Intuition When Sensors Lie: Leadership Lessons from Gary Klein’s Sources of Power

This week counted actuator energy and asked who owns the power plan. Part III goes upstream of structure entirely, to the moment a sensor reports a confident number that’s wrong, through Gary Klein’s Sources of Power (MIT Press, 1998).

Klein studied how experts decide under time pressure without full analysis: fire commanders, pilots, nurses. They recognize a pattern from a library of lived cases, mentally simulate one action, and act or reject it, recognition-primed decision. Physical AI recreates that setting and adds a trap: a confident model that’s sometimes simply wrong (drifted calibration, novel payload, blinded camera, stale training data), while the system runs on regardless. The running example: a vision agent clears a weld at 98%; a supervisor hears a pitch tied to a porosity defect the camera can’t see, and stops the cell in under two seconds. The agent wasn’t wrong about the pixels, it never had her cue. If policy demands a ticket first, the scrap surfaces hours later at far higher cost, while the dashboard still shows green.

Leaders must protect three conditions, none of which survive by accident: real experience (keep experts on shift), feedback on every override, and permission to act on anomaly. Your action this week: ask whether your best operator can still stop your most AI-supervised line in two seconds, or whether the stop needs a ticket first. Full framework at renegrywnow.com.

Reflection questions

  • Can your best operator stop your most AI-supervised line in two seconds, or does the stop require a ticket first?

  • Does the person who overrides a model ever find out afterward whether they were right?

  • Are you keeping experienced operators on AI-supervised lines, or rotating away the case library that catches what the sensor misses?

Keywords: Recognition-Primed Decision, Gary Klein, Sources of Power, Human-in-the-Loop, Sensor Failure, Expert Judgment, Override Authority, Case Library, Human Oversight, Physical AI

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Series: Energy Dominance · Week 41 · Part III
Previous: Part I — The Hidden Energy Bill · Part II — Who Owns Robot Power Planning.

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Who Owns Robot Power Planning — Operations, Energy, or IT?