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The safest approach is to treat every chatbot as a separate data processor. Keep regulated, secret and identifiable information out of consumer chatbots; redact the rest; disable model-improvement, memory and personalisation where possible; use Temporary Chat, Incognito or an equivalent one-off mode; and delete chats and uploads when the task is done. Before using ChatGPT, Claude, Gemini, Copilot or another service, check that provider’s current training, retention, deletion, review and account controls. A work account or API can add contractual and administrative safeguards, but it does not make careless prompts safe.
Why does using several chatbots increase privacy risk?
Each service can store, review, personalise or otherwise process what you send. Pasting the same customer record, medical note or source document into three tools creates three independent retention and access surfaces, each governed by different defaults and exceptions. Turning off training in one account does nothing to the copies already sent to another.
The Office of the Australian Information Commissioner (OAIC) advises organisations, as a best practice, not to enter personal information—particularly sensitive information—into publicly available generative-AI tools. That is a useful baseline even when you are an individual: if a task can be completed with a fictional example or a redacted excerpt, do that instead.
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What information should never go into a consumer chatbot?
Keep data whose disclosure could harm a person, breach a duty or provide access to an account out of ordinary consumer chatbots. Use an approved enterprise workspace or API only after your organisation has checked its contract, settings and jurisdictional requirements.
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Classify the material before you paste it
- Public: already published material that carries no personal or confidential details.
- Internal: routine business information that is not public but is not regulated or highly sensitive.
- Confidential: customer information, unpublished financials, contracts, source code, negotiations or non-public strategy.
- Personal or regulated: health, biometric, financial, identity, employment, education or legally protected records.
- Secret: passwords, API keys, private encryption keys, recovery codes, security findings before disclosure and information subject to a strict confidentiality obligation.
Do not put regulated, secret or directly identifiable material into a consumer account. If an approved business environment exists, confirm that it covers the particular data, model and country involved; “business” in the product name is not by itself a legal or technical guarantee.
How should I redact a prompt or uploaded file?
Remove direct identifiers and unnecessary context while preserving the relationships the model needs to answer. Use stable placeholders so a long conversation remains understandable without exposing the original identity.
- Replace names, email addresses and phone numbers with tokens such as
[CLIENT_A]and[PHONE_1]. - Remove account numbers, authentication codes, passwords, API keys and private URLs. Never ask a model to “remember” a credential.
- Generalise exact addresses and locations to a city, region or distance band when precision is not essential.
- Summarise health, financial or employment details instead of uploading a complete record; remove dates or amounts that do not affect the answer.
- Replace client, patient, student and case identifiers, including identifiers hidden in filenames, document metadata, screenshots and tracked changes.
- Paraphrase confidential source text. Quote only the minimum lines needed to analyse a clause or error.
Keep a private mapping between placeholders and real identities only in an approved system. Before uploading, inspect the entire file—not just the visible page—for comments, revision history, embedded images, spreadsheet tabs and metadata. A short excerpt is preferable to a full document when it can answer the question.
What is the safest repeatable workflow for multiple AI chatbots?
Use the same gate before every provider and repeat it after a material policy or product change. The sequence below separates data minimisation from account controls, so one mistaken setting cannot undo all of your precautions.
- Classify the material. Mark it public, internal, confidential, personal, regulated or secret. Stop if it is regulated, secret or identifiable and you have no approved environment.
- Choose the least exposed service. Ask whether your employer, school or client has an approved enterprise workspace or API. Otherwise use a synthetic example or a redacted excerpt.
- Redact and minimise. Remove identifiers, secrets, unnecessary pages and hidden metadata. Replace recurring identities with stable placeholders.
- Inspect controls before the first prompt. Find the provider’s current settings for model improvement or training, memory, personalisation, history, retention, deletion and human or automated review.
- Use a one-off privacy mode. Select Temporary Chat, Incognito or the provider’s equivalent for a sensitive, non-recurring question. Confirm what that mode does not cover, such as safety logs or legal holds.
- Limit duplication. Do not send identical sensitive text to several providers merely to compare answers. Each additional copy creates another retention and review surface.
- Clean up. Delete the conversation and uploaded files when the task is complete, subject to your organisation’s retention or legal-hold rules. Deleting a view does not necessarily erase provider backups or mandatory safety records.
- Recheck after change. Product names, defaults and account eligibility change. Revisit settings after a major update, a change of account type, a new model or a policy revision.
How private is ChatGPT for personal accounts?
OpenAI says content from individual services may be used to train its models and that users can opt out. The opt-out changes future model-improvement use; it is not a promise that the provider never processes the conversation for security, abuse prevention or other operational purposes.
What does Temporary Chat do?
OpenAI states that Temporary Chat conversations do not appear in history, do not use or create memories and are not used to train its models. Treat that as a scoped mode, not as permission to submit secrets: safety, legal and abuse-monitoring processes can still apply, and the exact retention period depends on the current policy and account context.
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Is an OpenAI API different?
OpenAI states that, as of March 1, 2023, data sent to its API is not used to train or improve OpenAI models unless the customer explicitly opts in. Its documentation also describes abuse-monitoring logs retained for up to 30 days by default; eligible organisations can configure Zero Data Retention controls. Confirm eligibility, endpoint coverage and contractual terms before treating an API deployment as suitable for regulated data.
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Anthropic says consumer chats and coding sessions can be used to improve models when the user allows it, when a conversation is flagged for safety review or when the user otherwise opts in. Its Incognito mode is designed for conversations that are not used to improve Claude, but that does not remove the need to redact sensitive content or consider safety and legal exceptions.
What retention periods does Anthropic describe?
Anthropic’s consumer privacy documentation describes a maximum retention of five years for conversations associated with user feedback. Separate documentation for designated covered models used in safety work describes a 30-day retention rule for prompts and outputs, with automatic deletion after 30 days except for flagged or legally required cases. Those figures apply to the situations described by Anthropic, not automatically to every account, model or region.
What privacy protections does Microsoft Copilot provide?
For consumer Copilot accounts, Microsoft says users can opt out of using conversation activity for model training. Conversation history is retained by default for 18 months, and users can delete individual items or the entire history.
Does opting out stop every other use?
No. Microsoft cautions that a training opt-out does not exclude conversations from other product-improvement, advertising, digital-safety, security or compliance uses. Some conversations may also receive automated or human safety review, so do not treat the toggle as a confidentiality setting.
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Is a work or school account safer?
Microsoft’s work and school Copilot Chat documentation says enterprise data protection applies when you are signed in with an organisational account. It says prompts and responses are not used to train foundation models, while chat data is logged for administrative audit. Administrators may therefore be able to access or retain records that a consumer user would delete; use the account only under your organisation’s approved policy.
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What about Gemini and other chatbot providers?
Do not infer a provider’s practices from another company’s settings. For Gemini or any service not covered by the controls above, open the current privacy and account pages for the exact edition (consumer, work, school or API), country and model, then record the answers to the same questions: Is training on by default? Can I opt out? What does a temporary mode exclude? Is memory enabled? How long are history, uploads and safety logs retained? Who can review them?
Feature names and defaults can differ by geography, age, subscription and administrator policy. If the provider does not clearly state the answer, treat the behaviour as unknown and keep sensitive material out.
How do the major chatbot privacy controls compare?
The table distinguishes documented behaviour from items that vary by account or are not established in the available provider material. “Consumer” means a personal account; organisational controls can change the result.
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|---|---|---|---|---|---|---|
| ChatGPT, individual service | OpenAI says content may be used to train models; users can opt out. | Temporary Chat does not appear in history, use or create memories, or train models. | Memory and history are controlled separately; exact deletion and retention depend on current settings and policy. | Operational, abuse, safety or legal processing may still apply. | API data is not used for training by default; abuse-monitoring logs may be retained up to 30 days; eligible organisations can configure Zero Data Retention. | Not applicable to a personal account; organisational administration depends on the deployment. |
| Claude, consumer | Chats may improve models when allowed, after a safety flag or when otherwise opted in. | Incognito chats are not used to improve Claude. | Anthropic describes up to five years for conversations associated with user feedback; designated covered-model safety prompts and outputs have a 30-day rule, with stated exceptions. | Flagged or legally required cases can be retained beyond the 30-day safety period. | Specific enterprise or API contractual protections are not stated in the available material; verify the current terms. | Not stated for consumer accounts. |
| Copilot, consumer | Users can opt out of conversation activity being used for model training. | Use the current account’s available one-off or history controls; a training opt-out is not a universal privacy mode. | Conversation history is retained by default for 18 months; individual items or all history can be deleted. | Other product-improvement, advertising, digital-safety, security, compliance and safety-review uses may remain. | Work or school Copilot Chat applies enterprise data protection; prompts and responses are not used to train foundation models. | Organisational chat data is logged for administrative audit. |
| Gemini or another provider | Not stated here; inspect the current policy for the specific account and region. | Not stated here; verify what the named mode excludes. | Not stated here; check memory, history, upload and deletion controls separately. | Assume safety and legal exceptions may exist until the provider says otherwise. | Not stated here; obtain the enterprise or API agreement and retention configuration. | Not stated here; ask whether administrators can audit prompts, responses and files. |
The comparison is deliberately conservative: a missing statement is not evidence of privacy. Save a copy of the provider’s current policy or an internal approval record when your compliance process requires proof of the setting in force.
Should I use a work account instead of a personal account?
Use a work or school account when your organisation has approved it, because it can provide enterprise data-protection commitments, central controls and auditability. It is not automatically more private for the individual: administrators may log prompts and responses, and the organisation may have its own retention, discovery and monitoring duties.
Before sending confidential material, ask your administrator or privacy lead:
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- Which models, regions and features are covered by the agreement?
- Are prompts and outputs excluded from foundation-model training, and are there separate product-improvement or safety uses?
- How long are chats, files, backups and abuse logs retained?
- Can administrators, support staff or a legal-discovery process read the content?
- Are memory, connectors, plugins and external actions disabled or governed?
- What deletion, export, incident-notification and data-location commitments apply?
If the answers are unclear, submit a redacted or synthetic example instead of the real record.
How can I experiment without exposing real people or secrets?
Build a synthetic test case
Create fictional names, addresses, account numbers and dates that preserve the shape of the problem. For a support workflow, use [CUSTOMER_01], a made-up order total and a fabricated error message. Synthetic data lets you compare prompts and model behaviour without creating a real-person record in several systems.
Minimise the context window
Ask what the model actually needs. To check a contract clause, provide the clause and a one-sentence objective rather than the whole agreement. To debug code, remove credentials, proprietary comments and unrelated modules; reproduce the error with a minimal snippet.
Separate analysis from identification
Have the chatbot classify or transform placeholder data, then perform the identity lookup inside an approved system. Do not ask a consumer model to join a redacted answer back to a customer database.
What should I do if I accidentally upload sensitive information?
- Stop sending follow-up prompts that repeat or expand the material.
- Use the provider’s controls to delete the chat and every uploaded file, and record the time and account used.
- Check whether the conversation was in a temporary/incognito mode, whether memory or personalisation was enabled and whether model-improvement sharing was turned on.
- Notify your organisation’s security, privacy or legal contact according to its incident procedure. A deletion click does not replace required breach assessment.
- Rotate exposed passwords, API keys, recovery codes and tokens immediately; revoke them rather than merely editing the text.
- Ask the provider what deletion, safety retention, support access and legal-hold exceptions apply if the exposure could cause harm.
Keep a factual record of what was sent, to which account and when. Avoid copying the same sensitive material into another chatbot while trying to investigate it.
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How often should I review chatbot privacy settings?
Review them when a provider changes its privacy notice, launches a model, adds memory or connectors, changes your account type or moves you to a new country or workspace. A quarterly check is a practical minimum for a team that uses several services; high-risk workflows should check before each deployment.
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Record the account edition, model, region, training choice, memory choice, history-retention setting, deletion method and administrator access. This small inventory prevents a team from assuming that a setting selected in one product applies everywhere else.
What is the practical privacy standard for everyday chatbot use?
Use public or synthetic text by default, redact anything identifiable, and send the minimum necessary excerpt to one approved provider. Disable training, memory and personalisation where available; choose a one-off mode for a sensitive question; delete the result and uploads when finished; and escalate regulated or secret material to an approved enterprise or API workflow. If you cannot explain who can retain, review or reuse a prompt, do not send it.
Frequently Asked Questions
Can deleting a chatbot conversation guarantee that it is gone everywhere?
No. Deletion may remove the user-visible history while backups, abuse-monitoring records, safety investigations or legal holds follow separate schedules. Ask the provider or your administrator which copies and exceptions apply.
Is a VPN enough to keep chatbot prompts private?
A VPN can conceal traffic from some local network observers, but the chatbot still receives the prompt and may retain or review it under its policy. Network privacy and provider-side data governance solve different problems.
Should I use browser private mode when chatting with an AI service?
Private browsing mainly limits local history and some cookies after the window closes; it does not prevent the service from storing your account activity. Use it only as a local-device measure, alongside redaction and provider privacy controls.
What should a team policy require before employees use an AI chatbot?
Require data classification, approved providers and accounts, redaction examples, a ban on secrets and regulated records in consumer tools, documented settings, deletion procedures and an incident contact. Reapprove the workflow when the model, region or provider terms change.
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