Keep sensitive or identifiable information out of public AI chatbot prompts. Before you paste text or upload a file, remove details the task does not need, replace identifying facts with realistic stand-ins, and check the specific service’s privacy terms and controls. If the information belongs to an employer, customer, patient, student or other person, use only a tool your organization has approved for that data classification.
Why a chatbot prompt is not automatically private
A chat window can look like a private conversation, but the provider’s handling of your input depends on its product, settings, contracts and applicable law. Potential handling can include collection and storage, use to improve or train a system, profiling or decisions about a user, uncertain future uses, and disclosure of information learned from prompts to other users. These are possible risks, not claims that every service does all of them. The Office of the Privacy Commissioner of Canada advises consumers not to share sensitive or identifiable personal information.
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The Australian Information Commissioner warns that information can be difficult to track or control after it is entered and that removing it may be difficult or impossible. Even data that has been de-identified can sometimes be linked back to a person through context or other datasets. For public tools, Australian government staff are told to “assume anything you enter into a public generative AI tool could be made public” (Digital Transformation Agency guidance).
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Use the pause-before-pasting test
Stop before entering a prompt, attaching a document or allowing a browser extension to read a page. Ask whether the task can be completed with public information, a made-up example or a summary that contains no person-specific details. The Australian Information Commissioner recommends assessing necessity, access, intended use and compliance duties before an organization uses personal information with a commercial AI product.
- What is the task? Define the output you need, such as a neutral outline, formula or code explanation.
- Which facts are essential? Keep only the minimum facts needed to produce that output.
- Whose information is it? Treat another person’s data as theirs to protect, not yours to disclose. Take extra care with minors’ information and images.
- What is the data classification? Follow labels such as public, internal, confidential, protected or restricted where your organization uses them.
- Which service and account are you using? A public consumer account and an organization-managed system can have different retention, access and training terms.
If you cannot explain why each field is needed, do not include it.
Minimize and alter the information
Remove direct identifiers and unnecessary context before using a chatbot. Delete names, email addresses, phone numbers, postal addresses, account and policy numbers, case identifiers, exact dates of birth, access tokens, passwords, signatures, faces and distinctive quotations. Replace detailed timelines, locations and job titles when they are not required for the answer.
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For a drafting task, replace “Maria Lopez, 47, diagnosed with rheumatoid arthritis on 12 March 2024 at Northside Clinic” with “Patient A, an adult with a chronic condition, recently received a diagnosis.” Use aliases, shifted dates, generalized locations and altered nonessential facts. The Canadian privacy commissioner specifically suggests aliases and changed identifying details.
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Separate the data from the task
Ask for a method or template instead of submitting the underlying record. For example, request “a checklist for reviewing an insurance claim” rather than pasting a claimant’s file. For code, create a small synthetic dataset with the same column types. For a letter, describe the situation in general terms and insert the personal details yourself after the chatbot returns a draft.
Check indirect identifiers
De-identification is not a guarantee. A unique combination of age, occupation, location, incident date, family relationship or medical detail can permit re-identification. Remove combinations that make a person unusual, not just the obvious name. Do not assume that a blurred image, initials or a customer number is anonymous.
Understand what the service may do with a prompt
Before relying on a chatbot, read the current privacy notice, terms and account settings for that exact product and edition. Look for separate explanations of:
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| Question | Why it matters | What to record |
|---|---|---|
| Can prompts or uploaded files be used to train or improve models? | Training use may create additional copies or expose content to review and model-development processes. | Whether training is on by default, how to opt out, and which account types qualify. |
| Who can access the content? | Access may include the provider, contractors, administrators, security personnel or human reviewers. | Provider and administrator access, review purposes and notification practices. |
| How long is it retained? | Deletion from a visible chat list may not remove backups, logs, abuse-monitoring records or derived data. | Retention periods, deletion scope, legal holds and export or backup rules. |
| Can history be deleted? | A deletion control can reduce exposure, but its effect depends on the service’s terms. | Exact deletion steps, waiting periods and exceptions. |
| Where is data processed and stored? | Location can affect contractual, regulatory and data-residency obligations. | Regions, subprocessors and residency commitments. |
| What happens to outputs and feedback? | Ratings, shared links, copied outputs and connected applications can create additional disclosures. | Sharing defaults, integrations, public links and feedback handling. |
Turning off model training, when that option exists, addresses only that one use. It does not by itself resolve retention, provider or administrator access, security incidents, legal process or accidental disclosure. Verify each control instead of treating an opt-out as a confidentiality guarantee. Settings and policies can change, so recheck them before a new or high-risk use.
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Public chatbots versus approved workplace systems
Do not infer that a workplace subscription is safe for every type of data. Authorization must come from the organization’s policy, contract and security review. Canada’s federal Guide on the use of generative artificial intelligence tells staff not to enter sensitive or personal information into tools not managed by the Government of Canada, to review supplier terms, match use to security classification and obtain approval for protected or sensitive uses.
Australian public-sector rules illustrate the same principle in a different jurisdiction. The Digital Transformation Agency prohibits personal or OFFICIAL: Sensitive-and-higher information in public generative AI tools and directs staff to their agency policy. Victoria’s guidance says public tools should receive only publicly available information and that agency-approved tools must be used for their permitted purpose and protective marking. These government rules are examples, not universal law for every private employer.
Employee decision path
- Identify the owner of the information and its classification.
- Read your acceptable-use, privacy, records-management and AI policies.
- Confirm that the exact tool, account and workspace are approved for that classification and task.
- Check whether prompts, files and outputs are retained, used for training, reviewed by people or accessible to administrators.
- Obtain the required privacy, security, legal or procurement approval before entering protected information.
- Use the minimum necessary data, keep an audit record where policy requires it, and share the output only with authorized recipients.
If no approved path exists, ask your privacy or security team for a sanctioned alternative rather than moving the work to a personal account.
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How organizations should assess an AI tool
For an organizational decision, compare tools against the actual use case and data classification, not marketing labels. The Office of the Australian Information Commissioner recommends due diligence on suitability, testing, human oversight, security and privacy risks, and access to input and generated personal information. NSW guidance also points to approved tools, an acceptable-use policy, a privacy impact assessment and ongoing risk management.
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| Assessment area | Questions for procurement and security teams |
|---|---|
| Permitted use and classification | Which data classes and business processes are allowed? Are regulated, confidential or children’s records excluded? |
| Training and secondary use | Are prompts and files excluded from training by contract and technical configuration, or merely covered by a user setting? |
| Access controls | Can provider staff, workspace administrators or support personnel view content? Are roles, least privilege and audit logs available? |
| Retention and deletion | What are the default and maximum retention periods? Can the organization delete chats, files, logs and backups, and verify deletion? |
| Security and residency | Are encryption, incident notification, subprocessors, regional processing and identity controls suitable for the information? |
| Human safeguards | Who reviews outputs, handles errors, responds to rights requests and prevents automated decisions from harming people? |
| Contract and compliance | Do terms, data-processing agreements and records support applicable privacy, confidentiality and sector obligations? |
Document the decision, test with synthetic data first and revisit it when the provider changes a model, feature, location, terms or default setting. A tool approved for public material is not automatically approved for customer records.
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For writing and editing
Provide the audience, tone, length and purpose, but replace names, contact details and case histories with placeholders. Generate the structure in the chatbot, then add the real details in an authorized editor or document system.
For analysis
Use aggregated counts, ranges or synthetic rows rather than raw records. Remove free-text notes, because a short narrative often contains more identifying context than a structured field. If exact values are essential, ask whether the approved system has access controls and contractual protections that a public service lacks.
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For technical troubleshooting
Strip API keys, session cookies, internal hostnames, customer identifiers and proprietary source code. Reproduce the error with a minimal example and replace domains, paths and data values. Never paste a secret merely because a tool requests the full log.
For images and audio
Do not upload faces, identity documents, medical images, voice recordings or screenshots containing notifications and account details unless the service and your policy expressly permit it. Crop or redact irrelevant regions before upload; remember that visual context can identify a person even when text is covered.
If you already submitted sensitive information
- Stop further disclosure. Do not continue the conversation or upload related files.
- Use the service’s current controls. Delete the conversation, uploaded files, shared links and connected integrations where available. Read what deletion does and does not cover.
- Revoke exposed secrets. Rotate passwords, API keys, access tokens and recovery codes that appeared in the prompt or attachment.
- Notify the right owner. For workplace, customer, patient, student or regulated information, contact your privacy, security or incident-response team immediately and follow its reporting deadline.
- Preserve necessary facts safely. Record the service, account, time, type of information and actions taken without copying the sensitive content into another unapproved system.
- Watch for follow-on harm. Monitor accounts, access logs and affected people according to your organization’s incident plan.
Deleting chat history may reduce availability in the interface, but the cited consumer guidance does not establish that deletion removes every copy or downstream use. Ask the provider or your organization what retention, backup and legal exceptions apply. If another person’s information was involved, include that person in the organization’s privacy assessment where required.
Common assumptions that fail
- “It is only a draft.” A draft can contain the same identifiers and confidentiality obligations as a final document.
- “I removed the name.” Context, dates, locations and rare characteristics may still identify someone.
- “Training is disabled.” Retention, access, security and disclosure risks remain separate questions.
- “The tool is paid for.” Payment does not prove the plan meets your classification, residency or contractual requirements.
- “The provider promises privacy.” Read the exact terms for your account and feature; connected services and administrators may have different access.
- “The output is safe because the input was safe.” Outputs can reproduce confidential details, infer sensitive traits or be shared onward. Review before distributing.
A compact checklist for every prompt
- Can I complete this with public or synthetic information?
- Have I removed names, contact details, numbers, secrets, images and unnecessary context?
- Could the remaining combination identify a person?
- Is the service approved for this data classification and use case?
- Have I checked training, access, retention, deletion, residency and sharing settings?
- Do policy, contract or law require a privacy or security review?
- Have I planned who will verify the output and where it may be stored?
If any answer is no or unknown, do not submit the sensitive material. Ask for an approved workflow or rewrite the task using a generic example.
What this guidance can—and cannot—promise
These practices reduce unnecessary exposure; they cannot make a public chatbot confidential or guarantee that a de-identified person cannot be recognized. Privacy duties differ by country, sector, employer and data type. For example, the Australian Information Commissioner explains that entering personal information may count as a use or disclosure under Australia’s Privacy Act when the organization no longer retains effective control. That legal analysis is jurisdiction-specific, so obtain professional advice for a regulated use.
The safest default is simple: public tools receive public information; sensitive work stays in an approved system with documented controls, human oversight and the minimum data needed for the task.
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