{
  "handle": "AnthropomorphicRiskBias",
  "gloss": "The gap between how humans model and manage risk and how organisms manage it: decision over organisation, prediction over creation, control of shape over change of shape",
  "mechanism": "Compare the way humans model risk, in intuition and in formal mathematics alike, with the way organisms manage it, and treat the difference as a bias to correct. It has five parts. (1) Humans focus on decision-making over organisation growth. (2) They focus on prediction over creation as the way to control outcomes. (3) When they do attend to organisation, they frame it as tighter {{shape_control}}: objectives, targets, constraints, plans. (4) As a result they read curves such as exponential growth as shapes to hit, when they are better read as loss of shape. (5) They have under-examined how computer theory relates to the mathematics of prediction and optimisation. Human solutions therefore lean towards {{mono_modularity}} and {{multi_modularity}}, while Nature leans towards {{meta_modularity}} and values {{information_growth}} that changes shape. The bias is not found by experiments on subjects, because the experimenters share it; it shows up by contrast with biology.",
  "invariants": [
    "The bias is defined as a difference from the biological body plan of risk, not from an ideal rational agent",
    "It is shared by scientists, mathematicians and economists as well as lay decision-makers",
    "Correcting it adds strategies; it does not throw away decision, prediction or shape control"
  ],
  "failure_modes": [
    "Treating the bias as a list of individual psychological errors rather than a structural preference for {{mono_modularity}}",
    "Over-correcting by rejecting planning and prediction altogether",
    "Taking biology as a source of loose metaphors rather than of mechanisms to model"
  ],
  "_meta": {
    "path": [
      "Mind",
      "Reasoning"
    ],
    "ring": 2,
    "tier": 2,
    "source": "Adam Timlett, On the Origin of Risk (2025), Introduction p.8-13, Conclusion p.128"
  },
  "sema_id": "sema:AnthropomorphicRiskBias#mh:SHA-256:abbe331f94cedf8bf3306ff3e638db4821bb4b624a3c35cccee6b2cf9e5bfe9b",
  "sema_ref": "AnthropomorphicRiskBias#abbe",
  "sema_stub": "abbe",
  "dependencies": {
    "references": {
      "information_growth": "sema:InformationGrowth#mh:SHA-256:9a86182b8561d0eada5a28b0ceb30fa00500e725d050f760805b8f0da37125de",
      "meta_modularity": "sema:MetaModularity#mh:SHA-256:cb6cc554a6eb00214b5e2fba0504373bc4312dd5d74ec4fdc71bb20224197aef",
      "mono_modularity": "sema:MonoModularity#mh:SHA-256:944c5f3013c718b6999c18f4628b584633ba3a8e294a6c268e0c5e2bfcf1d22e",
      "multi_modularity": "sema:MultiModularity#mh:SHA-256:156543a6f644d72a469b5b23b8b59f178f1d59aa018f7cc26b272641b80c38be",
      "shape_control": "sema:ShapeControl#mh:SHA-256:185f506a48d483fc549fb77ece35dc1f3c54180a0c31657960a2fa6daf155a2d"
    }
  },
  "sema_layer": "Mind",
  "sema_category": "Reasoning",
  "used_by": {}
}