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The strongest all-purpose setup is to turn off Improve the model for everyone, keep Memory enabled only for low-sensitivity preferences, use non-personalized Temporary Chat for sensitive one-off work, and choose Search or Deep research based on how much evidence the task needs. Pair those controls with restrained Custom Instructions and prompts that state your goal, audience, date, geography, assumptions, and evidence requirements.
A practical default configuration
No single switch makes ChatGPT private, accurate, and convenient at the same time. The settings control different data flows, while tool choice and prompt design control how current and verifiable an answer can be. Use this baseline for a personal account, then move toward the privacy-max profile whenever a conversation contains sensitive material.
| Control | Recommended default | Why |
|---|---|---|
| Improve the model for everyone | Off | New conversations are not used to improve OpenAI models; existing chats remain in your history. |
| Memory | On for low-sensitivity preferences; off when personalization is not worth the privacy cost | Memory changes how answers are personalized. It is a separate decision from model-training eligibility. |
| Temporary Chat | Use for sensitive, one-off work; choose the non-personalized option when available | Temporary chats do not appear in history, do not create or update memories, and are not used to improve models. |
| Custom Instructions | Use only durable, low-sensitivity preferences | They improve consistency but may be used to improve model performance and can be shared with relevant third-party plugins. |
| Search | Use for current or unfamiliar facts | It can retrieve recent sources, but cited results can still be incomplete, outdated, or incorrect. |
| Deep research | Use for multi-source comparisons, investigations, and documented reports | It is designed for synthesis and citations rather than a quick lookup. |
Availability of Memory, Search, Deep research, Temporary Chat variants, and administrative controls can differ by plan, region, platform, and workspace policy. If a label is missing, check the account or workspace administrator rather than assuming the feature has been removed.
What the privacy controls actually change
Improve the model for everyone
On a personal account, open Settings → Data controls and turn off Improve the model for everyone when you do not want new conversations used to improve OpenAI models. OpenAI states that new conversations are not used for that purpose after the switch is off. The change does not erase previous conversations or remove them from your chat history, so it should not be confused with a history-deletion control.
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This setting answers one question: whether new conversations are eligible to improve models. It does not decide whether ChatGPT remembers facts about you, whether a chat appears in history, or whether a plugin receives information.
Memory
Memory is a personalization feature. Saved memories can influence later responses, and you can review, edit, or delete them. Turning Memory off prevents that personalization behavior, but it does not by itself change model-training eligibility. Conversely, turning off model improvement does not clear saved memories.
Use Memory for stable, low-risk preferences such as writing style, preferred units, or a recurring audience. Disable it when a topic is sensitive, when several people use the account, or when you would rather restate context than retain it. The exact Memory controls and their availability vary by plan, region, platform, and workspace.
Temporary Chat
Temporary Chat is the strongest per-conversation privacy option described in the available controls. OpenAI says temporary chats do not appear in chat history, do not create or update memories, and are not used to improve OpenAI models. A copy may be retained for up to 30 days for safety purposes, according to the OpenAI Help Center in 2026, so Temporary Chat is not the same as immediate, irreversible deletion.
When the composer offers a choice between personalized and non-personalized Temporary Chat, select non-personalized if you also do not want existing memories, Custom Instructions, or plugin personalization used for that conversation. This extra choice addresses information that might otherwise be applied to the response even though the chat itself is temporary.
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Custom Instructions
Custom Instructions are best for durable preferences that would be tedious to repeat: answer length, intended audience, formatting, assumptions to state, and a request to identify uncertainty or cite sources when appropriate. Keep them free of passwords, API keys, private legal or medical details, regulated data, and highly sensitive identifiers.
OpenAI states that information in Custom Instructions may be used to improve model performance. Relevant information can also be sent to third-party plugins when those plugins are used. Treat the field as account-level context, not as a private vault.
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Set the model-training preference
- Open ChatGPT and select Settings.
- Open Data controls.
- Turn off Improve the model for everyone.
- Start a new conversation only after confirming the toggle is off if the distinction matters for the work you are about to do.
Chats can remain visible in history after this change. If you need a conversation not to appear in history, use Temporary Chat for that conversation instead of relying on the Data controls toggle.
Review Memory before relying on personalization
- Open the Memory controls in Settings. The exact menu location can vary by platform and account.
- Review saved items and remove anything that is outdated, overly revealing, or no longer useful.
- Leave Memory on for harmless recurring preferences, or disable it before work where retaining personal context creates more risk than value.
Do not infer that an empty or disabled Memory list changes the training setting; verify both controls independently.
Start a protected one-off conversation
- Choose Temporary Chat from the chat composer or its conversation-options menu.
- If a personalization choice appears, select non-personalized for sensitive work.
- Do not paste secrets merely because the chat is temporary. A safety-retention period of up to 30 days still applies, and the model needs only the minimum information required to answer.
Write safe Custom Instructions
- Open Settings → Custom Instructions when that menu is available.
- Describe the response behavior you want, for example: concise headings, explicit assumptions, a stated date for current claims, and source links when appropriate.
- Remove credentials, confidential client names, account numbers, health details, and other identifiers.
- Revisit the text when your audience or privacy requirements change.
Choosing Search or Deep research
Tool selection should follow the question, not the desire for a more impressive answer. Search is appropriate when you need a current fact, a recent announcement, a changing policy, or an unfamiliar term. Select Search from the tools menu or invoke it with the available slash command.
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Search improves currency, not certainty. OpenAI warns that search results and citations can be incomplete, outdated, or incorrect. Open each cited page, check its publication or update date, confirm that it actually supports the sentence you plan to use, and look for disagreement between authoritative sources.
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Choose Deep research when the task requires multiple sources, a documented report, or synthesis across competing evidence. It is useful for literature-style work, multi-step comparisons, and questions where the method matters as much as the answer. It is unnecessary overhead for a single definition or a quick, stable lookup.
| Need | Search | Deep research |
|---|---|---|
| Typical task | One or a few current facts | Multi-source investigation or comparison |
| Output | Quick answer with citations | Structured, documented synthesis |
| Speed | Usually faster | Usually slower because it performs more research steps |
| Verification burden | Inspect the cited pages and dates yourself | Still inspect the sources; a longer report is not proof of correctness |
| Best privacy practice | Provide only the minimum context needed | Define the allowed source types and exclude confidential material before starting |
Prompt settings that improve accuracy
Model settings cannot compensate for an underspecified request. Put the decision-relevant context in the prompt and make the model show where uncertainty remains.
Specify the assignment
State the goal, intended audience, output format, constraints, geography, and date range. “Explain this policy” leaves the jurisdiction and effective date unknown; “Compare the policy in Ontario and California as of October 2026 in a table” gives the model a checkable target.
Request assumptions and uncertainty
Ask the model to list assumptions before calculating or recommending anything, identify missing information, separate established facts from inferences, and say when evidence is mixed. This makes a confident-looking guess easier to spot.
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Use evidence deliberately
For current claims, explicitly request Search and then inspect the linked sources. For a comparison, define the axes in advance: cost, privacy exposure, evidence quality, speed, effort, or another decision criterion. Ask for “not established” when a value cannot be verified rather than inviting an estimate.
Iterate instead of accepting the first draft
OpenAI describes prompt engineering as an iterative approach. Treat the first response as a working draft: point out an omitted constraint, supply a correction, ask for a clearer table, or request a distinction between facts and recommendations. A second, narrower prompt is often more useful than one enormous initial instruction.
A reusable prompt pattern
Goal: state the decision or deliverable in one sentence.
Audience: describe the reader’s expertise and location.
Time frame: give the relevant as-of date or period.
Constraints: list length, budget, tools, exclusions, and format.
Method: use Search for current facts or Deep research for multi-source synthesis.
Quality checks: state assumptions, flag uncertainty, cite supporting sources, and mark any value that is not established.
Output: specify headings, table columns, and the final recommendation criteria.Three configurations for different risk levels
Privacy-max configuration
- Turn off Improve the model for everyone in Settings → Data controls.
- Disable Memory and remove saved items that are not needed.
- Use non-personalized Temporary Chat for sensitive, one-off work.
- Leave Custom Instructions empty or limited to harmless formatting preferences.
- Use Search only when currency is necessary, and avoid uploading or pasting identifying details.
This profile minimizes personalization and history exposure, but it requires you to repeat context and may produce less tailored answers.
Balanced personal configuration
- Keep model improvement off if you do not want new conversations used for that purpose.
- Keep Memory on for low-sensitivity preferences and review it periodically.
- Use concise Custom Instructions that describe style, audience, and uncertainty handling.
- Switch to non-personalized Temporary Chat whenever the subject becomes sensitive.
- Use Search for current facts and Deep research only when the question warrants multi-source work.
This is the most practical setup for routine planning, writing, learning, and research that does not contain confidential information.
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Research-focused configuration
- Keep the privacy controls appropriate to the material before starting.
- Define the date range, geography, source types, and comparison criteria in the prompt.
- Use Search for targeted updates; use Deep research for a report that must reconcile several sources.
- Require citations, publication dates, explicit uncertainty, and a separate section for unresolved disagreements.
- Read the underlying sources rather than treating citations or a polished report as automatic validation.
Shared or managed workspace
In a team or managed workspace, an administrator may control feature availability or data handling. Confirm the workspace policy before entering client, employee, health, financial, or regulated information. A personal account’s toggle or Memory behavior may not map exactly to an organization’s configuration.
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Trade-offs to expect
| Configuration choice | Privacy exposure | Personalization benefit | Currency and evidence | User effort |
|---|---|---|---|---|
| Model improvement off | Reduces eligibility of new chats for model improvement | No direct effect on personalization | No direct effect on freshness | Low; verify the toggle |
| Memory on | More retained personal context | Higher continuity across chats | No guarantee of current facts | Low after review |
| Memory off | Less personalization context | Lower continuity | No direct effect on source quality | Higher; repeat preferences |
| Personalized Temporary Chat | No history or new memories, but existing personalization may be applied | Some continuity during the response | No automatic freshness | Low |
| Non-personalized Temporary Chat | No history, no new memories, and avoids existing Memory, Custom Instructions, and plugin personalization | Lowest personalization | No automatic freshness | Low to moderate; provide context in the prompt |
| Search | Depends on the information you provide and the sources opened | Little long-term personalization | Better currency, not guaranteed correctness | Moderate; inspect sources and dates |
| Deep research | More context may be processed because the task is broader | Useful synthesis rather than memory-based personalization | Designed for multi-source, cited reports | Higher; define scope and verify findings |
Common problems and fixes
“I turned off model improvement, but my chats are still visible.”
That is expected. The Data controls switch affects use of new conversations to improve models; it does not remove chats from history. Use Temporary Chat when avoiding history for a one-off conversation is the priority.
“I disabled Memory, but the answer still reflects something I said before.”
Check whether Custom Instructions, the current conversation, a workspace policy, or another personalization feature supplied the context. Memory and model-training controls are separate, and disabling one does not retroactively erase every source of context.
“Temporary Chat still feels personalized.”
Choose the non-personalized Temporary Chat option when it is offered. Ordinary temporary behavior prevents history and new memory creation, while the non-personalized choice also avoids applying existing memories, Custom Instructions, and plugin personalization.
“Search gave me a citation, so can I trust the claim?”
No. OpenAI explicitly cautions that search results and citations can be incomplete, outdated, or incorrect. Open the cited page, check its date and jurisdiction, and confirm that the wording supports the precise claim.
“Deep research produced too much detail.”
Use ordinary Search for a quick lookup, or narrow the Deep research brief with a source limit, date range, geography, required table columns, and a short executive conclusion. More sources increase effort and do not automatically resolve conflicting evidence.
“The answer is fluent but not useful.”
Rewrite the prompt with a concrete decision, audience, constraints, and output format. Ask for assumptions, uncertainty, and a table with named comparison axes. Then provide targeted feedback on what the first response missed; iterative refinement is an expected part of prompt engineering.
Quick Recap
A final pre-send checklist
- Is the conversation sensitive enough to require non-personalized Temporary Chat?
- Is Improve the model for everyone set the way you intend in Settings → Data controls?
- Could Memory or Custom Instructions reveal context that this task does not need?
- Have you removed passwords, secrets, regulated data, and unnecessary identifiers?
- Did you state the audience, geography, date range, constraints, and desired format?
- Do you need Search for current facts, or Deep research for multi-source synthesis?
- Have you asked for assumptions, uncertainty, and citations where appropriate?
- Will you inspect the cited pages and publication or update dates before acting on the answer?
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