Keep identifiable newcomer client information out of public AI chatbots unless your organization has formally approved the service and verified its legal, contractual and technical safeguards. Treat every public or online AI tool as an external processor. Start by deciding whether AI is necessary, remove direct and indirect identifiers, use an approved workflow, explain the processing when required, and have a responsible person check every output before it affects a client or is shared.
Why newcomer case information needs extra care
Newcomer-serving organizations may hold names, addresses, telephone numbers, immigration or refugee-claim details, identity-document numbers, dates of birth, family relationships, health information, legal histories, financial records, interpreter needs and notes about trauma or persecution. Even when a record contains no name, a rare nationality, a small settlement, an unusual event and a precise date can identify one person when combined.
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An AI prompt is not private merely because it is typed into a chat window, accessed through a familiar browser or covered by a paid subscription. The provider may process, retain, review or use prompts and uploaded files under terms that differ by product, account type, location and administrator settings. A generated summary, classification or risk assessment can also become new personal information about the client.
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A safe workflow before anyone enters a prompt
1. Pause and define the purpose
Write down the task in one sentence: for example, “create a plain-language explanation of a published form” or “suggest headings for a staff training handout.” Ask whether AI is necessary and proportionate. If the task concerns eligibility, safeguarding, legal strategy, credibility, housing access or another decision affecting rights or services, consider whether automation is appropriate at all. Convenience is not a sufficient reason to expose a client record.
- Use AI for a clearly defined administrative or drafting purpose, not open-ended exploration of a case.
- Identify the minimum information needed to achieve that purpose.
- Confirm who will receive the output and how it will be stored.
- Ask the privacy or information-security lead before using any real client information.
2. Prefer synthetic or de-identified material
Use a fictional scenario, a public document or a completely synthetic dataset whenever possible. If real information is necessary, remove names, email addresses, telephone numbers, addresses, client or file numbers, passport and permit numbers, dates of birth, biometric details and other direct identifiers. Replace them with neutral labels such as Client A and broad categories such as “a large Canadian city” rather than a street address.
De-identification is not a one-time find-and-replace operation. Review combinations that could single someone out: a rare language in a small community, an unusual medical condition, a specific incident date, a distinctive family structure, an employer, a detention location or a unique migration route. Canada’s Experience Office guidance for AI help applications warns that de-identified material may remain identifying in combination and that automated redaction can fail. A human must inspect the text and attachments before submission.
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3. Use only an approved service and account
Do not paste case notes into a free public chatbot, an employee’s personal account or an online service that the organization has not assessed. Public-facing availability is not approval. A subscription fee is not proof of confidentiality.
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An approved workflow should specify the service, account type, permitted purposes, data classes, administrator settings and people responsible for review. If no workflow exists, stop and obtain a decision from the privacy lead, security lead or authorized manager.
4. Confirm transparency and any required permission
Where law or policy requires notice, explain in understandable language whether AI is involved, what information is processed, why it is needed, who provides the service and how long information is kept. Whether consent is required depends on the governing law, the organization’s authority and the service context; do not treat a generic checkbox as a universal solution. The Office of the Privacy Commissioner of Canada’s principles call for legal authority and meaningful consent where consent is the basis for processing.
5. Review the result before use
A staff member with appropriate subject knowledge must check an AI output for factual errors, omissions, bias, unsafe advice, inappropriate tone and reproduced sensitive details. Confirm dates, names of programs, eligibility rules, translations and quotations against authoritative records. Never allow an AI-generated label, summary or “risk score” to silently become an official fact about a client.
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Store the approved prompt and final output only where organizational policy allows. Apply the same access controls used for the underlying case. Keep an audit record of who used the service, for what purpose and who approved the result when the activity is material. Follow a retention schedule: delete prompts, uploads, logs and drafts when they are no longer needed, while preserving records that must be retained for legal, funding or safeguarding reasons.
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How to assess an organization-approved AI service
Before approval, document answers to each question below. Obtain written terms or technical evidence rather than relying on a sales statement or a default setting.
| Assessment area | Questions to answer | Decision evidence |
|---|---|---|
| Purpose and data minimization | Is the intended task necessary? What exact data classes may be entered? Are real client records prohibited by default? | Use-case description, data-flow diagram and approved prompt examples. |
| Contract and confidentiality | Does the contract limit processing to the organization’s instructions? Are confidentiality, breach notification and subcontractor terms clear? | Executed agreement and current terms, reviewed by the responsible adviser. |
| Training and product improvement | Are prompts, files or outputs used to train or improve a model? Can that use be disabled contractually and technically? | Written provider commitment and administrator setting, not an informal promise. |
| Storage and processing location | In which countries are content, backups and support data processed? Do cross-border transfers meet the applicable rules? | Provider documentation and the organization’s legal assessment. |
| Retention and deletion | How long are prompts, uploads, outputs, safety logs and backups retained? Can an administrator delete them and verify deletion? | Retention schedule, deletion procedure and audit evidence. |
| Access and identity | Does the service support individual accounts, single sign-on, multifactor authentication and role-based administration? Can staff access be removed promptly? | Configuration record, access review and off-boarding process. |
| Audit and incident response | Are usage logs available without exposing more client data? How are suspected disclosures, prompt injection or account compromise reported? | Tested monitoring and incident playbook with named contacts. |
| Security architecture | Are uploads encrypted in transit and at rest? Are vendor staff or other third parties able to inspect content? What isolation exists between customers? | Security documentation and risk assessment appropriate to sensitivity. |
| Human oversight | Who checks accuracy, fairness and suitability? Is AI barred from making unreviewed decisions about access to services? | Named reviewer, quality checklist and escalation route. |
The SRA’s warning for solicitors makes the same core point in its own regulatory context: “Client information should only be entered into AI systems where appropriate contractual, technical and organisational safeguards are in place to protect confidentiality.” It also notes that both free and paid tools can create risk, depending on their terms, settings and architecture. Newcomer organizations should apply the principle through their own legal and contractual review.
Prompting without exposing a client
Safer drafting pattern
Describe the task, audience, constraints and desired format without case identifiers. For example:
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Rewrite the following fictional paragraph in plain English for an adult learner. Keep the meaning, use short sentences, and flag any term that requires a qualified legal adviser. Fictional text: “The applicant must submit the form within 30 days.”For a real case, first ask whether a generic answer from a public source would solve the problem. If it would, use the public source rather than the case record. If the case-specific facts are essential, use only the organization-approved environment and the minimum necessary facts.
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Details that commonly re-identify someone
- Exact arrival, appointment, detention or hearing dates.
- Small towns, shelters, employers, schools or clinics.
- Rare languages, disabilities, medical diagnoses or religious practices.
- Unusual family relationships, conflicts or incidents.
- Document numbers, file references, photographs, voice recordings and metadata in attachments.
- Long copied case histories that include identifiers outside the paragraph you intended to analyze.
Before sending, inspect the entire prompt, pasted text, attached file name, document properties and conversation history. Do not assume that a redaction tool detected every identifier.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Handling AI-generated summaries, translations and recommendations
Summaries and case notes
Compare every statement with the source record. Mark the result as an AI-assisted draft until a responsible worker approves it. Correct invented facts, merged people, missing qualifiers and overconfident language. Preserve uncertainty when the underlying record is uncertain; do not convert “client reports” into “it happened.”
Translations and plain-language materials
Check names, dates, legal terms, negation, numbers and culturally significant wording with a qualified interpreter or reviewer when the material could affect rights, safety or informed consent. A fluent-sounding translation can still reverse meaning.
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Do not use an AI output as the sole basis for refusing a service, reporting a safeguarding concern, assessing credibility or prioritizing a person. Examine whether the input omitted context or encoded historical bias. Give the client an appropriate human contact and a way to correct inaccurate information when the governing process requires it.
UK Department of Health and Social Care guidance for adult social care recommends that organizations “always include a human review of any AI (artificial intelligence)-generated outputs.” That guidance is specific to its setting, but the review principle is directly relevant to high-impact newcomer casework.
Organizational rules to put in place before adoption
- Approved-tools register: list services, account types, owners, permitted purposes and prohibited data.
- Role definitions: identify the privacy lead, security lead, service owner, reviewers and incident coordinator.
- Training: teach staff minimization, indirect identifiers, secure prompting, output review, phishing and reporting. Refresh training when tools or terms change.
- Client communication: provide a plain-language notice and an accessible route for questions or corrections where required.
- Access control: use individual accounts, least privilege, multifactor authentication and regular access reviews. Never share logins.
- Retention: specify how long prompts, outputs, logs and approvals remain, and how deletion is verified.
- Audit: sample use, review administrator settings and record exceptions. Do not collect more audit content than necessary.
- Impact assessment: consult the privacy official about whether a Privacy Impact Assessment or equivalent review is required for an institutional deployment.
- Change management: reassess when the provider changes a model, location, terms, training policy or subcontractor.
Recognizing and responding to a possible disclosure
- Stop further exposure. End the session, disable the account or integration if necessary, and do not continue testing with real data.
- Preserve evidence safely. Record the service, account, time, data categories and people involved. Avoid copying sensitive content into additional systems.
- Notify the designated privacy and security contacts immediately. Follow the organization’s incident timetable and escalation rules.
- Ask the provider about containment and deletion. Request confirmation of retention, access, downstream sharing and available deletion actions through the approved channel.
- Assess obligations and harm. The privacy lead or qualified adviser should determine notification, contractual, regulatory and client-support requirements under the applicable law.
- Correct the workflow. Revoke access, change settings, retrain staff and document lessons before resuming the use case.
AI-specific threats also deserve monitoring. The Office of the Privacy Commissioner of Canada identifies prompt injection, model inversion and jailbreaking among risks to mitigate. Treat instructions hidden in an uploaded document or retrieved webpage as untrusted content; never let them override access controls or disclosure rules.
Jurisdiction and accountability checklist
There is no single privacy rule for every newcomer-serving organization. A federally employed worker in Canada, a provincial nonprofit, a UK-regulated solicitor and a health or social-care provider may have different duties. Before deployment, confirm:
- Which country, province, territory or state law governs the organization and the client relationship.
- Whether the organization is a public body, charity, contractor, law practice, health provider or another regulated entity.
- What contractual duties funders, referral partners and interpreters impose.
- Whether data leaves the jurisdiction and whether a transfer assessment is required.
- Whether a privacy impact assessment, security review, client notice or consent is mandatory.
- Who can give authoritative advice when the answer is unclear.
Use official regulator guidance as a starting point, then obtain advice from your privacy officer or a qualified local adviser. Do not treat a Canadian federal prohibition, UK GDPR guidance or SRA rule as universal law outside its stated scope.
A quick staff decision test
- Is this task necessary and proportionate?
- Can I complete it with a public document, synthetic example or fully de-identified text?
- Have I removed direct and indirect identifiers, including from attachments and metadata?
- Is this exact service, account and use case approved in writing?
- Do its contract, storage, retention, deletion, access and training terms meet our requirements?
- Have we told the client or obtained permission when the applicable rules require it?
- Who will verify the output, and how will we prevent it becoming an unchecked decision?
- Where will the prompt and output be stored, for how long and who can access them?
If any answer is “no” or “unknown,” do not enter the client information. Pause and consult the organization’s privacy or security lead.
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