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Use two different defenses for two different exposure paths. If you upload an unpublished manuscript, review report, data set, or method to an AI service, you disclose it to that service and must check its current terms, retention, access, reuse, and model-training settings before submission. If the work is on a website, combine a visible rights reservation, supported metadata, crawler-specific instructions, and server-side access controls. No notice or robots.txt file guarantees that every crawler will comply, and blocking future access does not erase material collected in the past.
Start by separating AI uploads from web scraping
Researchers often use “AI training” and “AI scraping” as if they were the same event. They are not, and the remedy depends on which path is involved.
| Exposure path | What happens | Primary controls | Main limitation |
|---|---|---|---|
| Upload to an AI service | Your material is transmitted to a third-party provider for processing. Depending on the service and account, it may be retained, reviewed by people, reused, or used for model development. | Classify the material, read live terms, disable training or reuse where available, use an approved closed environment, and obtain required permission. | A “private” label is not a substitute for contractual terms. Once sent, you cannot assume the provider will delete every copy immediately. |
| Public or reachable website | Crawlers fetch pages, files, feeds, or APIs. A provider may use the content for search, retrieval, model development, or another stated purpose. | Rights notices, metadata, crawler-specific robots.txt rules, authentication, firewalls, rate limits, and monitoring. |
robots.txt and metadata are instructions, not authentication. A non-compliant crawler can ignore them. |
This distinction determines the first question to ask: Do I control the service receiving the file, or do I control the server publishing the file? Treat each answer as a separate workstream.
Protect material before you send it to an AI tool
1. Classify every item
Make a short classification before opening an AI tool. Include:
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- Unpublished manuscript text, figures, tables, code, hypotheses, and results.
- Peer-review manuscripts, editor correspondence, reviewer reports, and recommendation notes.
- Proprietary methods, trade secrets, patent-sensitive discoveries, and sponsor-restricted information.
- Personal data, health information, identifiable participant data, or confidential interview material.
- Third-party copyrighted text, licensed data, or material supplied under a nondisclosure agreement.
- Restrictions imposed by your journal, institution, employer, funder, ethics board, or collaborator.
Classification should follow the most restrictive applicable rule. A manuscript does not become safe to upload merely because it has not yet been submitted, and a review report remains confidential even after the journal makes a decision.
2. Read the service’s current terms and settings
Do this at the time of use, not only when an account is created. Terms and product controls can change, and an individual plan may not have the same protections as an institutional or enterprise plan. Check each item below and save the relevant page or setting for your records.
| Question | What to look for | Why it matters |
|---|---|---|
| Input retention | How long prompts, files, and outputs are stored; whether deletion is automatic or user-initiated. | Retention increases the period during which the material can be accessed or disclosed. |
| Model training and improvement | An express exclusion from training, model development, or service improvement; an account-level opt-out switch. | Processing a file to answer your request is different from adding it to a training or evaluation corpus. |
| Human access | Support, safety, quality-assurance, or contractor review rights. | Confidentiality risk includes people who can access the provider’s systems, not only the model. |
| Provider and subprocessors | Where data is processed, which affiliates or vendors receive it, and how they are bound. | A provider may rely on other companies to host, filter, or monitor content. |
| Your rights and the provider’s licence | Ownership language, licences to host or modify input, and rights that survive deletion. | Give only the rights needed to provide the service. Elsevier advises authors to avoid granting broader rights or training permission than necessary in its journal policy (updated June 2026). |
| Deletion and incident process | How to delete files, submit a privacy request, report a breach, and obtain confirmation. | You need a practical remedy if a file is uploaded accidentally or exposed. |
Do not infer an answer from marketing language such as “private,” “secure,” or “not used publicly.” Find the operative term, setting, or contract clause. If the service does not clearly exclude training and secondary use, treat the tool as unsuitable for confidential material.
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3. Use a closed or institution-approved environment when required
A closed deployment, an institution-managed tenant, or hosting with contractual privacy guarantees can reduce exposure to unrelated uses. The U.S. Geological Survey describes closed environments or third-party hosting with guaranteed privacy as possible safeguards for unpublished, sensitive, and proprietary information in its AI information-safeguarding FAQ. Confirm the exact configuration: a consumer account and an institution-approved service may have different retention, logging, and training controls.
“Closed” does not mean risk-free. Administrators, identity systems, backups, plugins, and connected storage can still create access paths. Verify who can administer the environment, where data is stored, and how deletion works.
4. Minimize what the tool receives
When policy permits limited assistance, send the smallest useful excerpt rather than an entire manuscript or data set. Remove names, email addresses, participant identifiers, unpublished numbers, and proprietary details. Replace sensitive passages with a short description and ask for a general transformation. This reduces the amount disclosed, but it does not remove the obligation to check the service terms or obtain permission.
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Do not assume that deleting a chat removes provider logs, backups, safety records, or copies made by integrations. The service’s retention language controls that question.
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Confidential journal review
Peer-review material is normally confidential. The American Physical Society says confidential manuscripts or reports may be used with an AI tool only when the tool’s terms state that uploaded material will not be used as training data; see its Appropriate Use of AI Tools guidance. If the terms are silent, unclear, or change after submission, do not upload the material.
Elsevier’s journal policy likewise tells reviewers and editors not to upload submitted confidential manuscripts or parts of them into AI tools. Its policy explains that even a tool described as private still receives the confidential research when you upload it. Check the current journal instructions as well as the provider’s terms.
Books, commissioned work, and planned submissions
For books and commissioned content, Elsevier’s policy updated July 2026 advises authors not to upload restricted or sensitive content unless they are confident that the terms protect confidentiality and prevent training. Oxford University Press similarly tells authors not to upload work intended for publication to a tool that does not permit an opt-out from reuse or training; its guidance is at Author use of Artificial Intelligence.
These are publisher policies, not a universal rule for every journal or country. Follow the policy that governs your particular submission, contract, employment, and funding arrangement.
Protect research published on a website
Publish a clear rights reservation
Put a plain-language notice on the page and, where supported, in the document or image metadata. State who owns the material, what uses are allowed, and whether text-and-data mining or model-development use is reserved. Make the notice match your actual rights: you cannot reserve rights that belong to a co-author, publisher, funder, or third-party licensor.
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The International Press Telecommunications Council (IPTC) recommends visible notices and rights statements in metadata in its publisher guidance. A notice communicates your position to people and services that read it; it does not technically stop a request from reaching your server.
Use crawler-specific robots.txt rules
Identify the agents relevant to your site and write rules for each one. Rules apply to the hostname where the robots.txt file is served, so repeat the policy for separate subdomains when necessary. Use the provider’s current documentation for the exact user-agent name and syntax.
Anthropic documents separate purposes for its crawlers. Its privacy guidance says ClaudeBot may gather content for model development, while Claude-User retrieves pages at a user’s direction. The example below blocks ClaudeBot across a site:
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Disallow: /Anthropic’s current explanation is available at Does Anthropic crawl data from the web, and how can site owners block the crawler?. Treat that example as provider-specific: it does not block other companies’ agents, and names or policies can change.
For a narrower path, use a path-specific rule after checking the crawler’s support for it:
User-agent: ClaudeBot
Disallow: /unpublished/
Disallow: /drafts/Test the deployed file from the public URL, check syntax with your server or search-console tooling, and review access logs. A typo, an incorrect hostname, or a rule placed on the wrong subdomain can leave the intended files exposed.
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Understand what robots.txt can and cannot do
- It is a voluntary protocol, not a password or firewall.
- It guides compliant crawlers; a crawler that ignores it can still request the file.
- It does not protect a file that is already available through an unprotected API, CDN URL, backup, feed, or alternate hostname.
- It does not delete copies collected before the rule was deployed.
IPTC recommends network-level protection because some crawlers disregard robots.txt and metadata. Use robots.txt as a signal, not as your only barrier.
Apply authentication and network controls for genuinely sensitive work
If a document should not be public, require authentication or place it behind an access-controlled repository. A firewall, web application firewall, reverse proxy, or allowlist can deny requests before content is delivered. Rate limits and bot-management rules can reduce automated harvesting, while logs help you investigate unusual traffic.
Server-side controls also affect legitimate users. Decide whether collaborators need individual accounts, whether a repository should be reachable only through a VPN, and how access is revoked when a project ends. Protect the files themselves, not just the landing page: PDFs, images, JSON endpoints, and downloadable archives often have separate URLs.
Build a protection plan around the actual threat
| Situation | Recommended baseline | Escalate when | Trade-off |
|---|---|---|---|
| General public article with a rights reservation | Visible notice, accurate metadata, crawler rules for identified agents, and access-log monitoring. | You see non-compliant requests or the material becomes commercially or legally sensitive. | Search and user access remain broadly open, but compliant crawlers receive your preference. |
| Unpublished manuscript stored privately | Do not upload to an unapproved AI service; use an approved closed environment and least-privilege sharing. | Personal data, patent-sensitive results, or contractual restrictions are involved. | More administration and potentially fewer convenient tools. |
| Confidential peer-review file | Follow the journal’s reviewer policy and use AI only when terms expressly exclude training, if use is allowed at all. | The policy is silent, the provider changes terms, or the file contains third-party confidential material. | Manual review may take longer, but confidentiality obligations take priority. |
| Highly sensitive web-hosted material | Authentication, server-side authorization, firewall controls, restricted storage, and monitoring; do not rely on robots.txt. | There is evidence of scraping, a legal hold, or a data breach. | Lower discoverability and greater operational cost. |
Compare options by exposure path, sensitivity, personal data, contractual rules, who controls the service or site, whether you need a usage signal or actual denial, crawler coverage, effect on legitimate access, monitoring burden, and whether the measure applies only to future requests.
Keep a record of each decision
- Record the material classification and the people or organizations that own or control it.
- Record the AI service, account type, enabled settings, terms URL, and date checked.
- Record approvals from the institution, journal, editor, employer, funder, or data steward.
- Record exactly what was uploaded, what was redacted, and when it was deleted.
- For websites, record rights notices, metadata fields, crawler names, robots.txt contents, firewall rules, and affected hostnames.
- Review the record when a provider changes terms, a project moves to a new host, or a manuscript is submitted or published.
No single standard dictates this log, but documenting the decision gives you an audit trail for confidentiality, contractual compliance, and incident response.
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If material has already been exposed
Uploaded to an AI service
- Stop further uploads and preserve the account, prompt, file name, and time of submission.
- Check the service’s deletion, retention, training opt-out, and privacy-request procedures.
- Delete the file and associated conversations where the service allows it, then request confirmation if available.
- Notify the responsible institution, editor, data steward, sponsor, or collaborator under the applicable incident process.
- Assess whether personal data, patent rights, confidentiality obligations, or publication agreements require legal or regulatory advice.
Do not promise that a deletion request removes every prior copy or reverses model training. The provider’s documented process and the facts of the incident determine what can be established.
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- Preserve access logs, timestamps, requested URLs, user-agent strings, and relevant file hashes.
- Move sensitive files behind authentication or block the offending network path while maintaining access needed by legitimate collaborators.
- Publish or update rights notices and deploy crawler-specific rules for the agents identified.
- Contact the provider with the URLs and your requested remedy; ask what material was collected and whether future collection is excluded.
- Escalate to your institution, publisher, funder, or counsel when contractual, privacy, or intellectual-property interests are involved.
An opt-out is generally prospective. Anthropic describes restricting ClaudeBot as signaling that future materials should be excluded from its training datasets; that statement does not promise removal of material collected previously.
Legal and technical limits you should state accurately
Rights reservations, text-and-data-mining opt-outs, contract terms, and crawler instructions do not have one worldwide legal effect. The applicable result depends on jurisdiction, ownership, licences, access conditions, contractual language, and the facts of the collection. The OECD’s 2025 paper, Intellectual property issues in artificial intelligence trained on scraped data, describes web scraping as a major way training data is obtained while examining differing legal and regulatory responses. It does not establish a single global rule.
IOP Publishing’s Text and Data Mining Policy illustrates how a publisher can restrict scraping, extraction, and use of publications to develop or improve commercial AI unless permission is granted. Such a policy may specify technical, operational, security, and access conditions. It governs the material covered by that policy; it is not automatically a rule for every website or dataset.
For your own work, identify the governing law and the contracts that actually apply. A notice can preserve a claim or communicate a preference, but it cannot override a licence, co-author’s rights, an access agreement, or a statutory exception.
A practical pre-publication checklist
- Classify: mark unpublished, confidential, personal, proprietary, licensed, and public components.
- Check authority: confirm journal, institution, employer, funder, ethics, and collaborator requirements.
- Check the tool: verify retention, training, human access, subprocessors, deletion, and rights language on the day of use.
- Minimize: redact identifiers and send only the smallest necessary excerpt where policy permits.
- Choose the environment: use an approved closed service for material that cannot be disclosed to a general-purpose provider.
- Reserve rights: publish a clear notice and accurate metadata on public pages and files.
- Configure crawlers: deploy current, agent-specific robots.txt rules for each hostname.
- Block when necessary: use authentication and network controls for work that must not be reachable.
- Monitor: review logs, feeds, APIs, CDN paths, and alternate hostnames.
- Document: retain the classification, approvals, settings, rules, and dates.
These layers reduce exposure without claiming more than they can deliver: service terms govern uploads, compliant-crawler instructions guide web collection, and authentication or firewall controls can actually deny access.
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