The essay introduces 'decoherence' as the accumulation of locally valid but mutually incompatible or redundant models within a system, arguing that widespread AI generation is producing this at an unsustainable rate. While decoherence rules out the threat of runaway recursive AI self-improvement, it instead points toward a different risk: 'decoherence collapse,' where the cost of managing and translating between conflicting models becomes overwhelming.
Background
This essay explores the concept of decoherence in AI-generated information ecosystems, drawing an analogy from quantum physics to describe how contradictory models accumulate and degrade systemic coherence. It responds to concerns about AI doom scenarios by reframing the risk in terms of informational entropy rather than intelligence explosion.
- Source
- Lobsters
- Published
- Oct 17, 2026 at 12:36 AM
- Score
- 5.0 / 10