Contact

Reaching the editorial and technical teams behind this reference property follows a structured process. This page outlines what information to include in an inquiry, how long responses typically take, what alternative channels exist, and where correspondence should be directed. Queries that arrive with sufficient context receive faster, more specific responses.

What to include in your message

The quality of a response depends directly on the specificity of the inquiry. Poorly scoped messages — those that do not identify the subject matter, the nature of the request, or the relevant publication — create unnecessary back-and-forth and delay resolution.

A well-formed inquiry to an intelligent systems reference property should include the following elements:

1. Subject area — Identify the specific domain: machine learning, natural language processing, computer vision, autonomous decision-making, regulatory compliance, or a named standard such as NIST AI 100-1 or IEEE standards for autonomous systems.
2. Page or section reference — Cite the specific page title or URL path where an issue, error, or question originates. For example, a question about ethics and bias in intelligent systems is more actionable than a general inquiry about "AI fairness."
3. Nature of the request — Distinguish between the following categories:
4. Factual correction — A named source contradicts a claim on a published page.
5. Content gap — A topic, standard, or named regulatory body is absent from coverage where it is materially relevant.
6. Technical error — A link, code sample, or structural element on the page is broken or misdirected.
7. Licensing or republication — A request to reproduce or reference published content.
8. Source citation — If the inquiry involves a factual dispute, include the name of the authoritative public source at issue — for example, a specific NIST publication, an FDA Software as a Medical Device regulation under 21 CFR Part 820, or a Federal Trade Commission statutory reference under 15 U.S.C. § 45.

Inquiries that omit the page reference and the nature of the request are deprioritized in the response queue.

Response expectations

Not all inquiries receive the same response timeline. The following classification boundaries govern how correspondence is handled:

Factual corrections tied to a named public source receive priority handling. When a specific standard body, federal agency, or published framework is cited as the basis for a correction, the editorial process can verify and act on the claim directly. Responses to documented factual corrections typically occur within 5 business days.

Content gap requests are evaluated against the existing publication roadmap. Coverage decisions for this property span more than 40 topic areas — ranging from types of intelligent systems to regulatory landscape for intelligent systems in the US — and additions are prioritized by demonstrated relevance to named standards, regulatory requirements, or established research frontiers. Content gap responses may take up to 15 business days.

Technical errors (broken links, malformed structures) are addressed on a rolling basis. Reporting a specific URL and the nature of the error accelerates resolution.

Republication and licensing inquiries are handled separately from editorial correspondence. These require identification of the requesting organization, the specific content at issue, and the intended use case.

Automated or mass-generated inquiries receive no response.

Additional contact options

For structured reference material relevant to specific intelligent systems topics, the published pages on this property cover discrete subject areas including intelligent systems standards and frameworks, accountability frameworks for intelligent systems, and privacy and data governance for intelligent systems. Consulting the published reference content before submitting an inquiry resolves the majority of factual questions.

For regulatory source verification, the following named public repositories are the primary reference points for intelligent systems governance in the United States:

• NIST AI Resource Center — airc.nist.gov — Houses NIST AI 100-1 (the AI Risk Management Framework) and related technical guidance.
• FTC AI guidance — ftc.gov — Federal Trade Commission enforcement positions on automated decision systems under 15 U.S.C. § 45.
• FDA SaMD guidance — ecfr.gov, 21 CFR Part 820 — Quality system regulations applicable to AI-based medical device software.

Inquiries that can be resolved by consulting these primary sources directly should be directed there rather than to editorial correspondence channels.

How to reach this office

Correspondence is accepted through the contact form embedded on this page. The form routes to the editorial team responsible for content accuracy, factual sourcing, and structural integrity across all published pages on this property.

When submitting via the contact form, use the subject line to identify the request type from the 4 categories verified above — factual correction, content gap, technical error, or licensing. This classification determines queue routing and response priority.

Postal and telephone correspondence are not available for this property. All substantive communication is handled in writing through the digital channel to ensure a complete, reviewable record of each exchange. Responses are sent to the email address provided in the form submission — generic or role-based addresses (such as noreply@ or donotreply@) cannot receive replies and should not be used for contact.

References

• 15 U.S.C. § 45
• FDA Software as a Medical Device regulation under 21 CFR Part 820
• NIST AI 100-1
• ftc.gov