Define unsafe-weather override triggers and a fallback | AIGP
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Define unsafe-weather override triggers and a fallback: What control should be completed before deployment?

AIGP Understanding How to Govern AI Development Medium

Define intervention triggers and a fallback process so dispatchers can act safely in real time.

The question

A logistics company is designing an AI scheduler for delivery routes. Weather data may become unreliable, and unsafe routes could create serious risks. Dispatchers will oversee the system, but the design does not yet specify when they may intervene or what happens after a route is rejected. What control should be completed before deployment?

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  1. Define unsafe-weather override triggers and a fallback routing process. ✓
    This gives dispatchers defined intervention authority and specifies what happens when a route is rejected, making oversight operational.
  2. Display model confidence scores beside every proposed route.
    Confidence scores may inform dispatchers but do not define intervention authority, triggers, or the fallback after rejection.
  3. Review route outcomes periodically and revise the model after deployment.
    Retrospective review can improve the system but cannot prevent an unsafe route when unreliable weather data is encountered in real time.
  4. Require dispatcher acknowledgment before every route is released.
    Acknowledgment does not establish when rejection is required or what safe process follows a rejection, and may encourage rubber-stamping.
The trap
A human-in-the-loop design needs defined triggers, authority, and a workable fallback—not merely visibility or sign-off.

How to remember it

Define intervention triggers and a fallback process so dispatchers can act safely in real time.

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