{
  "handle": "ShapeControl",
  "gloss": "Keeping an organisation, model or trajectory close to a desired form or target, with information serving that form",
  "mechanism": "A desired shape is defined up front: a target, plan, blueprint, policy, objective or standard. Information from the environment is then used only to detect and correct deviation from that shape, as a self-righting agent corrects for a rocking deck. Information that would push the agent away from the shape is filtered out as noise. Value sits in the shape itself; information is valued only in its service. Shape control is one of three ingredients of organisation growth, next to adding mass and growing information, and it trades off against both.",
  "invariants": [
    "Information is valued only insofar as it restores or maintains the target shape",
    "The target shape is fixed before the information that corrects deviation from it arrives",
    "Control of shape weakens as mass is added faster or as information is pursued for its own value"
  ],
  "preconditions": [
    "A desired shape or target can be stated explicitly"
  ],
  "failure_modes": [
    "Treating every risk as a problem of better shape control and missing the value of changing shape",
    "Discarding as noise information that would be valuable to a different shape",
    "Overcommitting to an initial shape whose small error grows as more is invested in it"
  ],
  "_meta": {
    "path": [
      "Mind",
      "Strategy"
    ],
    "ring": 2,
    "tier": 2,
    "source": "Adam Timlett, On the Origin of Risk (2025), Introduction p.14, Ch 2-4"
  },
  "sema_id": "sema:ShapeControl#mh:SHA-256:185f506a48d483fc549fb77ece35dc1f3c54180a0c31657960a2fa6daf155a2d",
  "sema_ref": "ShapeControl#185f",
  "sema_stub": "185f",
  "sema_layer": "Mind",
  "sema_category": "Strategy",
  "used_by": {
    "references": {
      "AnthropomorphicRiskBias": "sema:AnthropomorphicRiskBias#mh:SHA-256:abbe331f94cedf8bf3306ff3e638db4821bb4b624a3c35cccee6b2cf9e5bfe9b",
      "ExplosiveNoise": "sema:ExplosiveNoise#mh:SHA-256:fde13e8fe8e40d0be4bd3e133570f284ff8d1dc5edab8dde4b029c09eb96e8d3",
      "FractalityTest": "sema:FractalityTest#mh:SHA-256:54821a508ea02eee285d10a669d27ed3a6179e5d6e3169c25faf14cba63ec323",
      "InformationDividend": "sema:InformationDividend#mh:SHA-256:80a31b65e2e233ba0230d8a6477e43b1d8308ae8a020e5135f1665602ec79280",
      "MassAmplifiedError": "sema:MassAmplifiedError#mh:SHA-256:19b274047a79ec641a4d9db1074d82de3def8c245515a6d57ba7b7df605d6c70",
      "OrganicWork": "sema:OrganicWork#mh:SHA-256:3df69c75934f1e354c6a414cbf27652ad76389f9605b7059c57a176c93337cbc",
      "OrgChartBias": "sema:OrgChartBias#mh:SHA-256:71b1eb2b8eea243b25753f2e17134f501ebe6982f33ebe23b34f1d71af266063",
      "ResourceShapeSeparation": "sema:ResourceShapeSeparation#mh:SHA-256:a134b6a1aba900011db79661ee8a6c3cb9a4cc1e0da8ff78e1286afc9954a657",
      "SelfCheckingBias": "sema:SelfCheckingBias#mh:SHA-256:a395d033d3f7b496343149133cfd76ffa831aacf8c2ce455e42c5fc54cc714b6",
      "ShapeLossAsGrowth": "sema:ShapeLossAsGrowth#mh:SHA-256:e110c719cd96e48f7580d5438f7aa093c035ea39ab7cd27d6d6f4ace400e4bbd",
      "ShapeMassInformation": "sema:ShapeMassInformation#mh:SHA-256:cc79283f222d0fa3398ad741d5e4f96363103dc191d538a28d6e7a5ee4f6a16b",
      "WeatherAgent": "sema:WeatherAgent#mh:SHA-256:25e1d749c629abfedc88613c936da6d6aa40e661d411d6764fe70b30ae690274"
    }
  }
}