Exclusive: Deep dive on AI and watermarking
Watermarking is being tossed around by policymakers as a key way to help people identify AI-generated content, but a new paper says lawmakers should consider more authentication techniques as they develop legislation.
Driving the news: The paper from the Information Technology Industry Council shared exclusively with Axios argues that a combination of methods will be most helpful for consumers to navigate AI content, and that clear standards for authentication are needed for the industry.
- Watermarking — embedding a "signal" in a text or an image to identify it as AI-generated — is just one way to tackle the problem, and the paper argues there are other useful ways to show a piece of content's roots that need to be part of the conversation as lawmakers develop new rules.
Other methods include:
- Provenance, which traces "signals" in a dataset, such as when it was created and modified.
- Metadata auditing, or checking things like editing history, time stamps and device information, which could be useful for copyright concerns, per the paper.
- Human authentication, which would have experts decide whether something has been AI-generated. It would be slower and less reliable but useful in certain cases.
Yes, but: In some cases, marking whether something has been AI-generated may not be necessary at all.
What they're saying: "There's a strong need to examine which use cases and instances where watermarking makes sense, because lower-risk applications might not need that sort of disclosure, such as changing the filter or lighting mode on a smartphone's camera," Courtney Lang, ITI's vice president of policy, trust and data, told Axios.
What's next: Lang said it's too early to tell what type of content authentication method would be best for educating consumers about AI-generated content in elections.