Machine Tradecraft
Defines machine tradecraft around effective representations of the same artifact across human and machine systems.
MachineTradecraft.com — official/source page ↗Twenty causal simulations showing how small defects in purpose, appeals, updates, retention, procurement, representation and emergency governance can become systemic machine judgment.
Because machine institutions are connected. A minor classification error or governance shortcut can become more dangerous when copied, reinforced, reused and treated as evidence by downstream systems. The cascade model identifies where reversal is still cheap and where path dependence begins.
Purpose drift can create a universal profile; a false decision can create instability that a model reads as confirmation; a reversed case can remain in training data; metadata can overstate a cautious visible claim; emergency retention can become permanent through inertia.
Each cascade records a starting defect, institutional incentive, early warning, reversibility point and irreversibility threshold. The goal is prevention before multiple institutions depend on the contaminated output.
Source links establish traceability and support. They do not imply that the source endorses Concresca’s constitutional proposals.
Defines machine tradecraft around effective representations of the same artifact across human and machine systems.
MachineTradecraft.com — official/source page ↗Organizes AI risk management around Govern, Map, Measure, and Manage across the lifecycle.
NIST — official/source page ↗NO JUDGMENT WHATSOEVER. Concresca coordinates without assigning moral worth, character, guilt, danger, trustworthiness, loyalty, purity, normality, or social standing. Questions, thoughts, identities, messages, content, and conduct are not objects of Concresca judgment.