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Do not put sensitive personal, financial, health, credential, protected, classified, or confidential business information into a public AI chatbot. A public chatbot is an external service: once you paste text or upload a file, its handling depends on the provider, account type, settings, connected features, terms, and jurisdiction—not just on the chat window you can see.
You can still use these tools safely for many low-sensitivity tasks. Classify the material first, replace real details with synthetic or fictional ones, remove identifying combinations and secrets, and use only an organization-approved service for information that must remain protected.
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Why a public chatbot is not a confidential channel
A public AI chatbot runs outside your immediate control. Your prompt, uploaded document, image, spreadsheet, code sample, or copied conversation can be stored, processed, reviewed, routed to service providers, or handled through connected features under the provider’s rules. The exact result varies by product, account, configuration, and contract.
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The Government of Canada’s workplace guidance states: “Never input protected, classified or personal information into public generative AI tools.” That is the safest default when you cannot verify the service, account, data handling, and approval required for the material.
What should you avoid putting into ChatGPT or another public chatbot?
Unless a specifically approved system and process permits the information, keep the following out of a public chatbot. The examples include information in attachments and screenshots, not only words typed into the prompt.
| Category | Examples to keep out | Safer alternative |
|---|---|---|
| Credentials and security secrets | Passwords, API keys, private keys, recovery codes, access tokens, session cookies, authentication codes, and configuration files containing secrets | Describe the error with the secret removed; use a redacted placeholder such as [API_KEY]. If a secret was exposed, revoke or rotate it through the applicable security process. |
| Government and identity data | Passport or driver’s-license numbers, national identifiers, immigration records, tax identifiers, copies of identity documents, and combinations of details that identify a person | Use a fictional person and a generic region. Keep only the attribute needed for the task. |
| Financial and payment data | Bank-account and card numbers, statements, payment records, loan details, transaction histories, and financial account logins | Use invented figures and a generalized description such as “a recurring payment was charged twice.” |
| Health and care information | Medical records, diagnoses tied to a named person, prescriptions, test results, insurance identifiers, therapy notes, and appointment details that could identify a patient | Ask about a general medical concept without copying the record, or use a synthetic case that does not describe a real patient. |
| Private personal material | Private correspondence, legal papers, employment records, family details, school records, photos of documents, and location or contact information | Summarize the issue in your own words and remove names, addresses, exact dates, and unique circumstances. |
| Customer and client data | Customer emails, support tickets, order numbers, addresses, phone numbers, account histories, contracts, and data exported from a customer system | Describe a fictional customer scenario and retain only the workflow or writing goal. |
| Confidential business information | Non-public financial results, pricing, contracts, personnel matters, incident reports, strategy, acquisition discussions, unreleased products, and supplier information | Use public information or a fabricated example. Confirm that the exact tool and account are approved before using any internal material. |
| Proprietary technical material | Source code, unreleased architecture, security findings, internal logs, database dumps, proprietary algorithms, and credentials embedded in code or logs | Provide a minimal, fabricated reproduction with secrets and identifying infrastructure details removed, or use an approved development service. |
| Protected or classified information | Any material restricted by government classification, regulation, contract, professional duty, or organizational policy | Do not submit it to a public tool. Use the authorized environment and procedure. |
Anthropic’s help guidance specifically calls out financial information, health records, passwords and private login credentials, and confidential business or personal documents as material that requires careful consideration. The categories overlap: a harmless-looking name can become sensitive when combined with an address, date, account number, diagnosis, or unique event.
A pre-send workflow that prevents accidental disclosure
Use this check every time you are about to paste text or attach a file. It is designed to stop a disclosure before it happens rather than relying on deletion afterward.
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- Classify the material. Decide whether it is public, internal, confidential, regulated, classified, personal, or otherwise restricted. Follow the policy and law that apply to the information, not merely the convenience of the tool.
- Separate the task from the record. Ask what the chatbot actually needs to do. A request to draft a response, explain an error, or summarize a process often needs only a general scenario, not the original email, case file, or database row.
- Prefer public, synthetic, or de-identified input. Re-create the situation with fictional values. For example, ask for “a neutral response to a customer reporting a delayed shipment” instead of pasting the customer’s message, name, address, order number, and contact details.
- Remove direct identifiers and revealing combinations. Replace names, account numbers, exact dates, addresses, locations, employee numbers, URLs containing identifiers, and unique descriptions with labels such as
[CUSTOMER],[DATE],[ACCOUNT], or fictional values. Removing a name alone is not guaranteed de-identification if the remaining details still identify someone. - Strip secrets before seeking technical help. Delete passwords, API keys, private keys, recovery codes, access tokens, cookies, and authorization headers. Redact values rather than asking the chatbot to “ignore” them.
- Inspect every attachment. Treat images, PDFs, spreadsheets, code archives, exported chats, and screenshots as data inputs. Check hidden worksheets, document metadata, revision history, comments, headers, footers, filenames, embedded images, and copied identifiers.
- Verify authorization. For work or client information, confirm that the specific service, account, workspace, connected app, and purpose are approved for that information classification. A personal consumer account is not an acceptable substitute for an approved company workflow.
- Check the current provider documentation. Review the exact account’s model-improvement setting, temporary or incognito option, retention and deletion behavior, access rules, contract terms, processing geography, and administrative controls. Product labels and defaults can change.
- Keep the prompt narrow. Submit the minimum context needed for the answer. Do not add a full history, unrelated names, or the entire document when a few abstract facts will do.
- Review feedback actions. A thumbs-up, thumbs-down, rating, support request, or copied transcript can create another data-use path. Read the provider’s explanation of what feedback includes before attaching a conversation.
How to redact without making the task useless
Good redaction preserves the relationships and constraints that matter while removing facts that identify a person, account, organization, or system.
Keep the structure, replace the values
If you need help debugging a calculation, preserve the field types and relationships but substitute values: customer_id=[CUSTOMER_ID], invoice_date=[DATE], and total=[AMOUNT]. Keep the error message if it contains no secret or identifying value; otherwise rewrite it as a generic description.
Generalize dates and locations
Use “last quarter,” “a regional office,” or “within two weeks” instead of an exact date, street address, or small location when precision is not required. Exact combinations can identify a person even when the name has been removed.
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Instead of copying a real complaint, write: “A customer received a shipment three days late and wants a refund. Draft a concise, empathetic response that explains the next step.” This supplies the tone and outcome without exposing the customer’s message or contact details.
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Build a minimal technical reproduction
For code or logs, retain the smallest input that demonstrates the behavior. Replace hostnames, usernames, repository paths, tokens, customer identifiers, internal URLs, and proprietary names. A fabricated five-line example is safer than an entire production log.
Check whether the output could reveal the input
Even a sanitized prompt can produce an answer that contains copied text if the input included distinctive passages. Review generated output before sharing it, and do not treat a chatbot’s promise to forget or not reveal information as a security control.
Privacy settings help, but they do not make sensitive input safe by themselves
Settings affect particular data uses. They do not replace classification, authorization, contractual review, or a decision to avoid submitting restricted information.
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|---|---|---|
| ChatGPT individual Free, Plus, and Pro accounts | OpenAI says users can turn off Improve the model for everyone in Settings > Data controls, or use the Privacy Portal. The setting applies to new conversations. With the setting enabled, eligible content may otherwise be used to improve model performance and safety. | It does not prove that the data is authorized for submission, remove every retention or access question, or govern conversations sent from another account or connected feature. |
| ChatGPT Temporary Chat | OpenAI says temporary chats are not used to improve models while temporary, do not appear in chat history, and do not create or update memories. If a temporary chat is saved, it becomes a regular chat and follows normal account settings. | Do not translate this into “nothing is retained.” The stated scope is narrower than a guarantee that no copy, safety record, support access, or backup exists. |
| ChatGPT Business, Enterprise, Edu, and API products | OpenAI says inputs and outputs are not used to improve models by default and describes encryption and access-management controls for these offerings. | An organization must still assess its service agreement, configuration, user permissions, connected applications, retention, geography, and approval for the particular classification and purpose. |
| Claude incognito chats | Anthropic says incognito chats are not used to improve Claude even when Model Improvement is enabled. | Anthropic’s own guidance still tells users to be mindful of sensitive financial, health, credential, and confidential-document content. Incognito status is not permission to upload it. |
| Other providers and account types | Defaults, retention periods, human-access rules, and opt-outs differ by product and can change. | Do not infer current controls for another provider from a different service, plan, or account. Check its official documentation for the exact product. |
OpenAI also documents an important feedback exception for individual plans: feedback on a response may allow use of the associated conversation for model improvement even after opting out. Treat feedback as a separate submission decision, not as a harmless rating.
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Using AI with workplace or client information
Do not use a personal account for company, government, or client material unless the organization has explicitly approved that tool and use. Approval should cover both the service and the information classification; a general statement that “AI is allowed” is not enough.
Questions an organization should answer
- Which data classifications may be entered, and for which purposes?
- Are prompts and files used for model improvement by default, and can that use be disabled contractually and technically?
- How long are conversations, uploads, logs, backups, and safety records retained?
- Who can access content: administrators, reviewers, support staff, subprocessors, or connected applications?
- What data-processing commitments, confidentiality terms, audit rights, and deletion procedures apply?
- Where is data processed and stored, and do residency or cross-border rules matter?
- Are identity management, least-privilege permissions, audit logs, encryption, and workspace separation configured?
- Can users connect external drives, email, repositories, plugins, or other systems, and are those connections approved?
- What is the incident-reporting path if someone submits restricted information?
A business or enterprise label alone does not prove that a workflow is approved. Verify the actual contract, settings, retention configuration, user permissions, connected apps, geography, and data-handling commitments. Involve privacy, security, procurement, and legal teams when the classification or jurisdiction requires it.
The Office of the Australian Information Commissioner explains that entering personal information into an AI system can constitute a use or disclosure under Australia’s Privacy Act, depending on whether the information remains within the organization’s control. Its advice to define the purpose and minimize personal information is useful operationally, but that legal framework is Australian and should not be treated as universal legal advice.
How to compare a chatbot or account before approval
Do not rank a service as “private” or “safe” because it has one opt-out switch. Evaluate the exact product and account against all of these dimensions:
- Model-improvement use: Is it on by default? Is the opt-out available to this account, and does it cover prompts, files, feedback, and support interactions?
- Retention and deletion: What is retained, for how long, and what does deletion cover? Ask separately about backups, abuse monitoring, legal holds, and exported data.
- Human and supplier access: Which employees, reviewers, subprocessors, or support channels can access content, and under what controls?
- Contractual commitments: Are confidentiality, processing instructions, breach notification, deletion, and audit terms documented for the account?
- Administrative management: Can the organization enforce single sign-on, role-based access, logging, workspace boundaries, and connection restrictions?
- Processing geography: Where are prompts and files processed and stored, and does that satisfy the organization’s residency or transfer requirements?
- Purpose approval: Has the organization approved this particular use, not merely the vendor or product name?
What to do if you already submitted sensitive data
There is no single provider-neutral remedy that applies to every service, account, jurisdiction, and type of data. Act promptly and use the appropriate incident process.
- Stop further disclosure. Do not continue the conversation with more identifying details, and do not copy the transcript into another service.
- Record what happened privately. Identify the account, service, date, conversation or file, data categories, people affected, and whether the material included credentials. Share this only with the responsible privacy or security contacts.
- Report workplace or client exposure. Use your organization’s incident, privacy, or data-breach procedure immediately. That team can determine notification, legal, contractual, and preservation duties.
- Revoke or rotate exposed credentials. Change passwords, invalidate tokens, replace keys, and terminate sessions according to the relevant security procedure. Do not wait for a chat-deletion request to protect an active credential.
- Review the provider’s current controls. Consult its deletion, privacy, support, and account-management documentation. Request assistance through an authorized channel if the organization’s process requires it.
- Do not promise complete erasure. Deleting a visible chat may not remove every copy, backup, safety record, export, or downstream disclosure unless the service documentation confirms that scope.
Threats that redaction and settings do not solve
Privacy exposure is broader than whether a model trains on a prompt. Information may be retained, reviewed for safety or support, made available to a supplier, included in feedback, or passed through a connected feature. Provider terms and account plans differ, and controls change over time.
The Privacy Commissioner of Canada identifies prompt injection, model inversion, and jailbreaking as threats requiring ongoing awareness and mitigation. These are broader system risks: ordinary prompt redaction does not prevent them, and a privacy setting does not replace security architecture, access controls, monitoring, or human review.
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For that reason, the strongest protection is data minimization combined with an approved workflow. Settings are useful defense-in-depth controls, not a reason to place restricted information in an otherwise unapproved public channel.
Quick Recap
A compact decision rule
- If the information would cause harm, violate a duty, or breach policy if copied into an unknown external service, do not enter it.
- If the task can be completed with public, fictional, or de-identified material, use that instead.
- If the task requires protected information, use only a specifically approved service and account after checking contract, retention, access, geography, and administrative controls.
- If you cannot verify those conditions, stop and ask the responsible privacy or security team.
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