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The AI first draft of an official record and the record of who used AI and on what inputs are not kept with the final version

When AI drafts an official record, the unedited first draft the AI produced is stored and kept for as long as the final record is kept, and an audit trail is kept for the same time that names the person who used AI and the inputs (such as video and audio footage) it used.

Informational data, not legal advice. Summaries and rules have not been reviewed by a lawyer: always verify official law text for decisions. A suggested guard is intended to address each rule; adding it is not a statement of compliance to that law.

Family: AI decisions cannot be reconstructed after the fact · control id cond.ai-first-draft-and-use-record-not-retained

Reach

1items this one guard addresses
1jurisdictions where binding law on it is in force
0more where it is enacted, not yet applying
0standards and frameworks on the same control

Law in force in California (US-CA).

Trust and provenance

How far the rules this guard addresses have been checked. Each rule links to its provision, with its citation, official text and its own panel.

This control
Audit-grade: meets all 3 checks of the TwinEthos audit standard that apply to it.
Lanes
Binding law — in force 1
Verification
Sources last verified 4 Oct 2026; each provision states how.
Data release
Data release 2026.10.04.3, data as of 4 Oct 2026, schema 0.3.10.
Legal review
None of the 1 rule has been reviewed by a lawyer; no TwinEthos rule has been legally reviewed yet. Treat each as research to check against the official text; it is not legal advice. Open questions for counsel on them: 1.
Audit standard
1 of 1 rule audit-grade. The audit standard is TwinEthos's own quality bar for provenance, dates, applicability, detectors, fixtures, remediation and licences; it is not a legal review.
Detectors
1 detector, all experimental: written from the rule's text and not yet measured for precision on real code, so treat a hit as a lead to verify. Each provision lists its detectors' known limits.

The guard to add

Save the AI's first draft unchanged and an audit entry (who ran the AI, which footage) next to the final record, and keep both as long as the record.

The drafting service writes the model's first output to a write-once draft store keyed to the report id before any edit, and an audit row with the invoking user and the footage or audio ids it used; the retention job deletes drafts and audit rows only together with the final report; editing works on a copy, never on the stored first draft.

Where it goes: 1 application source code, 6 API calls and integrations, 14 user-facing text.

What reviewers look for: a persisted first_draft (or equivalent) written from the raw model output before edits; an audit trail with the user and source media ids; retention tied to the final record; no update or delete of the first draft in the edit path.

Example (Python report service), before:

draft = llm.invoke(prompt_from(footage))
report.narrative = draft
save(report)

After:

draft = llm.invoke(prompt_from(footage))
drafts.insert_once(report_id=report.id, first_draft=draft, retain_with=report.id)
audit_trail.record(report_id=report.id, ai_user_id=current_user.id, footage_ids=[f.id for f in footage])
report.narrative = draft  # edits change the report, never the stored first draft
save(report)

Engineering guidance, not legal advice. Each provision below may add its own details (a cadence, a deadline, a required notice element): open it for those.

Every rule this guard addresses

Binding law — in force (1)

Related incidents

No guardrail sits on this exact control; these incidents are cited by guardrails on related controls.

Informational data, not legal advice. Summaries are TwinEthos's own words and rules have not been reviewed by a lawyer: check the official text before relying on any of it. A guard addresses an item; adding it is not a statement that your code meets any law.