Definition: A process where frontline supervisors actively shape how AI systems deliver prompts, reinforce expectations, and handle ambiguity—ensuring relevance and buy-in.
Why it Matters: AI adoption fails without field relevance. When supervisors help calibrate, they commit to the system.
Common Mistake: Building execution logic in a vacuum. Frontline involvement is not optional.
Related Concepts: Calibrated Human Oversight, Leadership Language Embedding, Drift Onboarding
Sample Usage: “We didn’t just build the system for supervisors. We built it with them. That’s Supervisor-Led Calibration.”
Synonyms:
supervisor-led-calibration