Home   »   Press Freedom Index   »   Deepfake Technology

Deepfake Technology, How Deepfakes Work, Dangers and Solutions

Deepfake Technology: Deepfakes are computer-generated manipulations of audio, video, or images that create highly realistic, but fake, content. They involve using artificial intelligence techniques, particularly deep learning algorithms, to create media that appears to be genuine but is actually fabricated. Deepfake Technology is important for UPSC Prelims Exam and UPSC Mains Exam (GS Paper 3- Science and Technology).

Deepfake Technology in News

Recently, several radio stations and even local TV networks appear to have been hacked to broadcast a deep fake address allegedly by president Putin. This fake address announced mass mobilisation and introduced martial law in border regions.

  • In a broadcast accompanied by the message “President’s emergency appeal,” a digitally altered Russian leader claims that Ukraine’s military has crossed into three border regions.
  • The leader declares martial law in those areas and advises residents to seek refuge within Russia.
  • Several television and radio stations in the affected regions aired the message, which Russian officials attribute to a hacking incident, though no responsible parties have been identified.

Deepfake Technology Explained

Deepfakes are digital media – video, audio, and images edited and manipulated using Artificial Intelligence. It is basically hyper-realistic digital falsification.

  • AI-Generated Synthetic media or deepfakes have clear benefits in certain areas, such as accessibility, education, film production, criminal forensics, and artistic expression.
  • The term “deepfake” combines “deep learning,” a subset of machine learning, with “fake.” Deepfakes are created to inflict harm on individuals and institutions.
  • Access to commodity cloud computing, public research AI algorithms, and abundant data and availability of vast media have created a perfect storm to democratise the creation and manipulation of media. This synthetic media content is referred to as deepfakes.

How Deepfakes Function?

Deepfake technology utilizes neural networks, particularly generative adversarial networks (GANs), to generate realistic synthetic media.

  • GANs consist of two components: a generator and a discriminator.
  • The generator creates the fake content, while the discriminator evaluates the authenticity of the generated content.
  • Through an iterative process, the generator learns to produce increasingly realistic outputs, while the discriminator improves its ability to differentiate between real and fake content.

Deepfakes, a New Disinformation Tool

Disinformation and hoaxes have evolved from mere annoyance to warfare that can create social discord, increase polarisation, and in some cases, even influence the election outcome.

  • Nation-state actors with geopolitical aspirations, ideological believers, violent extremists, and economically motivated enterprises can manipulate social media narratives with easy and unprecedented reach and scale.
  • The disinformation threat has a new tool in the form of deepfakes.

Positive and Negative use of Deepfakes?

Artificial Intelligence (AI)-Generated Synthetic media or deepfakes have clear benefits in certain areas, such as accessibility, education, film production, criminal forensics, and artistic expression.

  • However, as access to synthetic media technology increases, so does the risk of exploitation. Deepfakes can be used to damage reputation, fabricate evidence, defraud the public, and undermine trust in democratic institutions.
  • All this can be achieved with fewer resources, with scale and speed, and even micro-targeted to galvanise support.

Impact of Deepfakes, Who are the Victims?

Deepfakes have very disturbing impact on human society, especially when they are used to tarnish the image and take revenge against other people. Few important impacts of the deepfake technology are discussed below-

  • Pornography: The first case of malicious use of deepfake was detected in pornography. According to a sensity.ai, 96% of deepfakes are pornographic videos, with over 135 million views on pornographic websites alone.
    • Deepfake pornography exclusively targets women.
    • Pornographic deepfakes can threaten, intimidate, and inflict psychological harm.
    • It reduces women to sexual objects causing emotional distress, and in some cases, lead to financial loss and collateral consequences like job loss.
  • Tarnishing the Individual Image: Deepfake can depict a person as indulging in antisocial behaviors and saying vile things that they never did.
    • Even if the victim could debunk the fake via alibi or otherwise, that fix may come too late to remedy the initial harm.
  • Social Harm: Deepfakes can also cause short-term and long-term social harm and accelerate the already declining trust in traditional media.
    • Such erosion can contribute to a culture of factual relativism, fraying the increasingly strained civil society fabric.
  • Threat to Public Safety: Deepfake could act as a powerful tool by a malicious nation-state to undermine public safety and create uncertainty and chaos in the target country.
    • Deepfakes can undermine trust in institutions and diplomacy.
  • Use by Terrorist Organizations: Deepfakes can be used by non-state actors, such as insurgent groups and terrorist organisations, to show their adversaries as making inflammatory speeches or engaging in provocative actions to stir anti-state sentiments among people.
  • Promotes Fake News: Another concern from deepfakes is the liar’s dividend; an undesirable truth is dismissed as deepfake or fake news.
    • The mere existence of deepfakes gives more credibility to denials.
    • Leaders may weaponise deepfakes and use fake news and alternative-facts narrative to dismiss an actual piece of media and truth.

Way Forward against Deepfakes

Various stakeholders of the society can take following steps to minimize the harmful impact/misuse of the Deepfake technology in the world-

  • Ensure Media Literacy: Media literacy efforts must be enhanced to cultivate a discerning public.
    • Media literacy for consumers is the most effective tool to combat disinformation and deepfakes.
  • Collaborative Regulatory mechanism: We also need meaningful regulations with a collaborative discussion with the technology industry, civil society, and policymakers to develop legislative solutions to disincentivising the creation and distribution of malicious deepfakes.
  • Develop Detection Technology: Social media platforms are taking cognizance of the deepfake issue, and almost all of them have some policy or acceptable terms of use for deepfakes.
    • We also need easy-to-use and accessible technology solutions to detect deepfakes, authenticate media, and amplify authoritative sources.
  • Mass Comapaign against Deepfakes: To counter the menace of deepfakes, we all must take the responsibility to be critical consumers of media on the Internet, think and pause before we share on social media, and be part of the solution to this ‘infodemic’.


Collaborative actions and collective techniques across legislative regulations, platform policies, technology countermeasures, and media literacy approaches are a few of the ways in which deepfake threat can be mitigated. It’s important to exercise caution and critical thinking when encountering media online, particularly if there is a possibility of manipulation. Being aware of the existence of deepfake technology can help individuals stay vigilant and make informed judgments about the authenticity of the content they encounter.

PM SVANidhi Scheme Completes Three Years, Performance Evaluation

Follow US 
UPSC Govt Jobs
UPSC Current Affairs
UPSC Judiciary PCS
Download Adda 247 App here to get the latest updates

Sharing is caring!


What are deepfakes?

Deepfakes are digital media - video, audio, and images edited and manipulated using Artificial Intelligence. It is basically hyper-realistic digital falsification.

How are deepfakes created?

Deepfakes are generated using advanced machine learning algorithms, particularly deep neural networks. These algorithms are trained on large datasets of images or videos of the target person to learn their facial features and expressions. Once trained, the algorithms can manipulate and morph the target's appearance in new videos.

What are the main concerns surrounding deepfakes?

Deepfakes raise several concerns, primarily related to misinformation, privacy, and potential misuse. They can be used to create fake news, defame individuals, manipulate public opinion, and facilitate fraud or social engineering attacks.

Leave a comment

Your email address will not be published. Required fields are marked *