Descent Law - Domain Applications

This v0.1 preprint presents domain applications of Descent Law: the proposal-authority boundary applied across media routing, data brokers, institutional meeting procedure, and AI governance. The central thesis is that a claim, motion, score, label, recommendation, or model output is only a proposal until it carries a verifiable descent structure under a declared evaluator. Authority requires an inspectable packet: claim, source, evaluator, evidence path, residual ledger, terminal status, and terminalizer. The recurring operational rule is: no packet, no claim; no residual ledger, no closure; no terminalizer, no action. The paper applies this discipline in four domains. In media routing, it proposes authority-aware claim packets and DescentRank: ranking by verified residual reduction rather than attention or citation popularity. In data-broker regulation, it proposes treating brokered person data as authority-bearing person claims requiring provenance, contestability, use boundaries, expiry, correction paths, and downstream ledgers. In meeting governance, it introduces Observer Rules of Order: a protocol for keeping motions in proposal-status until evidence, residuals, and terminalizers are declared. In AI governance, it states evaluator sovereignty as a design constraint: models may propose actions or evaluator revisions, but they may not own the terminal authority that authorizes execution. This paper is a policy/product application memo, not a statute, legal opinion, deployed product specification, or theorem paper. Its native claims are operational rules, proposed legal architectures, product designs, worked examples, interpretive applications, and scope fences. Lean4 support is included for finite “no terminalizer, no action” packet-boundary cases and sufficient-condition DescentRank cores, but those artifacts do not convert the domain proposals into unconditional mathematical theorems. Legal validity, product efficacy, manipulation resistance, and empirical outcomes remain open deployment and validation questions.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-16
DOI
https://doi.org/10.5281/zenodo.20711513
Primary Topic
Ethics and Social Impacts of AI
Type
preprint
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preprint

Descent Law - Domain Applications

Jeremy H. Carroll
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
preprint

Descent Law - Domain Applications

Jeremy H. Carroll
preprint en

Abstract

This v0.1 preprint presents domain applications of Descent Law: the proposal-authority boundary applied across media routing, data brokers, institutional meeting procedure, and AI governance. The central thesis is that a claim, motion, score, label, recommendation, or model output is only a proposal until it carries a verifiable descent structure under a declared evaluator. Authority requires an inspectable packet: claim, source, evaluator, evidence path, residual ledger, terminal status, and terminalizer. The recurring operational rule is: no packet, no claim; no residual ledger, no closure; no terminalizer, no action. The paper applies this discipline in four domains. In media routing, it proposes authority-aware claim packets and DescentRank: ranking by verified residual reduction rather than attention or citation popularity. In data-broker regulation, it proposes treating brokered person data as authority-bearing person claims requiring provenance, contestability, use boundaries, expiry, correction paths, and downstream ledgers. In meeting governance, it introduces Observer Rules of Order: a protocol for keeping motions in proposal-status until evidence, residuals, and terminalizers are declared. In AI governance, it states evaluator sovereignty as a design constraint: models may propose actions or evaluator revisions, but they may not own the terminal authority that authorizes execution. This paper is a policy/product application memo, not a statute, legal opinion, deployed product specification, or theorem paper. Its native claims are operational rules, proposed legal architectures, product designs, worked examples, interpretive applications, and scope fences. Lean4 support is included for finite “no terminalizer, no action” packet-boundary cases and sufficient-condition DescentRank cores, but those artifacts do not convert the domain proposals into unconditional mathematical theorems. Legal validity, product efficacy, manipulation resistance, and empirical outcomes remain open deployment and validation questions.

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Ethics and Social Impacts of AI
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