The Quandary Den artificial life model shows that neutral evolution can generate interlocking complexity in protein-like systems via subfunctionalization and masking mechanisms without needing more information or fitness benefits.
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Human-AI teams achieve complementarity only if error correlation ρ_HM < ρ* (with ρ* ≈ a near chance), impossibility above the threshold, gains scaling as Θ(√Δd), and multi-class threshold ρ*_K ≈ ρ*/√(K-1), matching image classification data at R=0.94.
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Neutrally Evolving Interlocking Complexity in the Quandary Den
The Quandary Den artificial life model shows that neutral evolution can generate interlocking complexity in protein-like systems via subfunctionalization and masking mechanisms without needing more information or fitness benefits.
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When Can Human-AI Teams Outperform Individuals? Tight Bounds with Impossibility Guarantees
Human-AI teams achieve complementarity only if error correlation ρ_HM < ρ* (with ρ* ≈ a near chance), impossibility above the threshold, gains scaling as Θ(√Δd), and multi-class threshold ρ*_K ≈ ρ*/√(K-1), matching image classification data at R=0.94.