Deep fake (also spelled deepfake) is a type of artificial intelligence used to create convincing image, audio and video hoaxes. The term, which describes both the technology and the resulting bogus content, is a portmanteau of deep learning and fake.
Deep fake content is created by using two competing AI algorithms — one is called the generator and the other is called the discriminator. The generator, which creates the phoney multimedia content, asks the discriminator to determine whether the content is real or artificial.
Together, the generator and discriminator form something called a generative adversarial network (GAN). Each time the discriminator accurately identifies a content as being fabricated, it provides the generator with valuable information about how to improve the next deep fake.
The first step in establishing a GAN is to identify the desired output and create a training dataset for the generator. Once the generator begins creating an acceptable level of output, video clips can be fed to the discriminator.
As the generator gets better at creating fake video clips, the discriminator gets better at spotting them. Conversely, as the discriminator gets better at spotting fake video, the generator gets better at creating them.
Until recently, video content has been more difficult to alter in any substantial way. Because deepfakes are created through AI, however, they don’t require the considerable skill that it would take to create a realistic video otherwise. Unfortunately, this means that just about anyone can create a deepfake to promote their chosen agenda. One danger is that people will take such videos at face value; another is that people will stop trusting in the validity of any video content at all.
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