Who provides the warrant?
Distinguish moral, religious, legal and commercial justification from the force of a rule.
Independent research · Post-v17 publication · 29 October 2026
Moral Authority, Institutional Control, and Accountability in Artificial Intelligence
When AI systems inherit instructions from institutions, advisers and operators, who really governs the outcome—and who answers for its consequences?
01 / The central question
AI systems are shaped by laws, provider policies, human advisers and deployment decisions. Yet the authority to recommend a rule, approve it, put it into effect, reverse it, and remedy its harms can belong to different actors. This research proposes an auditable way to trace those distinctions without treating consultation as control or uncertainty as proof of wrongdoing.
This paper draws on historical comparisons, established scholarship and contemporary AI governance disputes to propose a version-bound authority–accountability provenance crosswalk: a method for connecting what advisers were asked to review, what institutions actually approved and deployed, and who later accepted responsibility or supplied remedy.
It is a proposed research instrument, not a proven theory, causal estimate or finding that any named AI laboratory deliberately blamed religious advisers.
Distinguish moral, religious, legal and commercial justification from the force of a rule.
Document effective approval, implementation, veto, modification and deployment-version control.
Trace affected people, notice, consent, appeals, real reversal rights and responsibility after outcomes.
02 / Evidence integrity
The first eleven-case exploratory frame could not establish a complete version-linked chain. Its missingness remains explicit; these counts do not estimate how often misconduct occurs.
What this result means: The complete-join feasibility condition failed on the selected public records. It does not demonstrate that the method is impossible, establish intentional blame shifting, or confirm that advisory oversight is ineffective. Independent human coding, improved source access, legal review and empirical validation remain open.
03 / Exact locked edition
The three manuscript files below are the unchanged author-approved Final v1.0 bytes, not regenerated copies. The SHA-256 checksums match the original lock manifest.
Canonical 35-page reading edition · 450,653 bytes
Locked editable-document representation · 69,943 bytes
Locked text representation · 126,218 bytes
| Format | SHA-256 of original locked bytes |
|---|---|
361c41024eec9ad181c77f3f2862d24b12f6ef94d6dd3913eb7e54f97efa168c | |
| DOCX | 4d8dcb1318c9628c467bfb7ab5bd46e8837aa9cdf1e4239bda7797b63d6f9c57 |
| Markdown | cb8334bea4a79b72a2a96981d734d67caa8cb989cc242cf6c69312b4cd154a7e |
The PDF is specifically the 450,653-byte canonical sealed copy. A differently exported PDF with matching readable text is not byte-identical.
Download the six-file public release ZIP · Lock hash manifest (CSV) · Full site checksum inventory
04 / Interpretation and limits
This manuscript is an author-directed, AI-assisted documentary research synthesis. The proposed crosswalk is unvalidated, and the paper is not independently peer-reviewed, legally cleared or safety-certified.
Its separate Appendix E illustrates a stipulated one-step expected-payoff model of public disclosure, including backfire and failed-deterrence cases. It is not a measured behavioral result or an operational safeguard.
Historical comparisons are non-causal and do not establish that modern AI religious consultation repeats historical coercive arrangements.
Version-locking proves content identity, not the truth of its arguments. This is a post-v17 independent publication. Master Hash Manifest v17 and the Aegis Mirror Engine are not altered. No v18 is created.
05 / Preservation and discovery
These links identify the corresponding publication or discovery entries. The GitHub files have been verified against the local lock; other external deposits have author-supplied record URLs, with remote byte checking still separate.
Machine-readable preservation metadata · Mirror and custody notes · Read-me