Case registered against alleged Deepfake Video of the Union Home Minister in Maharashtra

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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.

Section 66D of the Information Technology (IT) Act, 2000 provides for punishment for cheating by impersonation using any communication device.
Rules 3(1)(b) and Rule 3(2)(b) of Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Rules, 2021 mandates social media intermediaries to observe due diligence to not host content that is obscene, deceives or misleads the addressee, etc.

Bletchley Declaration: To comprehensively and collaboratively address the risks and responsibilities involved in AI by concentrating more on fostering scientific cooperation

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