A Synthetic Media by Artificial Intelligence
Have you ever seen deepfake videos of Politicians, Celebrities, and Social Figures circulating around social media platforms? In 2019, for instance, a deepfake video of Facebook CEO Mark Zuckerberg was created to raise awareness about the technology’s potential for deception and its implications for user privacy. These videos are often designed to spread misinformation or manipulate public opinion. Companies have employed deepfake technology for dubbing and localization purposes, making movies and TV shows more accessible to global audiences by seamlessly replacing the original language with the desired language. For what and why it is used?
This cutting-edge AI-driven innovation enables the manipulation of images, videos, and audio to an unprecedented degree of realism. Deepfake technology is rooted in the concept of deep learning, a subset of artificial intelligence where algorithms are trained on vast amounts of data to recognize patterns and make predictions
Humans are able to detect artificially generated speech only 73% of the time, a study has found, with the same levels of accuracy found in English and Mandarin speakers.
The sound samples were played for 529 participants to see whether they could detect the real sample from fake speech. The participants were able to identify fake speech only 73% of the time. This number improved slightly after participants received training to recognise aspects of deepfake speech.
Deepfake content is created by using two algorithms that compete with one another. One is called a generator and the other one is called a discriminator. The generator creates the fake digital content and asks the discriminator to find out if the content is real or artificial. Each time the discriminator correctly identifies the content as real or fake, it passes on that information to the generator so as to improve the next deepfake. When clubbed together, these two algorithms form a generative adversarial network called GAN.
The benefits of Deepfake technology
Deepfake technology can provide the following benefits to marketers:
- It lowers the cost of the video campaigns.
- Deepfake technology can create better omnichannel campaigns.
- It can provide hyper-personalised experience to the customers.
Low-Cost Video Campaigns
Marketers can save money on their budgets by using deepfakes for their campaigns as you don’t need an in-person actor.
Instead of using an in-person actor, a marketer can purchase a license for an actor’s identity. You can then use previous digital recordings of the actor, insert the appropriate dialogue from a script for the actor and create a new video.
Improved Omni-Channel Campaigns
Since you don’t need to use in-person actors for a campaign, you can reorganize existing content for various marketing channels for both less time and money.
Instead of reshooting for different channels, you can instead just edit or replace video cuts to create a paid social campaign and save time for other works also.
Hyper-Personalisation
Deepfake technology has led to an upsurge in hyper-personalization.
A brand can provide individual customers with more relevant messaging and experiences based on their personal preferences, such as their ethnicity or skin colour.
Deepfake disadvantages
Unfortunately, deepfake technology has the potential to be used for malicious purposes just because of the power of concepts and ideas to create it are behind it.
Lack Of Trust Or Ethics Issues
The most obvious impact of deepfake technology is that it can be used to create a fake video, so ascertaining the authenticity of a piece of content has become more difficult.
Scamming Increases
Deepfake technology may also increase the number of scams online, you could create false accusations or complaints against companies.
How Can You Spot a Deepfake?
Following are some ways to detect or spot a DeepFake:
- Awkward facial positioning
If the person’s face is pointing one way and their nose is pointing the other way
- Unnatural body movement
When someone looks distorted or their movements are not smooth and disjointed
- Unnatural coloring
Discoloration, misplaced shadows and abnormal skin tone are signs that you are watching a deepfake
- Misalignment
When the visuals are misaligned or blurry
- Images that look unnatural as you zoom in or slow down
If you watch a video on a larger screen and zoom in, you can pay more heed to things like bad lip-syncing
- Inconsistent audio
Deepfakes spend more time on video images than fixing the audio. Look out for strange word pronunciation, digital background noise or even for that matter, the absence of noise
- Absence of blinking
You can see someone’s face and tell if they are saying something without batting an eyelid. That’s a very good sign to detect a deepfake.
What’s the solution?
Ironically, AI is the solution. Artificial intelligence already helps to spot fake videos, but many existing detection systems have a serious weakness: they work best for celebrities, because they can train on hours for freely available footage. Tech firms are now working on detection systems to flag up the fakes whenever they appear. Another strategy focuses on the provenance of the media. Digital watermarks are not foolproof, but a blockchain online ledger system could hold a tamper-proof record of videos, pictures and audio so their origins and any manipulations can always be checked.
Conclusion
Deepfake technology is an undeniable testament to the incredible capabilities of AI and deep learning. It has the potential to revolutionize industries and entertain the world audience by its capabilties. Nevertheless, the dangers of misuse and deception demand careful consideration and swift action to prevent the negative effect of it. As society navigates the future of deepfakes, a collaborative effort involving technology developers, legislators, and the public at large will be vital to ensure that this double-edged sword remains wielded responsibly.
Incoggeek
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