Wilson questions companies on deceptive AI advertising and disclosures

Thank you, Chair.

My questions are related to my bill, which deals with the disclosures and prohibiting deceptive advertising on AI models.

So my question is, what guardrails on misleading advertising and truthful disclosures do you wish your competitors had to abide by?

And given the complexity of these tools and AI models,

Where are consumers most likely to be misled or confused?

And what do you wish consumers understood better about these tools, capabilities, and risk?

So OpenAI's usage policies prohibit the use of our tools for scams, fraud, and impersonation.

We also embed in every single one of our images and audio content provenance or watermarks or metadata to tell people if the information was AI generated.

And we make tools available so that people can assess whether their content that they are seeing is AI generated.

Council Member, transparency is absolutely foundational to accountability and trust.

For example, our scaling framework has a change log which details each change that we have made to our framework, just as an example of the transparency that underlines our approach.

In relation to your question about competitors, I would just note that I generally think that there are significant laws already at federal and state level regarding misrepresentations.

Yes, sir.

I can honestly say the most important thing to us is continued technical standardization across the industry so that we have common ways to operate and identify the provenance of information.

We're very heartened by the broad adoption of the C2PA content credential that I referenced before.

I also referenced before that we built our own synth ID watermarking technology that many across industry have adopted as one tool

in order to identify when content is generative AI created.

One of the things that we do a lot of at Google is do research into how users interact with information.

You know, search is part of our DNA.

And one of the interesting things about labeling that we've found is that there are users who, when they see a label,

they are less likely to trust that information, but they are more likely to trust unlabeled information.

And just because information that you see online doesn't have a watermark or a label on it doesn't necessarily mean it is automatically trustworthy either.

So we work through and think very hard about what are the ways that we can give users information that they will be able to know the context of what they're.

interacting with and make sound judgments about which information is trustworthy and which isn't.

So this is part of the research that we do.

Council member, our view is that we want Claude, our product, to act unambiguously in the user's interests.

For that reason, we do not run ads, nor are Claude's responses influenced by those of advertisers.

And furthermore, Claude does not generate images.

We sort of try to reduce the risk surface in this way.

Thank you.

Councilmember Osei, followed by Councilmember Hudson, followed by Councilmember Shulman.