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Model Drift

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Essay Warns AI-Driven 'Decoherence' Could Trigger System-Wide Collapse

A new essay introduces 'decoherence' as the buildup of locally useful but incompatible or redundant models within a system, where the cost of change becomes dominated by translating between these models and avoiding unintended side effects. The author argues decoherence has always existed but is now being produced at an unsustainable rate due to widespread AI adoption, using an aging office building's plumbing as an analogy for different types of technical debt.