Mini thesis
Governance fails when the human is named, but not structurally present.
Many AI governance frameworks speak beautifully about human oversight, responsibility, safety, and alignment. The problem is not the language. The problem is where the human is placed inside the working system.
If the human appears only as final approval, liability holder, reviewer, or policy owner, then the system may still be called human-centered while the real decision gravity sits elsewhere. It can move to model output, stale handoffs, automation defaults, compliance artifacts, or platform convenience.
Signalane begins from the working layer. Who decides? What evidence is current? What happens when the handoff is wrong? Where does correction return? How does the human remain close enough to shape meaning without becoming a bottleneck or a decorative sign-off?
This is why Signalane argues for human-anchored AI cooperation: not humans outside the system, not AI outside responsibility, but a working structure where judgment, evidence, feedback, and authority stay readable.