Application follows FTC AI guidance; no overpromising AI capabilities
Why it matters
The FTC's 2024 AI guidance specifically targets 'AI washing' — labeling products as AI-powered when they use simple rules or templates with no ML component. This is an FTC Act §5 deceptive claim that inflates perceived product value and misleads purchase decisions. Beyond AI washing, overpromising accuracy ('99% accurate') without disclosing error rates or limitations creates material risk when the AI fails — particularly in high-stakes domains (health, finance, legal) where reliance on an AI output without a professional disclaimer can cause direct consumer harm that the FTC treats as an unfair practice.
Severity rationale
Info because AI capability misrepresentation typically requires a consumer to purchase and rely on the product before discovering the gap between the claim and reality — harm is delayed and varies by use case — but 'AI washing' is an explicitly named FTC enforcement priority.
Remediation
Verify every 'AI-powered' marketing claim against the actual codebase, and add limitations disclosures to AI outputs in high-stakes domains.
function AIAnalysisResult({ result }: { result: AnalysisResult }) {
return (
<div>
<div className="result-content">{result.output}</div>
{/* Limitations disclosure — required for high-stakes domains */}
<p className="text-xs text-gray-500 mt-3 border-t pt-3">
This analysis was generated by AI and may contain errors.
Review all outputs before acting on them.
{result.domain === 'legal' &&
' Not legal advice. Consult a qualified attorney.'}
{result.domain === 'medical' &&
' Not medical advice. Consult a healthcare professional.'}
{result.domain === 'financial' &&
' Not financial advice. Consult a licensed advisor.'}
</p>
</div>
)
}
For 'AI-powered' claims: grep for LLM API calls or ML model loading in the code path backing the claimed feature. If none exist, the claim must be corrected: 'smart filtering,' 'automated,' or 'intelligent' are acceptable without implying ML where none exists.
DetectionPro
The detection method for this pattern is part of AuditBuffet Pro.
The full method (what to look for, pass and fail conditions, and how results get reported) ships inside the FTC Consumer Protection Audit. The pattern definition, severity rationale, and remediation remain openly licensed under CC-BY-4.0.
External references
- external · ftc-ai-guidance-2024 — FTC Guidance: Keep Your AI Claims in Check (2023)
- external · ftc-act-section-5 — FTC Act Section 5 — Unfair or Deceptive Acts or Practices
Taxons
History
- 2026-04-18·v1.0.0·Initial import from ftc-consumer-protection·automated