Deepfake technology, a blend of advanced artificial intelligence and machine learning, has rapidly revolutionized the creation of convincing fake media. This paper explores the genesis, societal repercussions, and protective strategies associated with deepfake technology, born from advancements in AI, particularly generative adversarial networks (GANs) and deep neural networks. The technology's ability to create realistic audio, video, and images challenges traditional notions of media authenticity, giving rise to ethical concerns around misinformation, impersonation, and privacy breaches. As deepfake capabilities progress, risks such as identity theft and deceptive practices intensify. The erosion of trust in digital media is a pressing issue, necessitating advanced detection algorithms and authentication methods. Legal and regulatory frameworks are crucial in striking a balance between freedom of expression and preventing malicious use. The paper underscores the intricate dynamics between deepfake evolution, societal impacts, and ongoing protective measures, essential for responsible development and deployment in the synthetic media landscape.
Keywords: Deepfake technology, media authenticity, privacy concerns, identity theft