This work is especially important as this is likely to become an increasingly adversarial space in the years ahead. This integrates the watermarking mechanism directly into the image generation process for some types of image generators, which could be valuable for open source models so the watermarking can’t be disabled. For example, Meta’s AI Research lab FAIR recently shared research on an invisible watermarking technology we’re developing called Stable Signature. At the same time, we’re looking for ways to make it more difficult to remove or alter invisible watermarks. We’re working hard to develop classifiers that can help us to automatically detect AI-generated content, even if the content lacks invisible markers. But it’s not yet possible to identify all AI-generated content, and there are ways that people can strip out invisible markers. This approach represents the cutting edge of what’s technically possible right now. If we determine that digitally created or altered image, video or audio content creates a particularly high risk of materially deceiving the public on a matter of importance, we may add a more prominent label if appropriate, so people have more information and context. We’ll require people to use this disclosure and label tool when they post organic content with a photorealistic video or realistic-sounding audio that was digitally created or altered, and we may apply penalties if they fail to do so. While the industry works towards this capability, we’re adding a feature for people to disclose when they share AI-generated video or audio so we can add a label to it. While companies are starting to include signals in their image generators, they haven’t started including them in AI tools that generate audio and video at the same scale, so we can’t yet detect those signals and label this content from other companies. We’re building industry-leading tools that can identify invisible markers at scale – specifically, the “AI generated” information in the C2PA and IPTC technical standards – so we can label images from Google, OpenAI, Microsoft, Adobe, Midjourney, and Shutterstock as they implement their plans for adding metadata to images created by their tools. The invisible markers we use for Meta AI images – IPTC metadata and invisible watermarks – are in line with PAI’s best practices. Since AI-generated content appears across the internet, we’ve been working with other companies in our industry to develop common standards for identifying it through forums like the Partnership on AI (PAI). This is an important part of the responsible approach we’re taking to building generative AI features. Using both invisible watermarking and metadata in this way improves both the robustness of these invisible markers and helps other platforms identify them. When photorealistic images are created using our Meta AI feature, we do several things to make sure people know AI is involved, including putting visible markers that you can see on the images, and both invisible watermarks and metadata embedded within image files. A New Approach to Identifying and Labeling AI-Generated Content What we learn will inform industry best practices and our own approach going forward. During this time, we expect to learn much more about how people are creating and sharing AI content, what sort of transparency people find most valuable, and how these technologies evolve. We’re taking this approach through the next year, during which a number of important elections are taking place around the world. We’re building this capability now, and in the coming months we’ll start applying labels in all languages supported by each app. Being able to detect these signals will make it possible for us to label AI-generated images that users post to Facebook, Instagram and Threads. That’s why we’ve been working with industry partners to align on common technical standards that signal when a piece of content has been created using AI. We do that by applying “Imagined with AI” labels to photorealistic images created using our Meta AI feature, but we want to be able to do this with content created with other companies’ tools too. So it’s important that we help people know when photorealistic content they’re seeing has been created using AI. People are often coming across AI-generated content for the first time and our users have told us they appreciate transparency around this new technology. As a company that’s been at the cutting edge of AI development for more than a decade, it’s been hugely encouraging to witness the explosion of creativity from people using our new generative AI tools, like our Meta AI image generator which helps people create pictures with simple text prompts.Īs the difference between human and synthetic content gets blurred, people want to know where the boundary lies.
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