Training preferences, saved content and personal data in AI responses need separate controls. Start with the provider and account you use, then address any public source exposing your personal data.
For an ordered checklist, see how to manage personal data across AI services. An AI answer is not proof that your data was in a training dataset.
Documentation checked October 1, 2026. Signed-in account interfaces were not tested. Settings and eligibility can change.
Turn off Improve the model for everyone for new eligible conversations, or use OpenAI’s privacy portal. Feedback can still include the associated conversation for training. Chat deletion and personal-data requests are separate.
Read the ChatGPT guideConsumer model improvement depends on your saved choice. Feedback, safety review and explicit program opt-ins have separate rules. Commercial products use different terms.
Read the Claude guideWith Keep Activity off, future chats are not used to improve Google’s AI models unless you submit feedback. Service and safety processing, including human review, can continue. Deleting activity is separate.
Read the Gemini guideThe consumer AI data retention setting controls training collection after opt-out. It does not delete history or previously collected training data; service and legal processing can continue.
Read the Perplexity guideChoose Microsoft’s documentation for your app version and account. Updated consumer Copilot has separate memory, history, web search and personalization controls. Work and school accounts use different policies.
Read the Copilot guideMeta documents an EU route to object to public data being used for training. This is a regional process, not a universal account toggle. Check the options for your account, region and type of concern.
Read the Meta AI guideFor X and Grok, use the separate Grok privacy guide.
Delist finds exposed personal data, pursues supported removal requests and tracks their status. Review the current scope and any steps that require you. See how Delist works.
The free scan checks public exposure and known breach data within its current scope. It is not an inspection of a provider’s training dataset. A provider may require account access or identity verification for its own controls.
Removing public listings can reduce exposure at those sources. It does not establish a change to a trained model. See how training, retrieval and stored content differ.
Keep the request date, confirmation, stated scope and provider response. A submitted request, an accepted request and a verified removal are different outcomes. Recheck the specific response or source rather than assuming every copy is gone.
Some services offer training preferences for eligible account content. Availability and exceptions depend on the product, account and region. A conversation setting does not necessarily cover public web data or feedback.
Training permission and stored content are separate controls. Check the provider’s chat, file, memory and account deletion options, including retention exceptions.
Keep the prompt, response, date, product and any cited URL. Follow the provider’s personal-data or privacy request process when available. Requests are reviewed under its policy and applicable law; submission does not establish acceptance or removal.
Removing a listing can reduce exposure at that source. It does not prove that a model trained on the listing, undo completed training or remove other copies. Follow up separately on a specific AI response.
Sources accessed . See our source standards.
Run a free scan to see exposed personal data within Delist’s current scope. Use the provider guides for AI account controls and response concerns.