Scam ads and deepfakes on social media are eroding consumer trust and raising calls for stronger regulation and platform transparency. Scam ads and deepfakes research highlighted in WIRED features a survey showing that roughly half of U.S. adults under 55 and nearly two-thirds of those over 55 view government action against deepfake advertising as “very important.” Older users in particular report feeling heavily targeted by fraudulent offers, while respondents rank platforms like TikTok and Meta among the worst at preventing deepfake scam ads. Scam ads and deepfakes experts, including former Meta and Google staffers, argue that current ad transparency rules and data access for independent researchers are inadequate. Even with Europe’s Digital Services Act mandating more reporting from major platforms, academics and civil society groups still lack the granularity needed to compare fraud and scam prevalence across networks or to audit the effectiveness of detection systems. Platform-held data on impression counts, conversion funnels, and complaint handling remains opaque, making it difficult to benchmark performance or hold providers accountable. For regulators, privacy advocates, and trust-and-safety teams, scam ads and deepfakes represent a convergence of financial fraud, synthetic media, and platform governance failures. Without independent auditing and standardized metrics for scam and deepfake prevalence, claims about ad safety will continue to rely on self-reporting. Stronger disclosure rules, better researcher access to anonymized ad data, and cross-platform measurement frameworks are emerging as prerequisites for meaningful oversight.
🎯CORTEX Protocol Intelligence Assessment
Business Impact: Scam ads and deepfakes threaten not only individual consumers but also brand safety for legitimate advertisers whose campaigns appear alongside fraudulent content. Platforms that fail to control these threats risk regulatory penalties, loss of advertiser confidence, and pressure to accept external auditing of their ad ecosystems. Technical Context: Scam ads and deepfakes require a combination of content detection, behavioral analysis, and advertiser verification to mitigate. Detection pipelines must correlate creative assets, landing pages, and complaint data across campaigns and apply machine learning to flag deceptive patterns. Engineering teams should prepare for regulatory demands to expose standardized metrics and researcher APIs while maintaining user privacy.
⚡Strategic Intelligence Guidance
- Develop internal scam and deepfake ad metrics that track prevalence, takedown speed, and repeat offenders across campaigns.
- Strengthen advertiser verification and ongoing risk scoring, especially for financial, investment, and celebrity-linked promotions.
- Invest in creative-level analysis that combines image, audio, and text signals to identify synthetic or impersonation-based ad content.
- Prepare technical and governance frameworks for sharing anonymized ad data with trusted researchers under clear privacy and security controls.
Threats
Scam advertisingDeepfake ads
Targets
Online consumersSocial media platforms