- Deepfakes refer to synthetic media, usually images and videos created using AI and deep learning techniques.
- It is a combination of "deep learning" (a subset of machine learning that involves neural networks with multiple layers) and “fake.”
- How Deepfakes work?
- It uses Generative Adversarial Networks (GANs) to analyze and synthesize audio and visual content.
- GANs consist of two parts –
- Generator, which creates fake content, like a video or audio clip.
- Discriminator, which attempts to distinguish the fake content from the real one.
- Applications of Deepfakes: Natural and accurate dubbing in movies and TV shows, training simulations in fields, such as medicine, aviation, etc., to help professionals improve their skills and decision-making abilities, etc.
- Issues associated with Deepfakes
- Political Manipulation: Significant threat to the integrity of democratic processes by spreading misinformation, defaming public figures, etc.
- Weaponization against women: Revenge pornography, impersonation and defamation, online harassment, etc.
- Security Risks: Can be used to deceive security systems, such as facial recognition or voice authentication.
- Legal Issues: Fabrication of evidences, violation of intellectual property, consent, etc.
- Ethical Issues: Manipulation, disinformation, erosion of trust, etc.
Measures to counter DeepfakesIn India
At Global level
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