Deepfake Detection: How to Spot AI Video

'Deepfake' technically refers to media where a generative model has swapped, synthesized, or altered a person's face or voice in video — but the term is now used loosely for any AI-generated or AI-manipulated footage. Both matter for the same reason: the footage shows something that didn't happen the way it appears to.

Unnatural blinking patterns (too little, or too regular) is one of the older, still-sometimes-useful tells. Look at the edges where a face meets hair, ears, or the background for blurring or flickering, and check whether lighting on the face actually matches the lighting in the rest of the scene. For audio-paired video, mismatched lip sync — especially on consonants — is often the most noticeable giveaway.

Rather than checking one still image, video detection analyzes the clip frame by frame for the visual inconsistencies above, plus artifacts that only show up across motion — flickering, temporal inconsistency in lighting, or unnatural micro-movement. Those per-frame signals get reduced into one overall verdict, which is what the AI Video Detector returns after analyzing an uploaded clip.

Check the source — who posted it first, and does their account have a track record. Look for the same footage from an independent source. Run it through a detector for a frame-level read rather than relying on a single freeze-frame check. And treat the result the same way as any other detector output: a confidence signal to act on carefully, not an unappealable verdict — especially before sharing or reporting on a clip further.