The paper demonstrates how transformation competence serves as a measure of general intelligence in institutional contexts, suggesting implications for assessment and justice.
Most evaluation of artificial intelligence measures task competence, that is, performance onbenchmarks posed within a single space of problems. We argue that general intelligence in delegated,institutionally embedded contexts is instead transformation competence. A capable system must occupya plurality of reason-spaces, each a vocabulary with its own material implications andincompatibilities. It must transform reasons correctly as they cross the boundaries between thesespaces, preserving an identifiable entity's reason-relational profile where the boundary permits andrefusing transfer where it would violate a defining incompatibility. And it must grow a newreason-space where transformation across the existing ones systematically fails. We call the corenorm anaphoric fidelity. A transformation that claims to track the same entity must preserve enoughof that entity's reason-relational profile for the claim to hold, and breaking it is a covertreferential substitution. Monolithic scaling cannot yield transformation competence, because bycollapsing the plurality into one space it can only transfer a reason flat, treating it as validacross boundaries without transformation. Flat transfer is the fault behind familiar failures, froman assessment that drops a person's standing at an institutional boundary to an agent that carriesan instruction or a permission across a context boundary, the confused deputy. We groundreason-spaces in implication-space semantics, give a typology of what can happen to a reason at aboundary, illustrate the criterion on institutional transitions in disability policy, and propose atransformation-competence benchmark that operationalizes both the criterion and the anti-monolithclaim. The criterion has two faces. Over entities it is a criterion of competence, testable on asystem. Over persons it is a criterion of justice, identified with legal capacity. Note on tools: The author used AI-assisted drafting, translation, and editorial tools during thepreparation of this manuscript. The conceptual framing, theoretical argument, selection of sources,responsibility for the content, and final editorial decisions remain with the author.
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Peter Nausner (2026) studied this question.
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