Decision inputs
Facts that change the policy answer
The working material is an open dataset and documented quality rules; the intended result is a corrected and structured dataset. Recording that pair prevents a vague approval from spreading to other uses.
- 1Task and owner
- Data researcher wants to clean a public dataset. The policy check should identify who can approve, correct or withdraw a corrected and structured dataset.
- 2Information involved
- An open dataset and documented quality rules. Check uploads, history and connected systems before describing the request as low sensitivity.
- 3Tool and account
- An approved company account. The request should identify the exact account because product-level approval leaves important controls unknown.
- 4Intended result
- The expected result is a corrected and structured dataset. Follow the result to its real endpoint so the request captures its practical effect.
- 5Consequence if it is wrong
- Automated corrections can change meaning or remove unusual but valid records. That risk sets the level of review and the person who should receive an exception.
- 6Human review
- data steward should inspect, change, reject or stop the result. Review is meaningful only when that person has enough context and authority to change the result.
Possible policy routes
The task name alone cannot decide it.
A published workplace policy can return different answers for the same task. These are the practical branches worth encoding.
A routine policy route may be possible
The least restrictive path starts only after the exact account is approved, only the minimum public information is used, a corrected and structured dataset remains within the stated purpose, and data steward reviews it before use.
Approval may be required
A named reviewer should take over when the account or data handling is uncertain, automated corrections can change meaning or remove unusual but valid records, or a corrected and structured dataset reaches people or systems beyond the requester’s authority.
The request may need to stop or change
A stop or redesign route becomes relevant if restricted information would enter an unapproved service, the output would act before data steward can intervene, or log transformations and compare a sample with the original source cannot be maintained. Consider less information, a controlled account or a non-AI process.
Request checklist
Questions to ask before using the tool
- 01
Which approved account will perform clean a public dataset, and what external connections can it reach?
- 02
Could an open dataset and documented quality rules be reduced to a short de-identified extract?
- 03
Will a corrected and structured dataset remain working material, reach another person or make another system act?
- 04
Who replaces data steward when the request falls outside ordinary expertise?
- 05
Which change in tool, data, purpose or impact would require a fresh request?
Worked request
What the employee should submit
This example supplies decision facts without pasting the underlying material into the approval record.
- requester
- data researcher
- task
- Use AI to clean a public dataset.
- information
- an open dataset and documented quality rules
- tool
- An approved company account
- frequency
- Recurring work
- region
- Where the work and affected people are located
- purpose
- Analyse
- impact
- Internal work
- review
- Complete human review
- owner
- data steward
Useful safeguards
Controls that fit this request
- ✓
Log transformations and compare a sample with the original source
- ✓
Keep whole files, mailboxes and datasets out of the prompt when a short part of an open dataset and documented quality rules is enough.
- ✓
Reassess the request whenever its tool, information classification, frequency or consequence changes.
- ✓
Link the completed check to the applicable policy version and append later reassessments separately.
Questions people ask
About this AI use
Is using AI to clean a public dataset automatically allowed?
The task name cannot settle the answer. Apply the company’s published rules to an open dataset and documented quality rules, the exact account, a corrected and structured dataset, its audience and the proposed review.
What belongs in the employee’s request?
Describe a corrected and structured dataset, identify an open dataset and documented quality rules, name the exact tool and account, explain who will receive or rely on the output, and state how data steward will review it.
Which evidence makes the answer reproducible?
Link the completed check to the applicable policy version and append later reassessments separately. A classification and controlled reference may be enough when copying an open dataset and documented quality rules would create unnecessary risk.