What is Deepfake Detection?
TL;DR
Technology for spotting AI-synthesized or altered faces and voices. AI analyzes unnatural blinking, lighting inconsistencies, and generation artifacts to flag fake videos and impersonation.
Deepfake Detection: Definition & Explanation
Deepfake detection is technology for identifying AI-synthesized or altered face images, videos, and audio. Generated footage can leave subtle traces invisible to the human eye, and detection AI analyzes the frequency of unnatural blinking, inconsistencies in skin texture and light reflection, wobble in facial contours, and generation-specific patterns in the frequency domain to judge authenticity. As deepfake misuse—impersonation fraud, disinformation, non-consensual sexual imagery—has become a social problem, detection technology has grown in importance for social platforms, news organizations, and financial-institution identity verification (eKYC). Alongside it, 'authenticity proof' approaches are advancing, such as embedding provenance at generation time via digital watermarks and content provenance standards (like C2PA). However, generation and detection are locked in a cat-and-mouse race, and detection is not foolproof. Beyond technical measures, the literacy to not take shocking footage of unknown origin at face value is essential.