What is Deep Fake?
Deepfake refers to an artificial intelligence-driven technology that utilizes machine learning algorithms, specifically generative adversarial networks (GANs), that produce synthetic media, which includes images, videos, and audio recordings. The Primary objective of deepfake technology is to generate synthetic media that exhibits a very high level of realism, closely resembling actual individuals, while incorporating manipulated elements within the content[1].
Deep learning is a subfield within the realm of machine learning that makes use of algorithms inspired by the complex framework and functionality of the human brain, referred to as artificial neural networks. These networks are employed to effectively process and analyse vast volumes of data. The field of deep learning has seen extensive application across various domains, including computer vision, natural language processing, speech recognition, and robotics[2].
The term Generative Adversarial Networks (GANs) are a class of deep learning architectures that employ two neural networks, namely a generator and a discriminator, to undergo training on a given dataset. The objective is to generate fresh synthetic data that closely resembles the characteristics of the original data. The generator is responsible for producing synthetic samples, while the discriminator evaluates the genuineness of both the generated samples and the real samples obtained from the training dataset. The two networks are trained using an adversarial approach, wherein the generator aims to produce samples that can deceive the discriminator, while the discriminator strives to accurately differentiate between the generated samples and the authentic ones. The aforementioned procedure persists until the generator achieves the capability to generate synthetic data that closely resembles real data[3].
Current Scenario of Deepfake in India!
Currently, in India, there is no specific law in place that criminalizes the creation or dissemination of deepfakes. However, specific provisions within current legislation can be utilized to address instances of misuse pertaining to this technology. For example, Sections 67 and 67A of the Information Technology Act, 2000 impose penalties for the circulation of sexually explicit material in an explicit manner. Section 500 of the Indian Penal Code, 1860 stipulates the legal consequences for the offense of defamation[4].
However, the legal framework is currently under development in order to address the distinct challenges presented by deepfakes. There are ongoing discussions regarding the necessity for the Indian Government to address this matter and develop a regulatory framework. There is an ongoing argument that the current laws implicitly forbid the public release of deepfakes. However, there are certain challenges within the existing framework that can potentially be resolved by implementing suggested legislative amendments[5].
The application of proficient artificial intelligence algorithms and cryptography has also been proposed as a means to identify deepfakes and facilitate necessary legal measures[6].
Deepfake technology has a significant presence in India, with notable applications in politics, the film industry, pornography, and instances of revenge defamation. The prevalence of deepfake technology has given rise to various concerning cases. For instance, there have been instances where individuals, such as Mr. Manoj Tiwari, have been depicted in deepfake videos insulting the state government of Delhi. Additionally, there have been instances where political parties, like the Aam Aadmi Party, have been portrayed speaking in English and Haryanvi dialects through deepfake manipulation. It is crucial to recognize that deepfakes have the potential to cause significant harm to both the targeted individuals and society as a whole. This harm manifests in the form of injury to the sentiments, thoughts, and perspectives of the people [7].
In addition, the case of Famous journalist Rana Ayyub highlights the insufficiency of our current legal framework in safeguarding individuals affected by revenge pornography. Regarding the matter involving Rana, it has come to light that an individual had manipulated a video of an explicit nature with the intention of falsely portraying Rana Ayyub as the central figure. The incident of this brutal assault took place shortly after she commenced her advocacy for the rape victim in Kathua. An eight-year-old girl was subjected to sexual assault over an extended period of time, resulting in her tragic death. The officials from the BJP in the Jammu area have been running a campaign fighting for the accused individuals, asserting that they have been subjected to unjust discrimination based on their religious affiliation. When Rana Ayyub expressed her concerns, she faced instances of online harassment and hate speech. To address this issue, she employed the use of Twitter as a means of combating such behaviour. A number of manipulated tweets featuring Rana were being shared on the microblogging platform, and she noticed her involvement in some of them[8].
Conclusion & Suggestion
The current cybercrime legislation in India falls short in adequately tackling the issue of deepfakes. The absence of specific regulations pertaining to the usage of AI, ML, or deepfakes in the Information Technology Act, 2000 presents challenges in effectively governing their application. In order to establish effective regulation of crimes involving deepfakes, it may be necessary to consider revising the IT Act of 2000 to incorporate specific provisions pertaining to the utilization of deepfakes and the corresponding repercussions for their misuse. There is potential to strengthen legal protections for individuals whose photos or likenesses are exploited without their consent. Additionally, it may be beneficial to increase penalties for individuals who create or distribute deepfakes with malicious intent.
It is important to bear in mind that the development and deployment of deepfakes pose a global issue, which will likely require collaborative efforts to regulate their usage and prevent infringements on privacy. One effective approach to safeguarding oneself and one’s business from the threat of deepfakes is to exercise caution and diligently verify the authenticity of online content. In the interim, governments may consider implementing the following measures:
- Censorship technique involves preventing intermediaries and publishers from spreading inaccurate information to the general public.
- Strategy which is of a more stringent nature, involves ensuring accountability for individuals responsible for the creation or dissemination of disinformation.
[1] https://www.scconline.com/blog/post/2023/03/17/emerging-technologies-and-law-legal-status-of-tackling-crimes-relating-to-deepfakes-in-india/ (Last Visited on 22.11.2023 at 6:20 PM).
[2] Ibid.
[3] Ibid.
[4] https://www.mondaq.com/india/new-technology/1164388/deepfakes–a-threat-to-facial-recognition-technology (Last visited on 22.11.2023 at 6:55 PM).
[5] Jha, Piyush and Jain, Simran, Detecting and Regulating Deepfakes in India: A Legal and Technological Conundrum (March 1, 2021). Available at SSRN: https://ssrn.com/abstract=4411227
[6] Ibid.
[7] https://www.thehindubusinessline.com/news/national/bjp-leader-manoj-tiwari-used-deepfake-videos-to-reach-out-to-voters-in-delhi-report/article30857871.ece (Last visited on 22.11.2023 at 6:58 PM).
[8] https://clt.nliu.ac.in/?p=887 (Last Visited on 22.11.2023 at 7:00 PM).
This article is written and submitted by Diwakar Prakash Garg during his course of internship at B&B Associates LLP. Diwakar is a 4th year BBA LLB student at UPES, School of Law, Dehradun.
