Deepfake phenomenon shows the development of AI in nowadays, specifically, those aspects related to deep learning evolution. Deepfake is defined as audio, image or video manipulation made through deep learning techniques in order to create a content very similar to original ones, making difficult to distinguish the ‘real’ content from that which is ‘fake’. The most used tools for getting that results are face-swapping, puppeteering, Lip-Sync and voice cloning, among others. Deepfake is currently used for different objectives, especially in those fields related to accessibility, educational areas or cinema industry, bringing users more tools to make their experience easier than it used to be. Moreover, deepfake evolution has affected forensic field through design of new tools focused on improving ways of studying crime scenes and, therefore, establishing more solid conclusions. However, despite of the benefits caused by this Artificial Intelligence branch, its use could also suppose a threat in personal, social and economic terms. Indeed, criminal phenomena such as CEO Fraud or porn-revenges take a more dangerous nature than they used to have because this technology enables criminals to make video or audio files where people (famous or not) appear doing some actions or saying words that they have never said, supposing a damage in their right’s protection. What’s more, Deepfake is progressive involved in human trafficking related to sexual exploitation and porn content, supposing an important source for obtaining more profits, usually, at women’s expense. It is worth to mention at this point its dangerousness has been increasing in recent years because of applications development that enables general public to elaborate this type of material without requiring any specific knowledge. For that reason, it is important to highlight the possible crime implications associated to Deepfake from a criminological view, including gender perspective in this analysis as well.
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