In the age of technology and digital innovation, the boundaries between reality and deception have blurred more than ever before. The advent of deepfake videos has opened up a new realm of possibilities and challenges. Recently, a deepfake video featuring popular actor Rashmika Mandanna garnered significant attention on the internet.
This manipulated clip depicts Ms. Mandanna entering an elevator, yet it is far from reality. The video set off a chain of reactions, including actor Amitabh Bachchan’s call for legal action and the notice of Union Minister Rajeev Chandrashekhar. But what are deepfakes, and how do they work?
Understanding Deepfakes: The 21st Century’s Digital Deception
Deepfakes, a portmanteau of “deep learning” and “fake,” are a product of artificial intelligence, specifically deep learning algorithms. These videos use artificial intelligence to create fake events, often indistinguishable from real occurrences. The essence of a deepfake lies in its ability to swap one person’s face with another, resulting in the seamless manipulation of visuals and audio. In the case of the Rashmika Mandanna video, her face was replaced with that of British-Indian woman Zara Patel.
Deepfakes serve two primary purposes: transforming existing source content by swapping faces, as in the aforementioned video, and creating entirely original content, wherein individuals can be made to appear as if they are saying or doing things they never did. The technology behind deepfakes involves advanced algorithms and machine learning processes that analyze facial features and expressions, enabling a seamless blending of faces, voices, and actions.
The Birth of Deepfakes faces by Rashmika Mandanna
The first notable instance of deepfake videos came to the fore in 2017, on the platform Reddit, when a user swapped the faces of celebrities, including Gal Gadot, Taylor Swift, and Scarlett Johansson, to create pornographic clips. These videos are crafted by machines employing deep learning algorithms.
The process begins with a deep learning algorithm, known as the encoder, which scans thousands of face shots to understand the commonalities between two faces. Subsequently, it compresses these images, reducing them to their shared characteristics. Then, an algorithm called the decoder is used to reconstruct the face with the appropriate expressions and orientation. This intricate procedure must be executed on every frame for a convincing deepfake video.
The Varied Uses of Deepfakes: From Misleading to Malicious
While many deepfake videos have been of a pornographic nature, they have also played a role in manipulating political narratives during elections. These digitally altered clips are often used to attribute false statements or promises to politicians. For instance, a deepfake video in the past depicted former US President Barack Obama making derogatory remarks about Donald Trump.
Similarly, a manipulated video showed Mark Zuckerberg, the head of Meta, bragging about having “total control of billions of people’s stolen data.” Deeptrace, an AI firm, identified 15,000 deepfake videos online in September 2019, signifying a significant increase over nine months. These developments have raised concerns among experts, such as Danielle Citron, a law professor at Boston University, who warns of deepfake technology being weaponized, particularly against women.
Deepfakes are not limited to videos alone. They also extend to the creation of entirely fictional photos, often used for various purposes. Cybercriminals have taken advantage of this technology to construct fake profiles on professional platforms. For instance, “Maisy Kinsley,” a non-existent Bloomberg journalist, had a deepfake-generated profile on LinkedIn. Similarly, a fake LinkedIn profile under the name “Katie Jones” claimed to work at the Centre for Strategic and International Studies. This aspect of deepfakes demonstrates the breadth of their potential application.
A Diverse Group of Creators
The technology behind deepfakes is utilized by a wide range of individuals and entities. Academic and industrial researchers, amateur enthusiasts, visual effects studios, and even the adult entertainment industry are among the users of this technology. These diverse applications highlight the accessibility and adaptability of deepfake technology, raising concerns about its potential misuse.
In a world where reality is often a matter of perspective, deepfake videos represent a formidable challenge. The Rashmika Mandanna deepfake incident underscores the need for vigilance and the imperative of addressing this digital deception effectively.
The technology’s applications, from benign to malevolent, require a multi-pronged approach, involving technology companies, policymakers, and the public to mitigate the risks associated with deepfakes. In the evolving landscape of digital deception, awareness, regulation, and innovation are essential tools to protect the authenticity of the digital world.
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