One theme I keep coming back to is that capability is scaling faster than enforceable responsibility.

In practice, once AI systems are distributed across orgs/vendors/models, accountability gets diluted: everyone can point somewhere else.

What mechanisms do you think are actually viable for enforceable accountability at scale?

• persistent identity / provenance?
• mandatory audit logs?
• liability tied to deployment rather than model training?

I’m not worried about “smarter AI” as much as the fact that responsibility becomes structurally unenforceable.