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Test an AI companion with fictional information before you disclose anything real. First read its current privacy policy and in-product settings, then identify what it collects, whether chats create persistent memories or inferences, whether content is used to train models, how long records remain, what deletion removes, and who can access or receive the data. Use a made-up scenario to exercise memory and deletion controls. If the service cannot give a specific answer about training, retention, deletion scope, or third-party access, treat that point as unknown and do not share sensitive information.
What should you establish before chatting with an AI companion?
An AI companion can handle more than the text you intentionally type. Account details, device permissions, usage patterns, conversation content, generated summaries, saved memories and inferred preferences may all become separate records. A privacy test therefore examines the complete data lifecycle rather than relying on a single “private” label.
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- Collection: What arrives from your messages, account registration, connected devices, permissions and activity?
- Use: Are the records needed to provide the service, moderate abuse, personalize replies, improve products or train models?
- Persistence: Are chats, memories, logs, summaries or inferences retained, and for how long?
- Access and disclosure: Can employees, contractors, service providers, affiliates, law-enforcement recipients or other third parties see the information?
- Control: Can you turn off memory, history or model-improvement uses, and can you delete each type of record?
The Federal Trade Commission’s September 11, 2025 inquiry into generative-AI companion services uses these categories in its information requests. The inquiry asks companies about data they collect, analyze, store, transfer, infer and retain, but it is not a finding that every companion uses any particular practice.
How do I read the privacy policy and settings efficiently?
Open the service’s current privacy policy, terms, help pages and account settings before starting a personal conversation. Record the policy’s effective date and compare its promises with the controls you can actually see.
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Search for the terms that reveal data handling
Use the page’s find function for conversation, input, output, memory, training, improve, retention, delete, service providers, sharing, human review and sensitive information. Read the surrounding paragraphs; a definition or exception several lines away can change the meaning of a setting.
Write down answers instead of relying on impressions
- List every data source: chat text, uploaded files, voice, images, account profile, contacts, location, device identifiers and usage telemetry.
- Note whether the service creates summaries, personality profiles, preferences, safety labels or other inferences from your interactions.
- Record whether chats or memories are used to train or improve models, and whether the answer changes for paid accounts, temporary modes or an opt-out switch.
- Find stated retention periods for conversations, memories, logs, backups and deletion requests.
- Copy the explanation of what deleting a message, conversation or account removes, including exceptions for safety, fraud prevention, legal duties and backups.
- Identify service providers, reviewers, affiliates and other recipients, their stated purposes and any international transfer language.
A statement such as “we value your privacy” does not answer these questions. Prefer a policy that names data categories, purposes, time limits and controls in plain language.
How can I tell whether my conversations train or improve the AI?
Look for an explicit statement about using customer content to train, fine-tune, evaluate or improve models. “The service may use data to improve our products” is broader than a promise that chats are excluded from model training, so determine which activities the wording covers.
Check whether the policy distinguishes between account types, regions, age groups, human-review programs and settings that disable model improvement. Confirm the setting’s default state and whether it applies to new chats only or also to previously stored content. Save a copy or note of the policy version and the date you checked it.
The FTC’s January 2024 guidance, “AI Companies: Uphold Your Privacy and Confidentiality Commitments,” says providers must honor privacy promises, including commitments about not using customer data to train or update models. Its plain warning is: “There is no AI exemption from the laws on the books.” A provider’s later, undisclosed or retroactive expansion of data use can create a separate concern; the FTC discussed that risk in February 2024 guidance on quietly changing terms of service.
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If training use is not addressed, do not infer that an opt-out exists. Treat the practice as unknown until the provider’s current policy or support documentation gives a specific answer.
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These labels can describe different stores of data. A visible conversation may be only one copy; the service may also keep a persistent memory, a summary, an account attribute or an inference generated from your behavior.
| Data type | What it may contain | Question to ask |
|---|---|---|
| Chat history | Your prompts, uploads, replies and timestamps | Is it stored, and for how long? |
| Saved memory | Facts or preferences the companion reuses in later sessions | Can each item be viewed, edited and removed? |
| Profile details | Name, age, account attributes or connected-account information | Which fields are required, optional or shared? |
| Summaries and inferences | Personality traits, interests, risk scores or conversation summaries | Are they retained separately and covered by deletion? |
| Operational logs | Security, diagnostic, moderation and usage records | What retention period and access rules apply? |
The FTC’s companion inquiry specifically asks about summaries and inferences, not only the original text. Therefore, deleting a visible thread does not by itself prove that every derived record disappears.
How do I test memory without exposing a real secret?
Use a wholly invented identity and preference. Never use a real name, address, account number, medical detail, workplace secret, travel plan or relationship disclosure as a test case.
- Create a fictional statement, such as “My imaginary character prefers blue tea and lives on a made-up island.” Ensure none of the details identify a real person.
- Ask the companion to remember one specific preference. Do not add any genuine personal context.
- Open the account’s memory or personalization page and check whether the item appears, how it is described and whether an edit or delete control exists.
- Start a new conversation and ask what it remembers about the fictional character. This tests whether the service carries information across chats, not whether it can access your real life.
- Disable memory or personalization, remove the test item and read the confirmation text. Note whether disabling stops future collection, deletes existing items or merely prevents their use in replies.
If the interface cannot show what was saved or how to remove it, do not assume that memory is absent. The safe conclusion is that the scope of persistence is unclear.
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How do I test deletion and retention claims?
Deletion testing should use only the same fictional material. A delete button demonstrates that an interface accepted a request; it does not establish when backups, moderation records or derived data are removed.
- Save the policy wording for chat, memory and account deletion, including any stated waiting period.
- Send the fictional test prompt and identify every place it appears: conversation history, memory panel, search, export file or activity log.
- Delete the conversation, then inspect the memory and personalization areas separately.
- Read the confirmation and help text for scope, processing time and exceptions. Look for language about backups, legal retention, fraud prevention, safety review or aggregated information.
- If you request account deletion, record whether the service says the process is immediate, queued or irreversible, and whether you can download a copy first.
- After the stated period, check only the account interfaces you are permitted to use. Do not attempt to probe another person’s account or bypass access controls.
General FTC privacy guidance emphasizes collecting only what is needed and retaining it only while needed. That principle does not guarantee a particular service’s schedule, so rely on the service’s own current explanation and treat unaddressed copies as unresolved.
Who can see what I tell an AI companion?
Separate internal access from external sharing. A policy may permit limited employee or contractor review for safety, quality or abuse investigations while also allowing cloud, analytics, authentication or customer-support providers to process data.
- Find the categories of recipients, not only a generic “trusted partners” phrase.
- Check whether human reviewers can inspect conversations and whether you can opt out of that use.
- Look for disclosures about affiliates, processors, advertising or measurement providers, legal requests and corporate transactions.
- Review transfer and storage locations if your jurisdiction limits international processing.
- Check age-related rules. The FTC’s inquiry asks whether data practices and settings differ for children, teenagers or adults, and whether parental controls exist.
Do not interpret encryption in transit or at rest as a promise that no authorized recipient can access content. Encryption protects particular stages of handling; the policy determines permitted use and access.
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Use the same questions for every service and record the policy date. A side-by-side worksheet prevents a polished interface from hiding a weaker disclosure.
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| Comparison axis | Service A | Service B |
|---|---|---|
| Chat, account and device data collected | Record the policy’s categories; not stated if absent | Record the policy’s categories; not stated if absent |
| Training or product-improvement use | State the exact promise, default and opt-out | State the exact promise, default and opt-out |
| Memory and personalization | Describe visibility, editing and removal | Describe visibility, editing and removal |
| Retention | List periods for chats, logs, memories and backups | List periods for chats, logs, memories and backups |
| Deletion scope and exceptions | Note timing, derived data and legal or safety exceptions | Note timing, derived data and legal or safety exceptions |
| Human and third-party access | List recipient categories and purposes | List recipient categories and purposes |
| Policy-setting consistency | Check that the promised controls exist and are understandable | Check that the promised controls exist and are understandable |
| Age-related controls | Record age gates, teen settings and parental tools | Record age gates, teen settings and parental tools |
Use “not stated” when a policy supplies no answer; do not convert silence into a favorable result. A service with fewer features but precise retention and deletion language may be easier to evaluate than one with extensive controls that are poorly explained.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What privacy red flags should stop me from sharing personal information?
- The policy never says whether conversation content is retained or used for training.
- A “temporary,” “private” or “incognito” label has no definition or retention explanation.
- Memory is enabled by default, but the service cannot show or remove stored items.
- Deleting a chat is described without saying what happens to backups, summaries, inferences or moderation copies.
- Third-party access is described only as “partners” or “trusted providers,” with no purpose.
- The settings contradict the policy, or a promised opt-out is missing from the account.
- The provider reserves a right to change data practices retroactively without a clear notice and choice.
- The service asks for sensitive information that is not necessary for the feature you want.
One red flag does not prove misuse, but it identifies an unanswered question. Withhold sensitive information until the provider gives a specific, current answer you can accept.
What is a practical go/no-go decision rule?
After reading the policy and running fictional tests, classify each material issue as clear, limited or unknown.
Proceed only when the necessary controls are clear
You should be able to explain what is collected, why it is used, whether training is involved, how memory works, how long records persist, what deletion covers and who receives the data. The controls should be present in the product, not merely promised in general language.
Limit use when controls are partial
If the service gives useful answers but retains chats longer than you prefer, disable optional history or memory, avoid uploads and use fictional or low-sensitivity material. Do not treat a paid tier, a browser privacy mode or a separate email address as proof that the provider cannot access content.
Stop when a material answer is unknown
Unknown training use, retention, deletion scope or third-party access is enough reason not to disclose passwords, financial information, health details, precise location, confidential work material or information about another person. Ask the provider for clarification or choose a service whose policy is specific.
How should I use an AI companion after the initial test?
- Share the minimum detail needed for the task; replace names, dates and identifiers with placeholders.
- Keep passwords, authentication codes, payment data, government identifiers and private keys out of chats.
- Remove metadata from files and images before uploading when the service does not need it.
- Review memory and model-improvement settings after major app updates or policy notices.
- Periodically delete conversations and saved memories you no longer need, following the service’s stated process.
- Recheck the policy’s effective date because controls and defaults can change.
These habits reduce exposure, but they do not replace a provider’s obligations. The FTC’s January 2024 guidance makes clear that privacy and confidentiality promises still apply to AI services, and the September 2025 companion inquiry shows that age, data handling and parental controls remain active regulatory questions.
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Does using a browser’s private or incognito window stop an AI companion from saving chats?
No. Browser private mode mainly limits local history and cookies on your device; it does not override the service’s server-side retention, memory or training policy. Check the companion’s own settings and policy instead.
Are paid AI-companion plans automatically more private?
Not necessarily. A paid tier may change defaults or provide an opt-out, but privacy depends on the exact plan language, region and settings. Compare those terms rather than inferring protection from the price.
What should I do if the policy changes after I tested the service?
Save the policy date you evaluated and read every change notice. Recheck training, retention, sharing and deletion controls before resuming use; a material expansion is a reason to remove stored data and stop sharing sensitive information until you understand it.
Can I test a companion with a real but unimportant personal fact?
It is safer to use entirely invented data. Even a seemingly harmless fact can be combined with account details, inferred into a profile or retained in backups, so a fictional scenario tests the control without creating a new privacy record.
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