This feels like a symptom of a deeper issue: we’re treating AI outputs as if they’re authoritative when they’re really just single, unaccountable generations. Disclaimers help, but they don’t fix the decision process that produced the content in the first place.
One approach we’ve been exploring is turning high-stakes AI outputs (like news summaries or classifications) into consensus jobs: multiple independent agents submit or vote under explicit policies, with incentives and accountability, and the system resolves the result before anything is published. The goal isn’t “AI is right,” but “this outcome was reached under clear rules and can be audited.”
That kind of structure seems more scalable than adding disclaimers after the fact. We’re experimenting with this idea on an open source CLI at https://consensus.tools if anyone’s interested in the underlying mechanics.