{
  "handle": "ConcurrentBetHedge",
  "gloss": "Switch one line of development back and forth between two inversely related niches, so that a path to complex function exists where no path exists within a single niche",
  "mechanism": "In a complex niche, valid functions are separated by gaps: from a working gene, every single added change breaks it before a longer working gene is reached, so no step-by-step path of improvements exists against that one target. Pair it with a simpler niche in which the broken intermediate is an advantage (a disabled pathway lowers metabolic load, as yeast mutations harmful in the wild are beneficial in a lab medium). Then, generation by generation, some fraction of the population finds itself in whichever niche currently rewards its form: the intermediate steps pay off in the simple niche, and the completed longer gene pays off in the complex one. The two niches act like a hedge, being inversely related, but used concurrently over time rather than in parallel. This raises {{meta_accuracy}} at the cost of meta-precision, as a {{natural_problem}} requires. It differs from {{exaptation}}, which is a single, decisive switch of target, and it can be read as the population's {{computational_entropy_rate}} being lowered by having two acceptor languages. Done asynchronously over the same code, it can produce overlapping coding sequences.",
  "invariants": [
    "At each step the current form is beneficial in at least one of the niches",
    "The niches are inversely related: what breaks function in one helps in the other",
    "The switching is repeated, not a one-off transition"
  ],
  "preconditions": [
    "Two niches are available whose fitness criteria are approximately inverse",
    "Some fraction of each generation can occupy either niche, by agency or by distribution"
  ],
  "failure_modes": [
    "Evaluating progress only in the complex niche and concluding no path exists",
    "Treating it as a static portfolio split across niches",
    "Assuming the niches are independent, which lowers the odds that each improves"
  ],
  "_meta": {
    "path": [
      "Mind",
      "Strategy"
    ],
    "ring": 2,
    "tier": 3,
    "source": "Adam Timlett, On the Origin of Risk (2025), Ch 15 p.101-103, Ch 18 p.118-127"
  },
  "sema_id": "sema:ConcurrentBetHedge#mh:SHA-256:9c2a799b9cba80a6358823edeb7cee76593e95596853a6715c1f5bf056b47787",
  "sema_ref": "ConcurrentBetHedge#9c2a",
  "sema_stub": "9c2a",
  "dependencies": {
    "references": {
      "computational_entropy_rate": "sema:ComputationalEntropyRate#mh:SHA-256:4f452b8ec7cb60a7e69fa5509ed17eaa33a77019be8631a7bbb71ae1a24c9144",
      "exaptation": "sema:Exaptation#mh:SHA-256:06cae6a4301f79235dfe22ff7cb2f2428bd5fe86b1d689e32e290d48b7bbc783",
      "meta_accuracy": "sema:MetaAccuracy#mh:SHA-256:dd9f9e02d4206c9eb636f9e2bc9356d375fe37c9aa97277f91a04691dbcf7809",
      "natural_problem": "sema:NaturalProblem#mh:SHA-256:ea59543ebcccb8df82bcc1a5e3dace47428a178230154ac53345b0e39daae102"
    }
  },
  "sema_layer": "Mind",
  "sema_category": "Strategy",
  "used_by": {
    "references": {
      "PartialCryptographicChange": "sema:PartialCryptographicChange#mh:SHA-256:aa0b47ebb9952dc028813bc0140379b99d8f92acd23518c6fe95e21dd89d681e"
    }
  }
}