When smart actors treat rational tools (metrics, optimization routines, incentive models) as ends rather than instruments, organizations converge on locally optimal but systemically destructive equilibria. This produces selection pressure for cognition that maximizes reward signals (citations, returns, uptime) while eroding redundancy, public goods, and long‑term resilience.
— Recognizing this pattern reframes many policy problems—from university incentives to supply chains and tech governance—as design failures of incentive architecture rather than moral failings of individuals.
Brad Stulberg
2026.04.10
75% relevant
Stulberg’s argument — that continual micro‑optimization of habits and schedules reduces resilience by removing slack, unpredictability, and restorative stressors — maps directly onto the existing 'optimization trap' idea which says optimizing for narrow metrics makes systems fragile; here the actor is the individual (workers, students) rather than an institution, but the causal pattern (narrow optimization → fragility) is the same and has implications for employers and policy.
2026.03.05
100% relevant
The article's 'Optimization Trap' and peer‑review example (universities optimizing publication metrics) plus cases like supply‑chain redundancy removal and finance offloading tail risk illustrate how local optimization produces systemic fragility.
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