Advances in artificial intelligence have made it possible to create highly realistic fake images, videos and audio recordings known as AI deepfakes. These manipulated media pieces can make people appear to say or do things that never happened. While the technology behind deepfakes can have creative and educational uses, there are warnings that it also poses serious risks to trust, privacy and public discourse.
AI deepfakes are created using machine-learning techniques, particularly deep neural networks, that analyze large amounts of real images, videos or audio of a person. The system learns patterns such as facial movements, voice tone and expressions and then generates synthetic media that closely imitates the real individual. As this technology improves, deepfakes are becoming increasingly difficult to distinguish from authentic content.
It can be said that deepfakes are effective because humans naturally trust visual and audio evidence. When a video or voice recording appears realistic, people are more likely to believe it without questioning its authenticity. Social media platforms further amplify this effect by allowing deepfake content to spread quickly before it can be verified or removed.
Deepfakes can be used to spread misinformation, manipulate public opinion and damage reputations. They can be used to impersonate public figures, create false evidence or carry out scams such as voice-cloning fraud. Deepfakes also raise ethical concerns related to consent, privacy and the erosion of trust in digital media.
As deepfakes become more common, they threaten to undermine trust in legitimate media. If people can no longer be sure whether videos or recordings are real, this can lead to confusion, skepticism and disengagement from sources, that have been reliable until now. This phenomenon, sometimes called the “liar’s dividend”, can allow real wrongdoing to be dismissed as fake, further weakening accountability.
AI deepfakes represent a powerful but risky technological development. While they demonstrate the capabilities of modern artificial intelligence, they also pose significant dangers when used irresponsibly. Understanding how deepfakes are created and recognizing their potential impact is an essential part of media literacy in the digital age.
Sources
- Chesney, R., & Citron, D. (2019). Deepfakes and the New Disinformation War. Foreign Affairs.
- Europol. (2024). Facing Reality? Law Enforcement and the Challenge of Deepfakes.
- Karen Hao, MIT Technology Review. (2019). The biggest threat of deepfakes isn’t the deepfakes themselves