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Make AI-assisted text more inclusive by reviewing it as an editor, not by trusting the model or a readability score. Check whether it is accurate and complete, clear for its intended readers, respectful in how it describes people, and accessible in its structure and format. Then get a suitable human review before publication. This checklist helps you find problems; it cannot guarantee that every reader will find the text inclusive or accessible.
What does an inclusive review of AI text involve?
It is a human review of both what the text says and how readers can use it. The editor checks that the draft answers the real question, represents people respectfully, communicates clearly, and works for readers using different access needs. That means reviewing the source facts, the omissions, the language, and the published format—not just correcting grammar.
AI-generated text can sound certain while being inaccurate or incomplete. The NYC Digital Design System’s web content style guide warns that generative AI often produces misleading or inaccurate content and recommends human review for accuracy, missing information, plain language, reading level, and style rules. Its advice is written for New York City government content, so use your own organization’s rules for approval and disclosure.
Think of the review as a sequence: establish the reader and purpose, verify the content, improve clarity, examine representation, check accessibility, and assign final approval. If a later check reveals a substantive problem, return to the earlier one; for example, a missing exception is an accuracy and completeness issue, not merely a wording issue.
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How should I set up the review?
Before editing sentences, identify the intended reader, the action or understanding the text should support, and the rules that govern the publication. Without that context, “simpler” or “more inclusive” can become vague goals that lead to deleting necessary information or choosing terminology that does not fit the audience.
Clarify purpose and audience
- Write down who the content is for and what readers should be able to understand or do after reading it.
- Check whether the draft answers the reader’s actual question, rather than merely producing plausible-sounding background.
- Identify the knowledge readers can reasonably be expected to have. Explain terms or steps they need, but do not talk down to expert readers or remove distinctions that matter.
- Consider whether the content will be read on a web page, in a document, or in another format. The format affects how people navigate it and what alternatives they need.
Check the policy before sharing material
Find the rules that apply to the particular organization and use case. They may govern approved AI tools, sensitive information, required human review, and whether AI assistance must be disclosed. The NYC guide offers advice for its own government context; it is not a universal disclosure rule. Do not paste private or sensitive source material into a tool unless the applicable privacy and tool-use rules allow it.
Set a clear review boundary as well: the model may help produce a draft, but the publisher remains responsible for the wording and the decision to publish. Record who is responsible for checking specialist claims and who has authority to approve the final version.
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Compare the draft with trusted source material before polishing its style. Treat every concrete claim and instruction as something to verify, and look for missing information as carefully as you look for false statements.
Verify claims against authoritative sources
- Check names, dates, numbers, links, definitions, eligibility rules, and instructions against primary sources wherever possible.
- Open links and confirm that they lead to the page the text describes. A plausible URL or a confident explanation is not proof that either is correct.
- For a process, follow the steps against the authoritative instructions. Confirm that prerequisites, exceptions, and decision points have not disappeared from the AI draft.
- Separate sourced facts from interpretation or recommendation. Make sure the wording does not present an inference as an established rule.
Look for what is absent
AI output may omit an exception, an important group of readers, or a condition that changes what someone should do. Compare the output with the source material and ask whether it has preserved the information needed to make a decision. If you cannot verify a claim or find the source for it, remove it, qualify it, or hold the draft for a subject-matter review rather than leaving it as fact.
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- Does the text cover the main case as well as relevant exceptions?
- Does it explain what readers need to do next, including any prerequisite or limitation?
- Does it make assumptions about a person’s situation, identity, knowledge, or access to a service?
- Does its confident tone go beyond what the evidence supports?
Accuracy is part of inclusion: readers cannot act fairly on information that is misleading, incomplete, or framed as certain when it is not. The NYC guide’s warning about misleading AI content is a practical reason to give this check its own place in the workflow.
How can I make the text clearer without oversimplifying it?
Make the main point easy to find, organize supporting details so readers can scan them, and use familiar words where they preserve the meaning. Plain language is an accessibility aid, but it does not mean removing necessary nuance, technical detail, or a reader’s ability to choose.
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- Give the page a descriptive title and lead with its answer, outcome, or required action.
- Use headings that describe the content below them. A reader scanning only the headings should be able to understand the page’s main structure.
- Keep paragraphs focused on one idea. Use a list for actual steps, choices, or grouped requirements when that structure makes the information easier to follow.
- Put conditions and exceptions near the instruction or claim they qualify, rather than burying them where a reader may miss them.
Choose words and sentence structures deliberately
Prefer common words and direct phrasing when they communicate the same thing. Define a technical term when readers need it, and spell out an acronym at first mention unless the audience is certain to know it. Short sentences can help, but a sentence should not be cut so aggressively that the relationship between a condition and its consequence becomes unclear.
The Province of British Columbia’s Plain language checklist, updated 24 April 2026, suggests sentences ideally no longer than 15–20 words and a Grade 8 reading level or lower. Treat these as that government’s editorial targets, not universal pass marks. Language, subject matter, and reader needs vary; legal, medical, technical, or safety-critical content may need terms and qualifications that a score cannot judge.
The W3C WAI tips for writing for web accessibility recommend simple language and formatting as appropriate for the context. A readability tool can help flag long or complicated passages, but it cannot determine whether a claim is correct, an explanation is complete, or a word is respectful in context. Use scores as prompts to inspect a passage, not as a substitute for editing or reader feedback.
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How do I check representation and inclusive language?
Review how people are described, which people appear in the text, and whether the wording treats groups consistently. Prefer neutral, relevant descriptions and do not assume that one label is right for everyone in a group.
Remove unnecessary labels and stereotypes
- Ask whether a person’s identity, condition, or demographic category is necessary to understand the point. If it is not, leave it out.
- Check for assumptions about ability, behavior, family roles, culture, or circumstances that the source material does not support.
- Look across examples and scenarios: who is shown as an expert, decision-maker, customer, or person needing help? Is anyone reduced to a stereotype or included only as an exception?
- Use factual descriptions rather than language that portrays people as helpless or defined by a condition.
The UK Government’s disability-language guidance, updated 17 June 2026, identifies phrases such as “suffers from” and “confined to a wheelchair” as wording to avoid because they can imply victimhood or discomfort. That does not mean editors should substitute a different label mechanically. Follow an individual’s known preference and relevant guidance for the community and context.
Ask whose language belongs in the text
Some terms are contested or change over time; the intended meaning and the preferences of the people described matter. The UK Government’s disability-language guidance is specific to writing about disability, not a universal terminology list. For community-specific material, check appropriate guidance and involve people with relevant expertise rather than asking an AI system to settle a naming question.
The Australian Government Style Manual’s guidance on making writing accessible and inclusive notes that its examples were based on guidance developed by relevant community subject-matter experts. That is a useful model for sensitive topics: terminology decisions benefit from knowledge of the community, not just a general-purpose writing rule.
What should I check in the web page or document itself?
Accessibility depends on structure and format as well as sentence wording. Review the content as it will appear to readers, including the way someone can navigate it and understand information conveyed by images or other media.
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Check structure and non-text information
- Use real, meaningful headings and lists instead of relying on larger type, bold text, or visual spacing alone to signal structure.
- When an image, chart, audio clip, or video conveys information, provide an appropriate text alternative so readers can get the information another way.
- Do not use color as the only way to communicate a status, category, or instruction. Include another cue in the content or presentation.
- Review the published rendering, not only the source text. Confirm that headings, lists, links, and alternatives remain available in the format readers encounter.
The W3C’s Web Content Accessibility Guidelines 1.0 dates to 1999 and is useful here only as historical guidance for foundational ideas. Do not use it as today’s conformance baseline. The UK Government’s inclusive communication guidance, updated 17 June 2026, includes WCAG 2.2. For conformance decisions, use the current standard and the requirements that apply to your organization. WCAG 3.0 is a developing specification, not a settled replacement standard.
Keep editorial checks separate from conformance checks
A writing checklist can reveal a weak heading or missing text alternative, but passing an editorial review does not demonstrate that a page conforms to an accessibility standard. If the publication has formal accessibility obligations, follow the applicable technical and organizational process. Do not treat a readable draft or a favorable score as certification.
Who should review AI-assisted text before publication?
A suitable human editor should take responsibility for the final text, with subject-matter review where accuracy depends on specialist knowledge. For content about disability, identity, or a particular community, consider input from relevant experts or people with lived experience.
Match the reviewer to the risk
- For ordinary informational content, use an editor who understands the audience, the publication’s style, and the source material.
- For technical or consequential instructions, involve someone qualified to verify the subject-specific claims and exceptions.
- For community-specific terminology or representation, seek relevant community or subject-matter input when appropriate.
- Where your process calls for it, compensate external reviewers for their expertise and time.
Give reviewers a defined task. Ask them to check the claims, missing information, reader comprehension, and language within their expertise; do not ask one person to stand in for an entire community. Resolve disagreements by examining the evidence, the intended meaning, and the preferences of people described. Keep the publisher’s final approval with the person or team accountable for the content.
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Before approving a draft, use this sequence. A “yes” means the issue has been considered and resolved, not that a tool has certified the text.
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- Purpose: Is the intended audience clear, and does the text answer the question or support the action readers need?
- Policy: Have you followed the organization’s rules for AI tools, sensitive information, human review, and disclosure?
- Accuracy: Have names, dates, figures, links, claims, and instructions been checked against authoritative material?
- Completeness: Have you checked for unsupported assumptions, missing exceptions, and information readers need to act?
- Clarity: Does the text state its main point early, use descriptive structure, define necessary terms, and explain technical language?
- Representation: Are descriptions relevant and neutral, free of unsupported stereotypes, and consistent with known preferences and community guidance?
- Accessibility: Do the content structure and text alternatives support readers using the published format, without relying on color alone?
- Approval: Has an appropriate human editor—and, where needed, a subject-matter or community reviewer—checked the material, with a named person accountable for publication?
If an answer is no, revise the content or pause approval until the issue can be resolved. Keep the checklist proportionate: a low-risk informational update may need a straightforward editorial check, while sensitive or consequential material calls for reviewers with the relevant expertise.
Frequently Asked Questions
Can an AI detector tell me whether text is inclusive?
A detector’s classification of whether text was generated by AI does not establish whether its claims are true, its language is respectful, or its format is accessible. Review the actual content and its sources rather than treating authorship detection as an editorial verdict.
Should I disclose that I used AI to write something?
There is no single disclosure rule established for every publisher or use case. Check the policy that applies to your organization and content, including any requirements from the publication channel or governing context.
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Should I ask an AI model to choose the right identity term?
A model can suggest wording, but it cannot establish an individual’s preference or speak for a community. Verify terminology with the person, relevant community guidance, or an appropriate reviewer when the distinction matters.
Is WCAG 3.0 the standard I should use now?
The W3C WCAG 3.0 page describes a developing specification, so its draft material should not be treated as settled requirements. For a conformance decision, use the current standard and the rules that apply to your organization.
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