Deepfake digital face manipulation: A rapid literature review

Abstract

"Deepfake" refers to the complex processing of audiovisual content using generative adversarial networks (GANs) and other deep learning methods. It enables the smooth superimposition of one person's face or voice over another, producing remarkably lifelike fake films or images. However, the online distribution of the modified images could result in major moral, ethical, and legal issues if misused. This rapid literature review aimed to establish a clear perspective regarding deepfake digital face manipulation. The paper emphasized the potential risks of this technology while also discussing the benefits of looking into deepfakes. The study contributes to the field's understanding. It addresses the abuse of deepfake technology by offering insights into the most current advancements in identifying and creating manipulated facial images. Strict ethical standards and rules regulating its application must be developed to maximize its potential. To maximize the benefits and minimize the risks of this technology, a multifaceted strategy that considers ethical concerns, legal frameworks, technological innovation, and public awareness is necessary. With the development of AI-driven detection systems, the adverse effects of modified content on both people and society can be addressed.