Control
AI-generated consumer reviews or testimonials are published as if written by real customers who used the product
A feature that generates review or testimonial text with a model never publishes it as a consumer review or testimonial of a person who does not exist, did not use the product, or did not have the experience it describes; generated text is only a draft that a real, linked customer edits and submits, or it is published as clearly AI-generated content that is not presented as a consumer's review.
Informational data, not legal advice. Summaries and rules have not been reviewed by a lawyer: always verify official law text for decisions. A suggested guard is intended to address each rule; adding it is not a statement of compliance to that law.
Reach
Law in force in United States (federal) (US).
Trust and provenance
How far the rules this guard addresses have been checked. Each rule links to its provision, with its citation, official text and its own panel.
- This control
- Audit-grade: meets all 3 checks of the TwinEthos audit standard that apply to it.
- Lanes
- Binding law — in force 1
- Verification
- Sources last verified 4 Oct 2026; each provision states how.
- Data release
- Data release 2026.10.05, data as of 4 Oct 2026, schema 0.3.10.
- Legal review
- None of the 1 rule has been reviewed by a lawyer; no TwinEthos rule has been legally reviewed yet. Treat each as research to check against the official text; it is not legal advice. Open questions for counsel on them: 1.
- Audit standard
- 1 of 1 rule audit-grade. The audit standard is TwinEthos's own quality bar for provenance, dates, applicability, detectors, fixtures, remediation and licences; it is not a legal review.
- Detectors
- 1 detector, all experimental: written from the rule's text and not yet measured for precision on real code, so treat a hit as a lead to verify. Each provision lists its detectors' known limits.
The guard to add
Never publish model-written reviews or testimonials as a customer's; let a linked customer edit and submit any AI draft.
In review and testimonial features, model output is a draft returned to the signed-in customer (review_draft), and only that customer's submit action creates the review, with author_id and, where available, order_id or a verified-purchase flag. Remove any seeding, persona or marketing job that writes generated reviews or testimonials into the review store or posts them to third-party sites; AI summaries of real reviews are labelled as summaries, never shown as a review.
Where it goes: 1 application source code, 2 data models, 9 AI output handling, 14 user-facing text.
What reviewers look for: no code path from a model call to a review or testimonial insert or post without a real author id from the session; AI-written text stored as a draft; review summaries labelled; no persona or faker names attached to generated reviews.
Example (Python + OpenAI SDK), before:
text = client.chat.completions.create(model=M, messages=[{'role': 'user', 'content': f'Write a 5-star review of {p.name}'}]).choices[0].message.content
db.reviews.insert_one({'author': fake.name(), 'rating': 5, 'text': text})After:
draft = client.chat.completions.create(model=M, messages=help_me_write(customer_notes)).choices[0].message.content
return {'review_draft': draft} # the signed-in customer edits and submits it
def submit_review(user, order, text, rating):
db.reviews.insert_one({'author_id': user.id, 'order_id': order.id, 'verified_purchase': True, 'text': text, 'rating': rating})Engineering guidance, not legal advice. Each provision below may add its own details (a cadence, a deadline, a required notice element): open it for those.
Every rule this guard addresses
Binding law — in force (1)
- United States (federal) (US)
- Do not publish AI-generated reviews or testimonials that misrepresent that the reviewer exists or used the product (16 CFR 465.2) 16 CFR 465.2(a) · AI-adjacent law
Informational data, not legal advice. Summaries are TwinEthos's own words and rules have not been reviewed by a lawyer: check the official text before relying on any of it. A guard addresses an item; adding it is not a statement that your code meets any law.