Governance Proportionality
The Principle
Governance sophistication should scale with the capabilities being governed. Too little governance for powerful systems creates risk. Too much governance for nascent capabilities creates drag without benefit.
Why This Matters
Most governance conversations implicitly assume more governance is better, or frame governance as a constraint on innovation. The proportionality principle rejects both framings.
The goal isn’t maximum governance or minimum governance. It’s calibrated governance: mechanisms that can actually match the complexity, scale, and velocity of what they’re trying to govern.
This applies beyond national AI policy. Organizations adopting AI face the same dynamic: governance infrastructure that worked for traditional software may be inadequate for AI systems, but governance designed for frontier capabilities may be overkill for narrow applications.
How to Apply
Match instruments to capabilities: Don’t govern a chatbot like an autonomous weapons system. Don’t govern a frontier model like a spam filter.
Distinguish capacity from effectiveness: Having governance structures isn’t the same as achieving governance outcomes. Measure whether governance is actually working, not just whether it exists.
Anticipate scaling: Build governance infrastructure slightly ahead of capability deployment. The gap between capability and governance tends to widen under rapid development unless governance is proactively scaled.
Monitor the income-governance paradox: Advanced capabilities create governance complexity faster than formal structures can absorb. Public trust may erode precisely as governance instruments proliferate. Watch for this pattern.
When This Especially Matters
Any rapidly evolving capability domain. Any context where deployment is outpacing understanding. Any situation where governance overhead is criticized as “slowing things down,” the answer isn’t no governance, it’s right-sized governance.
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