Proof of Humanity in the Age of LLMs and Synthetic Content

Excluded from normalized aggregate trends after staff review: 3056 posts were attributed to March 2026; 671 shared March 14, 2026. The preceding six-month median was 13.5 posts.

Review evidence: 3,056 posts in March 2026; 671 shared March 14, 2026; preceding six-month median 13.5. Reviewed August 9, 2026.

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Advances in large language models and generative AI have made synthetic text, images, audio, and video increasingly realistic, increasing risks such as phishing, account takeovers, financial crime, misinformation, bot attacks, and deepfake impersonation. As conventional CAPTCHAs become easier for AI to defeat, organizations need stronger proof-of-humanity measures based on biometrics, liveness detection, face matching, device intelligence, and behavioral analysis. Didit presents its AI-native identity verification platform as a response to these threats, offering passive liveness checks that analyze subtle biometric signals, active checks requiring user actions, and 1:1 face matching against identity documents. Its broader tools include document data validation through OCR, MRZ and barcode processing, as well as NFC verification for ePassports and electronic IDs. The platform is designed to let businesses build verification workflows suited to their risk and regulatory needs, while continuously adapting its AI models to emerging forms of synthetic fraud.

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