India’s proposed deepfake rules (Oct 22) are a huge signal: they don’t just ask platforms to take down content, they want mandatory, persistent labeling on all AI-generated media. Specifically, a label must cover 10% of an image/video’s surface area or the first 10% of audio.
This moves liability upstream to the developer/platform. Forget policy, what is the immediate technical challenge this creates for your GenAI product? Is it model retraining overhead, metadata permanence, or the product experience hit of a massive watermark? How do you even enforce 10% visibility on mobile?
The metadata traceability is the real hell. A user uploads an image to my platform that was generated by a different, unregulated AI tool. The rule says I have to label it and ensure permanence. I can watermark, but how do I technically verify a user’s declaration that their content is synthetic? We’re being asked to build a deepfake detection engine that’s 100% accurate, or else we’re liable. Impossible.
10% visible surface area is a product killer. We just spent a year optimizing UX for mobile immersion. Now our core value prop, user-generated media, has a giant, mandated watermark. This is effectively a tax on innovation. People will just use offshore, unregulated models and manually crop the label out before uploading to bypass the platform’s detection. The rule punishes the compliant.
We are only serving the US and Europe right now, but this is clearly the global trend. Our plan is to build a generic, standardized Content-Source header/metadata field now and make the visual “10% label” a regional configuration flag. We will treat the Indian rule as the maximum viable compliance standard and architect for it globally. Get the non-visual infrastructure right first. Visual compliance can be adjusted later.