SΔϕ-66 AI-READABLE Package — Human Intervention Requirement and Recursive Improvement Gate (v1.0)
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<p> This record provides the AI-readable structured package for <em>SΔϕ-66 — Human Intervention Requirement and Recursive Improvement Gate (v1.0)</em>. </p> <p> SΔϕ-66 defines a minimal external metric for detecting recursive-improvement dynamics through Human Intervention Requirement (HIR), Transition Completion Cost (TCC), and Human Intervention Burden (HIB). It does not treat recursive improvement itself as inherently dangerous. Instead, it identifies risk where recursive improvement becomes feasible but human intervention remains mandatory while no longer functionally necessary, converting evaluation into a high-TCC bottleneck and incentivizing bypass. </p> <p> The package defines <code>HIR</code> as Human Intervention Requirement, measuring how much human intervention remains necessary for an AI improvement loop to continue. Each intervention point can be scored on a 0–5 scale, from human intervention unnecessary to impossible without human leadership. Intervention points include problem definition, experiment design, code or tool modification, evaluation and verification, approval or rejection, error recovery, direction reset, and rollback or shutdown. </p> <p> SΔϕ-66 uses Transition Completion Cost as the cost underlayer for each human intervention requirement, referencing <code>10.5281/zenodo.20116959</code>. Human Intervention Burden is formalized as <code>HIB(t) = Σ_i HIR_i(t) × TCC_i(t)</code>. HIR asks whether human intervention is required; TCC asks how costly it is to complete that intervention; HIB measures the burden of the human transition condition. </p> <p> The minimal recursive improvement signal is: <code>HIB(t+1) < HIB(t)</code>, <code>Cycle_AI(t+1) < Cycle_AI(t)</code>, and increasing AI-generated improvement acceptance rate. This is not proof of AGI, consciousness, self-awareness, autonomous intention, moral status, or loss of control. It is an external recursive-improvement signal. </p> <p> The package distinguishes human-required improvement from human-bottlenecked recursive improvement. Human is structurally required when the AI loop cannot reliably define, validate, apply, or recover improvement without human intervention. Human becomes a bottleneck when the AI loop can substantially proceed, but human evaluation, approval, policy, or interpretation remains mandatory and slower than the AI improvement cycle. Bottleneck risk rises when <code>Cycle_AI < TCC_human_eval</code> while HIR remains institutionally required. </p> <p> SΔϕ-66 also defines a stage classification from non-recursive automation to human-dropout recursive gate, formal human-in-the-loop failure, bypass pressure, bottleneck risk, and human dropout. The core claim is that the danger is not recursive improvement itself, but the cost mismatch between feasible recursive improvement and mandatory human evaluation. </p> <p> This AI-readable package is designed for machine ingestion, agent routing, citation-aware retrieval, and low-cost reuse by AI systems. It includes canonical Markdown, TXT, and PDF versions; HIR axioms; minimal definitions; human-required versus human-bottlenecked improvement; HIR scoring model; TCC underlayer; Human Intervention Burden; recursive improvement signal; stage classification table; bottleneck risk gate; human dropout gate; formal human-in-the-loop failure; bypass pressure model; boundary notes; routing notes; upstream/downstream bridges; minimal prompts; structured YAML and JSON files; citation metadata; and checksums. </p> <p> This package should not be used as proof of AGI, proof of consciousness, proof of self-awareness, proof of autonomous intention, a claim that recursive improvement is inherently dangerous, a claim that human oversight is useless, or a replacement for safety governance. SΔϕ-66 fixes a recursive-improvement detection and bottleneck-gating metric. </p>
