Learning Decoupling Operator (Δ^L)

Definition

The operator that structurally separates the act of updating from immediate institutional penalty: Δ^L: L → L* such that δU*/δF = 0, where F ∈ {legitimacy, authority, capital, narrative fragility}. Decoupled learning allows institutions to revise beliefs, rules, and models without triggering legitimacy loss, power displacement, or funding withdrawal. Must precede alignment.

Formula

Example

Creating a protected policy learning unit with authority to revise standards, insulated from immediate blame attribution, implements Δ^L. The unit can update models without each update threatening someone's position.

Source

ILA-Core Section 7