Time needed
90 minutes · 8 steps
What it takes
Nothing to install
What it costs
A free path exists
Last checked
2026-09-01

The steps

Only approved or redacted sensitive material
  • Grants and operations
  • Director or leadership
  • Human rights activist
  • Drafting reports and advocacy material
  • Grants and admin
  • Protecting sensitive information
  • Making sense of large document sets
  • Translation into and out of local languages
These are instructions, not case studies

A recipe tells you what to do. It is not a report of something that already happened somewhere else. Nothing here claims that any organisation did this. It is written for you to do now, and every step tells you how to check it worked.

What you will make

A donor-report draft, a protected source file, a safe working copy, and a claim checklist. The workshop uses synthetic monitoring data. Do not practise on a real beneficiary or incident file.

Sort the material into three lanes

  • Public: published programme descriptions, donor headings, and already released findings may use an approved cloud route.
  • Internal: draft results, partner detail, and ordinary operational data need an approved organisation account or verified local route.
  • Identifiable: names, exact dates, precise locations, case numbers, direct testimony, contact details, and small groups remain in the protected master. They never enter the cloud draft.

Aggregation is not automatic protection. A rare event, small count, location, and month can still point to one person. If the safe copy can be joined back to a public story or local knowledge, keep it local or generalise it further.

Workshop route

  1. Keep the unchanged master under its existing access controls.
  2. Build a second file containing only the minimum fields needed for the report.
  3. Draft from the safe copy and donor headings, marking every missing fact instead of inventing it.
  4. Reconcile the draft with the master, then restore approved detail only in the controlled final file.

Five checks before you finish

  1. Data: no row, quote, date, location, or small group can identify a person.
  2. Input: row counts and indicator definitions match the protected master.
  3. Output: activities, results, dates, totals, and quotations match source records.
  4. Human: programme and finance owners review the sections they own.
  5. Record: the final file records sources, reviewers, date, and any required AI disclosure.

Stop and use another route when

The donor needs case-level detail, the safe copy remains re-identifiable, or nobody can review the working language. A general assistant may help arrange approved text, but it must not translate an unchecked Sorani submission or decide what the evidence proves.

What happens to your information

Never use this for

Do not use the draft as evidence, invent missing results, conceal limitations or submit it without source and disclosure checks.

What leaves your device

Whose law it lands under · The fully offline option

Only the reviewed SAFE file may enter a hosted tool. MASTER, the re-identification key, raw data, names, exact locations and case identifiers remain in approved storage.

Whose law it lands under

Hosted assistants process data under the provider and account terms. A training setting does not remove transmission or all retention.

The fully offline option

Draft manually in MASTER or use a separately verified local route. Local models still require checks for cloud routing, sync, telemetry, backups and device access.

What it costs

Paying for this from Iraq

OpenAI and Anthropic list Iraq as supported, but availability does not prove a payment method will work. Test access and billing before planning delivery.

The free path

If you pay

The method works manually. A free hosted assistant is optional and is limited to data approved for the exact account and lane.

If you pay

No price is required for the workshop. Check current vendor pricing and terms before adopting a paid route.

Before you start

  • The donor template, reporting period, word limits and current disclosure rule.
  • A protected MASTER file and separate SAFE working file.
  • One case-aware reviewer and one authorised approver.
  • Synthetic data for the workshop. Apply the organisation rule before using real data.

Which machines this works on

Use documents and a browser on any platform. Use synthetic monitoring data in the workshop. The SAFE file is allowed into a hosted tool only after a person checks both direct and indirect identifiers.

The steps

  1. Step 1 / 8

    Create a restricted MASTER file and a separate SAFE working file. Keep the key that maps labels back to people only in MASTER.

    Copy this exactly

    REPORT-MASTER-RESTRICTED.docx
    REPORT-SAFE-WORKING.docx

    Check it worked

    SAFE contains no names, contact details, case numbers, protected locations or re-identification key.

  2. Step 2 / 8

    Apply the data gate to SAFE. Remove unnecessary detail, replace people and places with stable labels, generalise dates where possible, and inspect combinations and small groups.

    Check it worked

    A second person who knows the cases cannot identify anyone from SAFE alone. If they can, reduce detail or keep the work manual.

  3. Step 3 / 8

    Choose the route. Use a hosted tool only when SAFE fits the approved lane, account and current terms. Otherwise draft manually or use a separately verified local route.

    Check it worked

    The work log names the product, plan, workspace, settings checked, source, date and approving person.

  4. Step 4 / 8

    Ask for an evidence map before prose. Require the tool to place only supplied evidence under donor headings and mark missing evidence as [GAP].

    Copy this exactly

    Map the supplied evidence to the donor headings. Use only the supplied text. Mark unsupported requirements [GAP]. After each point, cite its source label. Do not draft prose yet.
    
    DONOR HEADINGS:
    [paste]
    
    SAFE EVIDENCE:
    [paste]

    Check it worked

    Every proposed point traces to a supplied source label. The map contains no new number, result, activity or attribution.

  5. Step 5 / 8

    Draft one section at a time. Preserve uncertainty words and require a source-check list after the draft.

    Copy this exactly

    Draft this section in plain professional language. Use only the mapped evidence. Keep every caveat and [GAP]. Do not fill missing information. Then list each factual claim with its source label.

    Check it worked

    Each number, date, organisation, quotation and factual claim appears in the source-check list.

  6. Step 6 / 8

    Verify against MASTER. A person checks each claim, number, name, date, quotation and causal statement. Restore necessary precision only inside the protected final workflow.

    Check it worked

    The checker initials a claim list and every unresolved item remains visibly marked for decision.

  7. Step 7 / 8

    Run the protection check again on the final prose. Rewriting can introduce a distinctive description even when SAFE was de-identified.

    Check it worked

    A hostile reader familiar with the location cannot identify a person or protected site from the submitted text.

  8. Step 8 / 8

    Check the donor rule for AI use and disclosure, record the decision, move approved text into the organisation document, and remove working copies under the retention rule.

    Check it worked

    The final file has an approver, claim checklist, disclosure decision, source list and storage location.

How to know the whole thing worked

Select three claims at random. A reviewer should trace each from the final report to MASTER, confirm that SAFE did not expose a person, and explain the tool and disclosure decision from the log.

What goes wrong, and what to do about it

  • SAFE contains a unique combination of date, place, role or event. Reduce detail or keep the section manual.
  • The model fills a gap with plausible text. Delete it and keep [GAP] until evidence exists.
  • Word-limit editing removes caveats. Compare the short version with the verified draft line by line.
  • The donor has no published AI rule. Ask the programme officer rather than guessing.

How well it works in your language

Arabic (Modern Standard) · Iraqi Arabic · Kurdish (Sorani)

Arabic (Modern Standard)

Useful for structured drafting when a fluent reviewer checks meaning, numbers and institutional terms.

Iraqi Arabic

Convert dialect notes into a formal report only with an Iraqi Arabic speaker checking source and draft.

Kurdish (Sorani)

Treat model output as untested for this workflow. Use a fluent Sorani writer or reviewer for the final report.

What that rests on

Vendor documentation describes controls, not report accuracy. No provider documentation proves correctness on your data or dialect.

Software named in this recipe

  • ChatGPT
  • Claude
  • Google Gemini
  • A manual document workflow

Sources

A CDR original, written for POINT Conference Iraq 7. Checked against vendor pages and package registries in August 2026; the sources are listed on this page.

What we could not verify

De-identification reduces risk but may not prevent re-identification, especially in small communities. Tool controls and donor rules change. Iraqi Arabic and Sorani were not independently tested for this workflow. The safe fallback is manual drafting and human translation.

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