THE SHORT ANSWER
Use Data Controls to turn off model-improvement use while retaining regular chat history, then verify the current help text. Use Temporary Chat for a separate no-history workflow; neither setting alone authorizes confidential data.
BEFORE YOU READ
Who this research is for
Read now
- You need to make the decision described here using current primary sources
- You want a repeatable test rather than a universal product ranking
Check something else first
- You need individualized legal, tax, medical or security advice
- You are looking for a guarantee that a tool or course will produce a particular outcome
KEY POINTS
What matters most
- 01
The model-improvement control can be changed separately from chat history
- 02
Temporary Chat has a different history and retention purpose
- 03
The setting does not replace contract or organizational approval
DECISION TABLE
Choose the control for the intended outcome
| Goal | Control | What still needs review |
|---|---|---|
| Keep history, stop improvement use | Data Controls setting | Retention and other processing |
| Do not keep the chat in history | Temporary Chat | Temporary retention and safety review |
| Handle approved business data | Business contract and admin settings | Organization policy and access controls |
ACTION PLAN
Turn the comparison into a four-step decision
Use one real, low-risk task and record the evidence. The goal is a decision you can reproduce and reverse—not a one-time impression.
- 01
Fix the task and constraints
Write the input, desired output, frequency and unacceptable failure. Start from this criterion: The model-improvement control can be changed separately from chat history
- 02
Verify the current primary sources
Open the 2 listed sources, confirm the account, region and retrieval date, and note any unresolved conflict.
- 03
Run the decision table
Replace every example with your own volume, time and required condition. Record manual work that remains after using the product or process.
- 04
Set a review trigger
Keep the decision with its assumptions. Review when pricing, terms, workload or the required data changes; reverse it if the named benefit does not appear.
WORKED EXAMPLE
Worked example: make assumptions visible
This is a structure for your own test, not a performance promise. Replace each value or condition with observed data.
- Keep history, stop improvement use
- Data Controls setting → Retention and other processing
- Do not keep the chat in history
- Temporary Chat → Temporary retention and safety review
- Handle approved business data
- Business contract and admin settings → Organization policy and access controls
What this example showsUse Data Controls to turn off model-improvement use while retaining regular chat history, then verify the current help text. Use Temporary Chat for a separate no-history workflow; neither setting alone authorizes confidential data.
Open Data Controls on the account you use
In ChatGPT settings, locate Data Controls and the option concerning improvement of the model. Change it on the relevant account and record the date.
Interface wording can differ by platform and version. Use the official help page as the durable reference instead of relying only on an old screenshot.
Do not confuse history with model improvement
A regular conversation can remain in history while the model-improvement choice is disabled. These are separate user goals and should be documented separately.
If your goal is that a conversation not appear in history, review Temporary Chat and its current retention description rather than changing the wrong control.
Understand what the toggle does not decide
The setting does not determine whether a customer contract permits upload, whether administrators can manage the account or how connected services handle data.
Avoid credentials and sensitive identifiers. Use an approved business service when the work requires contractual or administrative protections.
Recheck after product changes
Providers can change defaults, labels and related features. Include the setting in periodic account checks and after major product announcements.
Record the official URL, account type and effective setting so the decision can be reproduced by another person later.
COMMON PITFALLS
Where decisions go wrong
Treating a plan label as an outcome
A paid tier or popular product does not guarantee accuracy, completion or return. Test the final deliverable and the review work that remains.
Skipping the applicable source
We reviewed OpenAI's current Data Controls and consumer data-use documentation and separated the effect of each control.
Ignoring what can change
Settings, labels and retention details can change. Verify the current official help article and the interface on your account.
DECISION NOTE
Decision record to keep
Record the use case, selected option, rejected alternative, decisive condition, source check date and review trigger. Current conclusion: Use Data Controls to turn off model-improvement use while retaining regular chat history, then verify the current help text. Use Temporary Chat for a separate no-history workflow; neither setting alone authorizes confidential data.
CLAIM → SOURCE
Claims and supporting sources
Each central claim points to a primary or public source reviewed for this article.
The model-improvement control can be changed separately from chat history
Temporary Chat has a different history and retention purpose
The setting does not replace contract or organizational approval
FAQ
Frequently asked questions
What is the short answer?
Use Data Controls to turn off model-improvement use while retaining regular chat history, then verify the current help text. Use Temporary Chat for a separate no-history workflow; neither setting alone authorizes confidential data.
How was this comparison built?
We reviewed OpenAI's current Data Controls and consumer data-use documentation and separated the effect of each control.
What should I verify before acting?
Settings, labels and retention details can change. Verify the current official help article and the interface on your account.
METHODOLOGY
How this article was researched
We reviewed OpenAI's current Data Controls and consumer data-use documentation and separated the effect of each control.
Read the shared editorial method ↗SOURCES