Meta's internal documents revealed that the company knowingly earned approximately 10% of its revenue ($7 billion annually) from fraudulent advertisements and scams while deliberately limiting enforcement efforts to protect profits.
Internal Meta documents from 2021-2025 revealed that the company's platforms (Facebook, Instagram, WhatsApp) were exposing users to approximately 15 billion fraudulent advertisements daily, generating $7 billion annually in revenue for Meta. The company's automated systems flagged these advertisers as suspicious but instead of removing them, Meta charged them higher rates as 'penalty bids.' Meta's own research showed their platforms facilitated one-third of all US scams and 54% of UK payment-related scam losses. The company estimated it would face maximum regulatory fines of $1 billion while earning $7 billion from fraud, making the business model profitable. Meta imposed revenue guardrails limiting anti-fraud teams to actions that would reduce ad revenue by only 0.15% ($135 million). High-value fraudulent accounts could accumulate over 500 policy violations before being removed. Specific cases included a Canadian Air Force recruiter whose hacked account was used to defraud colleagues of CAD $40,000, with Meta ignoring hundreds of user reports. The company's safety teams were receiving 100,000 valid fraud reports weekly but were ignoring 96% of them. Meta also acknowledged that users who clicked on scam ads were automatically targeted with more scams through their ad-personalization system.
Domain classification, causal taxonomy, severity scores, and national security assessments were LLM-classified and may contain errors.
Using AI systems to gain a personal advantage over others such as through cheating, fraud, scams, blackmail or targeted manipulation of beliefs or behavior. Examples include AI-facilitated plagiarism for research or education, impersonating a trusted or fake individual for illegitimate financial benefit, or creating humiliating or sexual imagery.
AI system
Due to a decision or action made by an AI system
Intentional
Due to an expected outcome from pursuing a goal
Post-deployment
Occurring after the AI model has been trained and deployed