Can Submitting AI Feedback Override Your Training Opt-Out?
Sometimes. A general AI training opt-out may not cover a conversation you later choose to submit as feedback, so the feedback notice and included context still matter.
Sometimes. Turning off routine AI training does not necessarily cover a conversation you later choose to submit as feedback. Current OpenAI and Google documentation both describe feedback-specific paths that can apply after a general opt-out. That does not mean every rating always trains a model or sends every attachment. It means the feedback action, included context, account type, and current notice must be checked separately.
Who This Guide Is For
This guide is for people who:
- disabled a setting such as “Improve the model for everyone” or “Keep Activity”
- still use thumbs-up, thumbs-down, report, or written-feedback controls
- discuss client, employee, health, financial, legal, research, or product information with AI
- use consumer AI and assume one account-wide toggle controls every data path
- administer a business or API workspace with separate feedback-sharing settings
- want a privacy-focused AI workflow without making unrealistic claims about zero processing
The question is not whether feedback is good or bad. Feedback can help providers correct inaccurate or unsafe outputs. The privacy question is whether submitting it creates a new, voluntary use of data that the normal training opt-out did not cover.
The Short Answer: An Opt-Out And A Feedback Submission Can Be Separate Choices
Think of the controls as two gates:
- Routine-use gate: May ordinary future conversations be used to improve or train models?
- Feedback gate: May this selected interaction and its associated context be sent for review or improvement because the user deliberately submitted feedback?
Turning off the first gate does not always lock the second. A later click can be a new data-sharing decision under the provider's current terms and interface.
| Question | Routine training setting | Voluntary feedback action |
|---|---|---|
| What triggers it? | Account, app, workspace, or organization setting | Rating, report, feedback form, or explicit share action |
| What data can be in scope? | Eligible chats under the product's ordinary policy | Selected response, associated conversation, recent context, written comments, and sometimes uploads or connected content |
| Is it always enabled? | Depends on product and account type | Depends on the feedback feature, notice, and selections |
| Can it involve human review? | Provider-specific | Often possible when investigating quality or safety issues |
| Is retention the same as chat history? | Not necessarily | A reviewed feedback copy may follow a separate retention path |
| Does one provider's rule apply everywhere? | No | No—check the exact product, account, and interface |
“Override” is useful shorthand, but it can be misleading if taken literally. The provider may not switch your account-wide opt-out back on. Instead, your voluntary feedback can create a narrower exception for the conversation or context you chose to submit.
What Current Provider Documentation Says
Provider controls change, so the examples below were checked against official documentation in July 2026. Recheck the live notice before submitting sensitive material.
OpenAI: Feedback Can Be A Separate Exception After Opting Out
OpenAI's current guide to how data is used to improve model performance says individual users can opt out so new conversations are not used to train its models. The same guide then identifies a separate choice: even after opting out, a user can still provide feedback, such as a thumbs-up or thumbs-down, and the entire conversation associated with that feedback may be used to train models.
That wording supports a precise conclusion:
- the opt-out still matters for routine use of new conversations
- voluntary feedback can be treated differently
- the relevant scope may be the associated conversation, not only the one answer beside the rating icon
It does not prove that every rating is reviewed, retained for the same period, or used in a training run. “May be used” describes an allowed path, not a guarantee about every individual submission.
OpenAI also distinguishes consumer services from business products. Its documentation says ChatGPT Business, ChatGPT Enterprise, and API inputs and outputs are not used for training by default. However, organizations can deliberately enable some data-sharing features.
For example, OpenAI's API data-sharing documentation says Playground feedback sharing is disabled by default. If an organization owner enables it, a user can submit feedback with the conversation up to that point, including inputs, outputs, and uploaded files. Organizations with Zero Data Retention enabled cannot opt in to those data-sharing mechanisms.
That business example shows why “OpenAI does X” is too broad. Consumer ChatGPT, Codex, ChatGPT Business, Enterprise, and API projects can have different defaults and separate controls.
Google Gemini: Feedback Can Be Used When Keep Activity Is Off
Google's Gemini Apps Privacy Hub draws a similar boundary. It says that when Keep Activity is off, future chats do not appear in Gemini Apps Activity and are not used to train Google's AI models unless the user chooses to send feedback.
If a user submits feedback while Keep Activity is off, Google says it collects and uses:
- the feedback itself
- context that helps Google understand it, including the last 24 hours of chats
- content included in those chats, such as uploads and data from Connected Apps
Google says that feedback, associated conversations, included content, and related data may be reviewed by trained teams and used to provide, improve, and develop Google products, services, and machine-learning technologies. It also says reviewed feedback and associated data can be retained for up to three years after being disconnected from the Google Account.
Google's separate Gemini feedback instructions say the associated conversation is added to a feedback submission. The current form can also let a user choose whether to include files or images uploaded before the response.
Again, the narrow conclusion matters. It would be inaccurate to say every Gemini rating always includes every file or is always retained for three years. The documentation describes possible included content, a feedback-specific improvement path, and a maximum retention period for reviewed feedback.
A Four-Layer Test For Any AI Feedback Control
Do not stop after checking one training toggle. Audit the feedback path in four layers.
Layer 1: The Baseline Setting
Identify the exact control you changed. Its name may refer to:
- model training
- product improvement
- saved activity
- chat history
- memory or personalization
- audio or multimodal improvement
- organization-level data sharing
These are not interchangeable. Turning off training does not necessarily delete chats. Turning off history does not necessarily stop temporary processing. Turning off memory does not necessarily change a feedback policy.
Record the product, account type, setting name, and date. This is especially important for high-risk workflows because provider labels and defaults can change.
Layer 2: The Feedback Trigger
Determine what the rating control actually does:
- Does one click submit immediately?
- Does it open a review form?
- Is there a final Submit button?
- Can you add written comments?
- Does “Report” follow a different path from “Dislike”?
- Does a mobile app behave differently from the web app?
Do not treat a thumbs icon as a harmless one-bit signal. The interface may associate it with far more context.
Layer 3: The Payload
Read the notice and inspect every selectable item. Look for:
- the current answer
- the entire associated conversation
- a recent context window
- earlier prompts and responses
- uploaded documents, images, audio, or video
- content retrieved from connected apps
- screenshots, diagnostic data, or device information
- your written explanation of the problem
Even when an original file is not attached, the conversation may contain summaries, quotations, tables, names, or numbers derived from it. An attachment checkbox is only one part of the payload.
For more detail on attachment scope, read Can Rating An AI Response Send Uploaded Files For Model Improvement?.
Layer 4: Use, Review, Retention, And Deletion
Ask four separate questions:
- Can the feedback be used for model training or broader product improvement?
- Can a human or service provider review it?
- How long can the feedback copy be retained?
- Does deleting the visible chat also delete the submitted feedback record?
These questions should not be collapsed into “Is training off?” The NIST Privacy Framework is designed to help organizations identify and manage privacy risk across data processing. For an AI buyer, that means tracing the purpose, transmission, review, retention, and deletion of feedback—not relying on a single label.
What This Does Not Mean
It Does Not Mean The Training Opt-Out Is Fake
A general opt-out can still prevent routine eligible conversations from being used for model improvement. That is a meaningful control. The point is that a user can later make a separate choice to submit particular content as feedback.
It Does Not Mean Every Rating Always Trains A Model
Official documentation often says feedback “may” be used or helps improve services. A submission might be used for quality evaluation, safety investigation, product debugging, human review, model training, or more than one purpose. Do not turn an allowed use into a claim about what happened to one specific rating without evidence.
It Does Not Mean Every Feedback Form Sends The Entire Account History
OpenAI describes an associated conversation, while Google documents associated conversation context and, in one Keep Activity-off scenario, up to the last 24 hours of chats. The scope is provider- and feature-specific. Neither statement supports a universal claim that all account history is sent.
It Does Not Mean Every Uploaded File Is Automatically Included
Some interfaces expose attachment choices. Some documentation mentions conversation context without saying every original binary file is attached. File-derived text may remain in the conversation even when the original file is excluded. Inspect both the file list and the visible thread.
It Does Not Mean Deleting The Chat Necessarily Deletes Feedback
Normal chat storage and submitted feedback can be separate records. Google explicitly says reviewed feedback may remain after activity deletion because it is disconnected from the account and retained under a separate period. Check the provider's feedback-specific deletion language.
It Does Not Mean A Consumer Setting Controls A Managed Workspace
Business, enterprise, education, and API products can have different defaults and administrator controls. A personal subscription is not automatically governed by business data terms, and a third-party AI app may send feedback to the app developer, the model provider, or both.
A Safer Feedback Workflow
1. Pause Before Rating A Sensitive Thread
If the conversation includes client information, unreleased code, legal strategy, personal records, research data, credentials, or proprietary files, do not click reflexively. Treat feedback as a possible sharing event.
2. Read The Live Disclosure
Open the feedback form and read the text beside the final submit control. Look for “associated conversation,” “recent chats,” “files,” “images,” “connected apps,” “human review,” and “improve or train.”
3. Minimize The Context
When the interface permits it, remove attachments and extra diagnostic data that are not needed. Review earlier turns for sensitive information. Remember that file-derived excerpts can remain in text even after the file itself is excluded.
4. Reproduce The Problem Safely
For a useful but sensitive failure, create a new conversation with a synthetic example:
- replace real names with placeholders
- reduce a document to the smallest relevant excerpt
- substitute fake numbers and dates
- remove private URLs, identifiers, and metadata
- upload a purpose-built sample rather than the original file
Then submit feedback on the sanitized reproduction instead of the original thread.
5. Verify The Account Boundary
Confirm whether you are in a personal account, managed workspace, API project, or third-party app. For organizational data, check whether an administrator has enabled feedback sharing and whether the organization's policy permits voluntary submission.
6. Save Evidence When The Decision Matters
For regulated, contractual, or client-sensitive work, record the product, account type, visible notice, selected options, policy link, and date. A screenshot or approved internal record can be more useful than remembering how the interface looked months later.
What To Check Before Submitting AI Feedback
- [ ] What exact training or activity setting is off?
- [ ] Does that setting mention an exception for voluntary feedback?
- [ ] Does the rating submit immediately or open a form?
- [ ] Is one response, the whole conversation, or a recent context window included?
- [ ] Are files, images, audio, screenshots, or connected-app content included?
- [ ] Does the thread contain sensitive information derived from an upload?
- [ ] Can a human reviewer see the submission?
- [ ] Is the stated purpose training, product improvement, safety, support, or debugging?
- [ ] Does the account use consumer, business, education, or API terms?
- [ ] Has an organization owner enabled feedback sharing?
- [ ] How long can a reviewed feedback copy be retained?
- [ ] Does deleting the chat also delete the feedback record?
- [ ] Can the problem be reproduced with synthetic or redacted content?
Where OpenVeil Fits
OpenVeil is a paid, privacy-focused AI chat workspace with browser-local history and no server-side chat-history record for normal private chat sessions. OpenVeil does not use prompts, uploaded files, images, audio, selected local-history context, or AI outputs to train foundation models.
That does not mean OpenVeil is fully offline, anonymous, or free of necessary provider processing. Active requests may still be processed by OpenVeil and necessary AI, search, upload-processing, hosting, routing, security, billing, and infrastructure providers. Account, billing, security, and operational records are also separate from browser-local private-chat history.
OpenVeil is designed for people who want the convenience of hosted AI without a normal server-stored private-chat archive. Before using any hosted AI for sensitive material, review its current privacy boundary and decide whether necessary external processing fits the task.
Read the OpenVeil privacy policy and What To Check Before Trusting Any AI Privacy Claim, then create an OpenVeil account if that boundary fits your workflow.
Frequently Asked Questions
Can A Thumbs-Up Or Thumbs-Down Override My AI Training Opt-Out?
It can create a separate exception for the submitted conversation. OpenAI says voluntary feedback can be used for training even after an individual user opts out. Google says feedback can be collected and used to improve Gemini Apps when Keep Activity is off. Check the exact product and notice.
Does The Provider Turn My Account-Wide Training Setting Back On?
Not necessarily. A feedback submission can authorize use of selected content without changing the standing preference for ordinary future chats. “Separate feedback path” is usually more precise than saying the entire opt-out was reversed.
Does AI Feedback Include The Whole Conversation?
It can. OpenAI refers to the entire conversation associated with feedback. Google says associated conversation and included content can be submitted, and documents additional context for feedback when Keep Activity is off. The exact scope depends on the current interface.
Can Feedback Include Files Or Connected-App Content?
Yes, in some products and configurations. OpenAI explicitly documents uploaded files in an enabled API Playground feedback path. Google documents files, images, and Connected Apps content in Gemini feedback. Do not assume every rating includes every file.
Does Temporary Chat Prevent Feedback Use?
Do not assume it does. Temporary or no-history modes can limit ordinary history or training, but a later voluntary feedback action may follow a separate policy. Read the feedback disclosure before submitting.
Are Business And API Accounts Different?
Often. OpenAI says business and API content is not used for training by default, while an organization owner can enable certain sharing mechanisms. Managed Google accounts can also have different capabilities and administrator controls. Verify the exact workspace.
Can I Give Useful Feedback Without Sharing Sensitive Data?
Usually. Reproduce the problem in a new thread with synthetic names, fake values, and the smallest non-sensitive excerpt needed to demonstrate the issue. Then submit feedback from that sanitized example.
The Bottom Line
A training opt-out is not always the final control in an AI feedback workflow. It can stop routine model-improvement use while leaving the user free to make a separate, voluntary feedback submission that includes associated context.
Before clicking Submit, check four layers: the baseline setting, the feedback trigger, the payload, and the use/retention path. When the conversation is sensitive, minimize the context or recreate the problem with synthetic data. Privacy is strongest when unnecessary information is never included in the feedback copy.