For years we looked for mistakes: deformed hands, impossible movements, meaningless text. Today those clues are disappearing. Recognizing a video generated by artificial intelligence can no longer depend only on the viewer’s eye.
Platforms are introducing labels, creator disclosures and automated detection systems. It is a necessary step, but not a simple one. AI may be involved in an entire video or only in one shot, one voice, one correction or one background element. A single label risks treating very different processes as if they were the same.
For image makers, transparency should not be understood as a confession. It can become part of the credits: which tools were used, at what stages and under what degree of human control. Disclosing the process makes it possible to evaluate the work more intelligently instead of reducing everything to the question ‘real or fake?’
The challenge is not only to identify what is artificial. It is to preserve trust in video as a language. That requires readable information, shared standards and a visual culture capable of distinguishing manipulation, experimentation and deception.