Deepfake videos leverage advanced artificial intelligence to manipulate or generate realistic media, often depicting individuals saying or doing things they...
A deepfake video uses artificial intelligence, particularly deep learning, to create highly realistic but fabricated media, often swapping faces or synthesizing speech to make it appear as if someone said or did something they didn't.
Deepfakes are typically created using generative adversarial networks (GANs) or autoencoders. These AI models are trained on vast datasets of real images and videos to learn a person's features, then generate new, manipulated content.
Primary concerns include the spread of misinformation, reputational damage to individuals, fraud, blackmail, and potential interference in elections. They erode trust in digital media and can have serious legal implications.
While challenging, researchers are developing AI-powered detection tools that look for subtle inconsistencies, artifacts, or anomalies not present in genuine videos. Human verification and critical analysis are also crucial.
Various countries and regions are enacting laws to address deepfakes, especially concerning non-consensual pornography, defamation, and election interference. However, legislation is still rapidly evolving to keep pace with the technology.