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The safest approach is data minimization: do not put passwords, authentication codes, government identifiers, financial-account details, medical records, confidential work material, trade secrets, client data, children’s information, or identifiable information about other people into a public AI chatbot. If an AI system is genuinely needed, remove direct identifiers, generalize dates and locations, use a synthetic example, send only the smallest necessary excerpt, and confirm that the service is approved and its current privacy settings match your risk. Then verify every response independently and delete the conversation when the service permits it.
Public chatbots can collect and retain prompts, use them for model improvement or other purposes, expose them to reviewers or service providers, and disclose them under some circumstances. Australian, Canadian and United States regulators therefore emphasize authorization, purpose limitation, retention limits, strong account security and clear provider commitments.
Is it safe to paste personal information into an AI chatbot?
It is not safe to assume that a public chatbot is a private notebook. The provider may log prompts and uploads, retain them for a period that changes over time, use them to improve services, make them available to authorized personnel or contractors, or disclose them when legally required. The Office of the Privacy Commissioner of Canada advises limiting what you share and not sharing sensitive or identifiable personal information. Australia’s Office of the Australian Information Commissioner (OAIC), updated in 2025, says publicly available generative-AI tools present significant and complex privacy risks.
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Use a public chatbot for public facts, non-sensitive brainstorming and synthetic examples. Use an approved, contractually controlled system only when a legitimate task requires restricted data and your organization has authorized that use.
What information should I never share with an AI chatbot?
Unless an approved workflow explicitly requires it and provides appropriate controls, keep the following out of public chatbots:
- Passwords, password-reset answers, one-time authentication codes, API keys, session cookies and private encryption keys.
- Full payment-card numbers, bank-account credentials, tax records and other financial-account details.
- Government identifiers such as passport, driver’s-license, national-insurance or social-security numbers.
- Medical records, diagnoses, prescriptions, insurance information and other health data.
- Confidential contracts, unreleased financial results, trade secrets, source code, security architecture and proprietary formulas.
- Client, customer, employee or patient information that can identify a person, especially where a law, contract or professional duty applies.
- Children’s names, photos, school details, location data or other personal information. Canadian privacy guidance specifically says never share pictures or personal information of minors.
- Another person’s identifiable information without a lawful purpose, authorization and a need to use it.
Do not assume that removing a name makes a record anonymous. A rare job title, exact date, small-town location, unusual diagnosis and distinctive event can identify someone when combined. Remove or generalize those clues too.
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How can I remove identifying details before I prompt?
Redaction works best when you change the data before it leaves your controlled environment and preserve only what the task needs.
1. Classify the material
Label the content as public, internal, confidential, personal, sensitive, regulated or proprietary. If you cannot classify it, treat it as confidential and ask the data owner or your security team before using an external service.
2. Strip direct identifiers
Replace names with roles such as customer_A or project_lead. Remove email addresses, phone numbers, account numbers, URLs containing identifiers, exact addresses, photographs and document metadata. Use consistent aliases only when the model needs to distinguish people or records.
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3. Generalize indirect identifiers
Change an exact birth date to an age range, a precise timestamp to a month, and a street address to a region. Broaden rare occupations, small locations and unusual events. Keep the level of detail that affects the answer, but discard context that merely makes a person easier to recognize.
4. Substitute synthetic examples
For wording, coding, formatting or analysis-method questions, create fictional names, values and records. A synthetic incident report can demonstrate a classification method without exposing the real incident. Check that copied examples do not retain hidden identifiers in comments, tracked changes or file properties.
5. Minimize the excerpt
Send one paragraph, field or error message rather than a whole file. Ask the model to explain a technique using a short, sanitized sample. More context is not automatically a better prompt; it is more data at risk.
De-identification reduces exposure but is not a guarantee of anonymity. If re-identification would cause harm, use a system and process specifically approved for that risk instead of relying on redaction alone.
How do public, enterprise, private and local AI options differ?
Compare the actual controls, not the marketing label. The same category can have very different retention, review and deletion terms, so confirm each item in current documentation and your contract.
| Option | Typical exposure question | Controls to verify | Trade-off |
|---|---|---|---|
| Public chatbot | Are prompts retained, reviewed or used to improve models? | Prompt-retention period, training-use setting, human review, deletion process, account security and regional processing | Fast and convenient, but the user has the least control and may have no contractual assurance. |
| Enterprise-managed service | Does the organization control identity, users and data handling? | Written no-training commitment where required, retention and deletion terms, encryption, single sign-on, role-based access, audit logs, administrator controls, data residency and incident notification | More governance and cost; configuration errors can still expose data. |
| Private deployment | Who operates the infrastructure and support path? | Network isolation, administrator and vendor access, patching, backups, key management, logging, deletion and contractual responsibilities | Greater control but substantial operational and security responsibility. |
| Local model | Does information leave the device or local network? | Telemetry, update channels, local logs, model and dependency provenance, endpoint encryption and access controls | Can limit transmission, but requires capable hardware, maintenance and careful endpoint security. |
No option is automatically private. Ask who can access prompts, how long copies remain in backups, whether support personnel can view content, where processing occurs, what happens after account closure and how a deletion request is verified.
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What privacy settings should I check before using a chatbot?
Open the service’s privacy, data-controls and security pages while signed in, because settings can differ by account, region and plan. Record the choices that matter to your use case.
- Prompt retention: how long chats, uploads, feedback and diagnostic logs are kept.
- Model training or improvement: whether your content is used for those purposes by default, and whether an opt-out applies to future prompts only or also existing data.
- Human review and support access: who may inspect content, for what reasons and under what confidentiality controls.
- Sharing: whether data goes to affiliates, subprocessors, plug-ins or connected applications.
- Deletion: how to delete individual chats, an account and associated files, and whether backups or legal holds have separate schedules.
- Regional processing: the countries where prompts are stored, processed or supported, and whether your legal or contractual requirements permit that transfer.
- Security controls: phishing-resistant multifactor authentication, session management, device controls, access logs and administrator policies.
Recheck these settings after a material product or policy change. A previous choice is not proof that a new workspace, model, plug-in or mobile app has the same behavior.
How do I protect the account that contains my chats?
Privacy controls cannot help if someone else takes over the account. Use a long, unique password stored in a password manager and enable multifactor authentication. Phishing-resistant methods, especially FIDO2 security keys, provide stronger protection than codes that can be intercepted or socially engineered. Register a backup key and store it securely so a lost primary key does not force an unsafe recovery process.
- Turn on multifactor authentication in the account’s security settings.
- Prefer a FIDO2 security key or another phishing-resistant method when the service supports it.
- Review active sessions and revoke devices you no longer recognize.
- Remove unused browser extensions, integrations and shared links that can read or send chat content.
- Use separate work and personal accounts, and do not save confidential prompts in a shared browser profile.
A security key protects access to the chatbot account; it does not control what the provider does with prompts after you submit them.
What is the safest workflow before, during and after a prompt?
Before typing
- Define the task and the minimum information needed to complete it.
- Classify every input and identify legal, contractual or workplace restrictions.
- Confirm that the chatbot is public, enterprise-managed, privately deployed or local, then check the applicable terms and settings.
- Obtain organizational approval when the content is internal, confidential, regulated or proprietary.
- Prepare a redacted or synthetic example and inspect it for names, numbers, metadata and rare clues.
While prompting
- Paste the smallest sanitized excerpt that can answer the question.
- Keep secrets in your approved password, key-management or ticketing system rather than in the chat.
- Do not upload full spreadsheets, document folders, photographs or recordings when a few fields will do.
- State the desired format and constraints without adding personal history that does not affect the result.
- Do not connect plug-ins or external actions unless their permissions and data flows are approved.
After receiving the response
- Check facts, citations, calculations, code and recommendations against authoritative sources and your own records.
- Inspect the output for invented details, confidential text, personal information or content copied from an unexpected source.
- Remove sensitive text from exports, screenshots, tickets and shared documents.
- Delete the chat when appropriate and available, then follow your organization’s retention schedule.
- Report suspected disclosure through the provider’s reporting channel and your organizational incident process.
The Australian Signals Directorate and Australian Cyber Security Centre state: “Do not enter sensitive or classified information into AI tools unless that has been approved.” Treat that as a practical default for workplace use.
How should an organization approve AI chatbot use?
An organization needs a repeatable decision process rather than a blanket promise that a tool is safe. Assign an owner for each use case and document what information classes are allowed.
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Set purpose and authorization
Define the business purpose, permitted users, approved models and prohibited data. Require the data owner, privacy lead or security team to approve uses involving personal, regulated, client or proprietary information. Limit collection to that purpose and prohibit reuse for unrelated experimentation.
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Obtain written answers about retention, deletion, training use, human review, subprocessors, encryption, identity integration, data residency, breach notification and audit rights. Contractual promises must be specific, technically achievable and consistent with the product configuration. The US Federal Trade Commission emphasized in 2024 that there is no AI exemption from existing laws and that model-as-a-service companies must honor commitments made to customers.
Control access and monitor use
Use single sign-on, least-privilege roles, phishing-resistant MFA, approved devices and audit logs. Block unsanctioned uploads where feasible, train staff with realistic redaction exercises, and review logs for unusual exports or public sharing. Establish a route for reporting accidental disclosure and a timetable for deleting retained data.
Manage outputs as untrusted
Require human review before an output affects a person, a security decision, a legal filing, a financial report, medical advice, code deployment or public communication. Keep a record of the source data, reviewer and verification performed when the decision is consequential.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What should I do if I accidentally share private information?
Act quickly, but do not paste more sensitive material while trying to explain the mistake.
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- Stop the conversation and disconnect any automated action or plug-in that could propagate the data.
- Use the service’s deletion controls for the chat, files and shared links, and note the time and account involved.
- Change exposed passwords and revoke leaked tokens or sessions from a trusted device. Treat authentication codes as compromised even if they have expired.
- Notify your organization’s security, privacy or legal contact when the data belongs to work, a customer or another person.
- Preserve the minimum evidence needed for investigation without redistributing the sensitive content.
- Ask the provider what retention, deletion and incident procedures apply, and follow any required notification rules.
Deletion may not mean immediate removal from every backup or legal record, so obtain the provider’s documented scope and timeline rather than assuming the prompt has vanished.
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How do I judge whether an AI answer is safe to reuse?
Fluent text is not evidence. Models can hallucinate facts, generate unsafe instructions or reproduce sensitive information that appeared in their context or training data. Before publication, a decision or onward sharing, verify each material claim with an authoritative source, recalculate important numbers, test code in a controlled environment and remove personal or confidential content.
Use extra caution when the answer contains a person’s allegation, health or financial guidance, legal interpretation, security procedure or citation you cannot independently locate. If the model refuses to explain its source, treat the statement as unverified rather than filling the gap with a guess.
Frequently Asked Questions
Does browser incognito mode stop an AI provider from saving my prompts?
No. Private-browsing mode mainly limits local history, cookies and cached files on that device. It does not override the chatbot provider’s retention, training, review or deletion policies.
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Can I safely paste an anonymized customer record into an approved workplace chatbot?
Only when your organization has authorized that data class and the service’s contract and configuration cover the intended purpose. Check whether combinations of supposedly harmless details could re-identify the customer, and keep a record of the approval.
Does deleting a chat remove it from backups immediately?
Not necessarily. Providers may maintain separate backup, security or legal-retention schedules, so check the service’s deletion documentation and request confirmation when the distinction matters.
What if a chatbot reveals someone else’s private information in its answer?
Do not copy, publish or forward the information. Stop the task, record only the minimum evidence needed, report the disclosure to the provider and notify your organization’s privacy or security contact if the incident affects your work.
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