Detecting Synthetic Media
The technical and institutional approaches to identifying AI-generated content.
Detection Approaches
Detection of AI-generated content uses several approaches. Forensic analysis examines artifacts — inconsistent lighting, unusual blurring, irregular skin textures, or unnatural eye reflections in images. AI classifiers are trained to distinguish real from synthetic content by learning subtle statistical patterns that generators leave behind. Metadata analysis checks for signs of editing or generation in file data.
However, detection faces a fundamental arms race problem: as detectors improve, generators adapt. Current AI text detectors have high false-positive rates (incorrectly flagging human writing as AI-generated), which has already caused harm — students falsely accused of cheating, writers falsely flagged as bots. No detection method is reliable enough for high-stakes decisions.