love to hear from you.