Setting AI Content Rules for Members: Disclosure, Moderation and Trust

A member pastes a long, polished answer into your forum. It is tidy, confident and a little generic. Another member replies, “This reads like it came from a chatbot.” Within an hour the thread is about the answer’s origin instead of its content, and the moderator who gets the report has no rule to point to.

That moment arrives in every community that allows open posting. If you have not decided where you stand on AI-generated content, your moderators will decide case by case, and members will read those decisions as favouritism. This guide helps you write the rule first: what to ask members to disclose, how to word it, how moderators should handle reports, and how to keep trust intact while you do it.

It is a policy guide, not a tools list. If you want the other side of the topic, adding AI features to your own community, read How to Add AI Features to Your BuddyPress Community with Reign Theme. This article is about the content your members bring with them.

Why you need a rule before you need a ruling

Most communities start with no position on AI content, and that is a position of its own. Silence reads as “anything goes” to some members and “nobody is checking” to others. Both groups behave accordingly.

A written rule does three jobs:

• It tells members what you expect before they post, so you are not punishing behaviour nobody explained.
• It gives moderators something to cite, which makes their decisions repeatable and easier to defend.
• It shows your members that the space has an owner who pays attention, which is much of why people stay.

There is also a plain trust argument. People join a community to hear from other people: what they tried, what went wrong, what they would do again. Text that looks personal but was produced without lived experience weakens that exchange, even when every sentence in it is accurate. A rule lets you protect the exchange without banning a technology many of your members use every day.

This guide is about members who use AI openly and honestly. If your problem is low-quality AI spam and how to catch it, read Online Communities Fighting AI Content Slop instead. The two posts cover different problems.

Decide what you actually want to protect

Before drafting anything, answer one question: what does AI content put at risk in your community? The answer changes the rule. Here are the usual candidates.

What you want to protect	Typical worry	Rule that follows
First-hand experience	Answers that sound expert but were never lived	Disclose AI-drafted advice and add your own experience
Accuracy	Confident errors that members act on	Author is responsible for checking facts before posting
Conversation quality	Long, generic replies that end threads	Limit pasted generated text, ask for a short personal take
Member identity	Accounts that post only generated text	Rules on automation and accounts, not only on text
Search and reputation	Thin pages indexed under your name	Moderate low-effort content the same way you moderate spam
Fairness	Some members feel others are cheating on reputation or points	Same rule for everyone, applied in the open

Pick the top two or three. A rule that tries to protect everything becomes a rule nobody can enforce.

What counts as AI content

Your rule falls apart if “AI content” means something different to each reader. Define it in terms of what the member did, not which tool they used.

A workable split has three levels:

1. AI-generated: the member gave a prompt and posted most or all of the output.
2. AI-assisted: the member wrote the substance and used a tool to edit, restructure or polish it.
3. AI-free: the member wrote it, with at most a spell checker.

Most rules only need to ask for disclosure at level one. Asking members to confess every grammar suggestion creates noise and punishes people who need the help most.

Edge cases to settle in advance

These come up within the first few weeks. Decide them now and write the answer into your guidelines.

• Translation. A member writes in their first language and translates with a tool. This is usually welcome. Say so, so that non-native speakers do not feel watched.
• Grammar and spelling tools. Treat these like a spell checker. No disclosure needed.
• AI-generated images. Images are content too. Decide whether they need a label, and whether they are allowed in spaces where members share their own work, such as portfolios or product photos.
• Code and technical answers. A generated snippet that was never run can waste a reader’s afternoon. Many support communities ask for a note saying whether the code was tested.
• Summaries of other people’s posts. Useful, but a summary can drop context. Ask that it link to the original thread.
• Quoted output as an example. A member who pastes a model’s answer in order to critique it is not posting AI content in the sense your rule cares about. Allow it, clearly marked as a quote.
• Staff and moderators. If your own team uses AI for announcements or replies, the rule applies to them too, or members will notice the gap.

Choose your stance

There are four common stances. None is correct for every community; each fits a different purpose.

Stance	What it says	Works well for	Watch out for
Open	AI content is fine, no labelling needed	Casual or hobby communities	Quality drift, trust erosion over time
Disclose	AI-generated text is allowed if labelled	Most general communities	Relies on honesty, needs a clear label format
Restrict	Allowed in some spaces, banned in others	Communities with mixed purposes	Members must learn per-space rules
Prohibit	No AI-generated posts	Expert Q&A, peer support, professional networks	Hard to verify, risk of false accusations

For most owners the disclose stance is the best starting point. It is honest about reality, it asks for very little effort, and it can be tightened later. Restrict is a natural next step if one area, such as a health support space or a technical Q&A, needs stricter handling than the rest. Pair stances with spaces: a general chat space can be open while an expert answers space requires first-hand experience.

If you are still deciding how open the whole community should be, Private vs Public Community: How to Decide walks through that choice, and it affects how much AI content you will see in the first place.

Writing the rule

A good rule is short, specific and written in the voice your community already uses. Avoid legal language. Members will read it once, at sign-up, and again when they think they are being treated unfairly.

What to include

• What you expect. One or two sentences, in plain words.
• What disclosure looks like. Show the exact label members should use.
• What is exempt. Spell check, grammar tools and translation, if you allow them.
• What happens if the rule is broken. Point to your enforcement steps.
• Where to ask. A contact or space for questions, so members check before posting.

Sample wording you can adapt

Copy this, then change it until it sounds like you.

Using AI tools in this community

We want to hear from people. You are welcome to use AI tools to help you write, but the post is yours and you are responsible for it.

If a tool wrote most of your post, start it with “AI-assisted:” so readers know. You do not need to label spell checking, grammar suggestions or translation of your own words.

Do not post advice as if you tried it yourself when you did not. Check facts, links and code before you share them. If you are not sure something is right, say so.

Moderators may ask you to add a label, rewrite a post in your own words, or remove it. Repeated or deliberate rule breaking leads to the steps in our community guidelines.

Questions about this rule? Ask in the Community Help space.

Notice what the sample does not do. It does not claim detection, it does not threaten, and it does not assume bad faith. It states a norm and a consequence.

Once the wording is settled, it slots into your wider guidelines as one more section. The community guidelines template shows where it sits next to your rules on conduct, spam and privacy.

A stricter version for expert spaces

If a space exists to share lived experience, add a tighter line to that space’s description:

Posts in this space must describe your own experience. AI-generated answers are not allowed here, even with a label. Use the General space for those.

Putting the strict rule where it matters, rather than across the whole community, keeps the overall tone welcoming.

Labelling options

Disclosure only works if members can do it easily and readers can see it quickly. You have three practical choices.

1. A prefix in the post. Members type “AI-assisted:” at the start of the post. It costs nothing and works on every platform. The weakness is that it depends on members remembering.
2. A tag or topic label. If your forum or feed supports tags, create one called “ai-assisted” and ask members to add it. Readers can filter by it, and moderators can find every labelled post at once.
3. A moderator-applied marker. When a moderator confirms AI-generated content, they add the label or a note themselves. This is slower, but it works when members forget.

Whichever you choose, keep the wording identical everywhere. A label that reads “AI-assisted” in one space and “generated by AI” in another teaches members that the rule is optional.

How moderators should handle a report

The most important thing to give moderators is a process. Without one, every report becomes an argument about whether a post “sounds like AI.” Nobody can answer that reliably.

Do not rely on guesswork

Reading style is a weak signal. Plain, careful writing from a non-native speaker can look “machine-like” to a suspicious reader, and generated text can be edited to look casual. Accusing a member based on tone alone damages trust faster than the original post did. Treat style as a reason to look closer, not as proof.

Better signals are behavioural: a burst of long replies in a few minutes, the same structure in every answer, advice that does not match the question that was asked, links that do not exist, or a member who cannot discuss their own post when asked a follow-up.

A decision path for moderators

Give your team these steps, in order.

1. Check the rule. Does the post break a written rule, regardless of how it was made? Spam, off-topic content, harassment and misinformation are already against your guidelines. If so, handle it under that rule and skip the question of authorship.
2. Look at the content, not the author. Is it accurate, relevant and useful? A helpful AI-assisted answer with a missing label is a different problem from a wrong, generic answer posted ten times.
3. Ask, do not accuse. Send a private message: “This post looks AI-generated. If it was, please add the label. If not, tell us and we will close the report.” Give the member a fair chance to respond.
4. Decide the outcome. Label added, post edited, post removed, or report dismissed.
5. Record the decision. Write down the reason in your moderation log or notes, so the next moderator treats the same case the same way.
6. Close the loop. If the report came from a member, tell them it was reviewed. Do not share details about the other member.

What moderators should avoid

• Calling a member a liar in public.
• Using an AI detector as the only evidence. Such tools make mistakes in both directions, and a result should never be the sole reason to remove a post or penalise a member.
• Treating non-native English as a signal.
• Applying the rule harder to new members than to long-standing ones.

Enforcement ladder

A proportionate response is fairer and easier to defend. Here is a ladder you can adapt. Keep the steps and change the thresholds to match your community.

Step	Trigger	Action
1. Nudge	First unlabelled AI post, honest mistake	Friendly message, ask to add the label
2. Edit or remove	Post breaks the rule or is low quality	Edit with the member’s consent, or remove with a reason
3. Formal warning	Repeat after a nudge	Recorded warning that cites the rule
4. Temporary restriction	Continued breaches	Short posting suspension, with a way to appeal
5. Removal from the community	Deliberate, repeated deception, or automated posting at volume	Account ban, recorded with reasons

Two principles keep this fair. First, the member always learns which rule they broke. Second, anything that restricts a member can be appealed to someone other than the person who made the call.

Automated posting is a separate case. A member who runs a script that floods your community is not making a content choice; they are abusing the space, and your normal spam and rate-limit rules apply.

Setting it up on Reign, Jetonomy and BuddyNext

A rule is only as good as the tools your moderators have to carry it out. Reign gives you the theme layer, and Jetonomy and BuddyNext supply the community features. Both have a free version, which you get from the Wbcom store, and a Pro version. The sections below describe what each does today for this job.

One point first, to avoid confusion: neither plugin detects whether a member’s text was written by an AI, and this guide does not suggest otherwise. The tools help you collect reports, review them, record decisions and apply consequences. Judging authorship stays with people.

Jetonomy for forums and Q&A

Jetonomy covers forums and Q&A. The free version includes the pieces a disclosure rule leans on:

• Member reports. Any logged-in member can flag a topic or reply, and the report carries a reason. The built-in reasons are spam, offensive, off-topic, harassment and other. There is no dedicated AI reason, so ask members to choose “other” and add a note, or choose the closest match.
• A moderation queue. Flagged and pending content lands in a queue that moderators work through.
• Space moderators. Each space can have its own moderators, separate from site administrators. That matters if you run a strict expert space and a relaxed general one, because each can have its own person watching it.
• Trust levels. New members start with limited posting and earn more freedom as they take part. This is a useful brake on accounts that post a lot of low-effort text on day one.
• Bans and silences. A moderator can silence a member, which blocks posting, or ban them.
• A record of changes. An activity log shows who changed what, which helps with step five of the moderator path.
• Akismet. Spam checking through Akismet is wired in.

Jetonomy Pro, the paid licence, adds an Advanced Auto-Moderation extension with keyword filters, rate limits and user score gates, which can hold posts for review. It also adds an AI Assistant that offers AI-powered moderation and spam detection using the provider you choose. That is moderation of spam and abuse, not a test for AI authorship. If you turn it on, say so in your policy, because it is one more case where AI is part of how your community runs.

BuddyNext for the social layer

BuddyNext covers the activity feed, spaces, profiles and messaging. Its free version includes the pieces the enforcement steps need:

• Reports with a fixed list of reasons. Members can report a post, comment, direct message or profile. Reasons include spam, harassment or hate speech, misinformation, inappropriate content, fake account, impersonation and “something else,” with a notes field for details. Misinformation and fake account are the closest fits for the worst AI-related problems.
• A report queue. Moderators can work through open reports in wp-admin or on the front end.
• Warnings, strikes and suspensions. These map directly onto the ladder above, with a reason recorded for each, and strikes can escalate automatically at thresholds you set.
• Appeals. A suspended member can appeal, which covers the fairness requirement in the enforcement ladder.
• Content warnings. A moderator can apply a content warning that blurs a post until the reader chooses to view it. It is built for categories such as spoilers or sensitive content, so use it with care, but it shows the model of a visible marker on a post.
• Content safeguards. Banned words, blocked links and rate limits run on every post.

BuddyNext Pro, the paid licence, adds rule-based auto-moderation and an AI-assisted review of the report queue on a schedule, using a provider you connect. It works as a helper for your moderators. A person still decides the outcome.

To compare editions before you commit, see the Free vs Pro breakdown. If you are still choosing between a forum and a feed, the forum picker helps you narrow it down.

What to configure on day one

• Publish your AI rule as a pinned page or space description, and link it from your registration and community guidelines pages.
• Create the label or tag you chose, so members can find and use it.
• Give each space the moderators who know its purpose.
• Write the enforcement ladder into your internal moderator notes, with the reasons you will use for each step.
• Decide in advance who handles appeals.

Keeping trust while you enforce

The rule itself matters less than how it feels to be on the receiving end. A few habits protect trust.

• Explain the why. Members accept a rule when they understand the purpose. A short note about protecting first-hand experience goes further than a list of prohibitions.
• Be consistent. The same action for the same behaviour, whoever the member is.
• Be visible about your own use. If your team uses AI for drafting announcements or summaries, say so. It is hard to ask for disclosure from others while hiding your own.
• Give feedback when you remove something. Silence feels like censorship. A two-line reason does not.
• Protect members who get it wrong in good faith. The first violation is a conversation, not a punishment.
• Do not publicly shame. Handle it in private, then update the rule if the case showed a gap.

Moderation is also an opportunity to learn. When two or three members ask the same question about the rule, the rule is unclear. Fix the wording and tell everyone what changed.

If members publish longer posts on your site rather than short replies, the same principles apply with a review step in front. How to Let Members Publish Blog Posts on Your WordPress Site covers roles and review queues for that situation.

Reviewing the rule over time

AI tools change quickly, and so will how your members use them. A rule written once and never revisited will drift out of step with the community.

Put a review on the calendar, for example every six months, and use real evidence:

1. Read the moderation record. Which reports mention AI content? Which were dismissed, and why?
2. Count the repeat questions. If members keep asking whether translation is allowed, the wording needs work.
3. Check for false accusations. Any case where a moderator was wrong is a sign the process needs tightening.
4. Ask members. A short poll or a thread in your feedback space shows whether the rule feels fair.
5. Revisit the stance. A community that started open may want to move to disclose; one that started strict may find the ban unenforceable and soften it.
6. Announce changes. Post what changed and the reason, and keep the older version in a changelog so members can see the history.

Track the effect on the community, not just the number of reports. Community Metrics: What to Track Beyond Member Count is a good starting point for deciding which signals show whether trust is holding.

A short checklist

• [ ] You know what you are protecting (experience, accuracy, conversation quality).
• [ ] “AI content” is defined by what the member did.
• [ ] Edge cases are settled: translation, grammar tools, images, code.
• [ ] You picked a stance, and any per-space exceptions are named.
• [ ] The rule is short, uses your voice and includes a sample label.
• [ ] Moderators have a decision path that does not rely on guessing.
• [ ] The enforcement ladder is written down, with an appeal route.
• [ ] Your own team follows the same rule.
• [ ] A review date is on the calendar.

For the broader picture of structure, roles and onboarding, the guide to building an online community places this policy in context, and What Is Reign? explains the theme these community tools run on.

Frequently asked questions

Should members have to disclose AI-generated content?

For most communities, yes, when a tool wrote most of the post. It costs the member a few seconds and tells readers how much weight to give the content. Skip disclosure for spell checking, grammar suggestions and translation of the member’s own words, so the rule does not burden people who use these tools to take part.

Can I detect AI-written posts automatically?

Not reliably. Detection tools give wrong answers in both directions, and style is a poor guide. Jetonomy and BuddyNext include reporting, queues and, in their Pro editions, AI-assisted moderation for spam and abuse, but neither claims to prove that a post was written by an AI. Use behaviour and the member’s own answers, not a score, as the basis for any decision.

Should I ban AI content completely?

Only if your community’s purpose depends on first-hand human experience, such as peer support or expert Q&A. A total ban is hard to enforce and invites false accusations. A cheaper option is to ban it in specific spaces and allow it, with a label, elsewhere.

What should a moderator do when a member denies using AI?

Take the member at their word unless there is a clear breach of another rule. Judge the post on its quality and accuracy. If it is wrong, generic or off-topic, handle it under those rules without a ruling on how it was written. Record the outcome and move on.

Do these rules apply to staff and moderators?

Yes. If your team uses AI to draft announcements, replies or summaries, follow the same labelling rule. Members trust a rule more when the people enforcing it follow it too.

Do I need legal advice about AI disclosure?

Rules about AI-generated content and disclosure differ by country and region, and they keep changing. Check your local rules, and if you collect personal data or serve members in several regions, ask a qualified adviser. This guide covers community policy, not legal compliance.