Proposed
Training load pays its own interconnection and water
Households are not the residual claimant. Interruptible tariffs for training clusters.
No compiled flow or public database names this control yet.
Who should own it
Utility regulators
Regulators
How quickly it can land
Months
A planned program, one to two quarters.
Expedited implementation
3 months
90 calendar days with a crash team
Normal implementation
9 months
270 calendar days as a planned program
Risk this mitigates
16Given that AI data centres are already being cited by officials as a water-and-grid crisis, and household rates are being raised to underwrite them, there is a possibility of training and inference load outrunning local water, power, and political consent resulting in blackouts, agricultural water loss, and a public that experiences AI as a utility bill.
Residual composite 16 · still above the threshold
Effect if implemented
Applied to every failure scenario on that risk, then re-ranked. Axes are clamped at 1.
- Likelihood
- −0
- Consequence
- −1
- Urgency
- −1