There has never been a time in human history when information is as readily available as it is today. But with so much information spreading online new issues arise. One of these issues is deepfake.
The term deepfake combines “deep learning” and “fake”. It is the use of machine learning to fabricate events that never happened. It’s an advanced form of artificial intelligence, which can be used to manipulate faces and voices.
Hence, making the process of creating fake identities and spreading false information much easier. Deepfake technology is making it harder to tell whether some news you see and hear on the internet is real or not.
And there’s growing concern that in the wrong hands this technology can pose a very real security threat. This technology is threatening to undermine the credibility of almost everything we see online.
From mobile apps that can seamlessly transpose people’s faces into blockbuster movies, to fake statements made by public figures. This technology makes things that never happened appear entirely real.
With widespread deepfake content, there are problems such as manipulation of public identity, attacks on personal rights, violations of rights of intellectual property and personal data protection that are becoming more common.
With the rise of AI-generated media that intends to spread misinformation online, there are growing concerns that this problem will become more significant in the future. Hence what is deepfake?
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What is deepfake?
Deepfake is the use of artificial intelligence and computer processing to create content or situation that never happen that look completely real. By using the correct parameters, users can create videos that look like real people, without anybody doubles, the only thing needed is an image.
Hence, this AI technology use images to produce stunning results. Deep fake can create fake content that has a convincing appearance as a real person. There were over 85,000 harmful deepfake videos made by expert creators, were detected in December 2020.
The technique is popular for the same reason it is a popular choice for Hollywood. The same techniques are used to create a realistic-looking face. A typical deep fake involves changing a person’s face into a different person’s. A human editor can’t tell the difference.
The most common uses of deepfake are movies and television shows. When it is used in the media, its primary purpose is to influence the audience. Moreover, deepfake is also used online to spread fake videos.
The video can be fake or it can be a genuine one. In either case, the truth is the most important. The problem is not limited to fake videos, this technology is used to generate fake news stories. A misinformation campaign involving celebrities can easily change the mood of the masses. Hence this can raise havoc in society or even ruin someone’s reputation.
Impact of deepfake
The most significant challenge posed by deepfakes is the fact that they create false content without the consent of the source person. While the original video is created voluntarily by the creator, the AI content may not be based on real footage.
In addition, deepfakes have the potential to be dangerous. The use of false content can help spread misinformation, and it can be a source of fake news. Expert-crafted videos are doubling every six months since 2018.
As a consumer online, you’re going to watch something, you’re not necessarily going to know if this is real or not. This is where the problem is as it can misinform people or worst create social disorder.
Deepfake is a new type of social engineering that uses algorithms to create videos that mimic the faces of people. The final product uses the original voice and face of the person. This technology has been used in high-profile scams.
A fake video of a celebrity can sway public opinion, influence consumer behavior and even influence stock prices. Among other things, businesses can lose the value of defrauded funds as well as their goodwill and reputation.
These synthetic medias can also be used to impersonate upper management. Fraudsters may pretend to be upper management and demand money transfers from employees.
The impact of deepfake on media and society is already clear. As the Internet continues to grow, issues with these synthetic videos will continue to rise. There are also videos featuring fake people’s faces in nonconsensual pornography.
This is a serious problem for social media users, as many of them might be vulnerable to cyber-bullying or other risks. Some platforms may have commercial interests in keeping questionable content on the web. 93% of deepfake online are made for reputation attacks, defamatory, derogatory and pornographic fake videos.
In the meantime, AI-generated content can be damaging to public opinion and the reputation of a person. Deepfakes have also raised ethical questions. Because they can fool most viewers, they have the potential to cause major damage.
Photoshopping techniques to manipulate an image can circulate a rumor through a family, Facebook, messenger group and all of a sudden this can travel like wildfire. Some have called for these videos to be removed but there are also legal issues to consider and it’s not that easy.
And once something gets on the internet, it cannot be eradicated completely there will always have a copy somewhere. For instance, AI-generated content may lead to disinformation and harassment on social media. This is why we need a better way to detect these fakes. Most of the deepfakes victims are women.
Deepfakes can be generated by AIs using simple techniques such as pasting photographs on videos. The creators use generative adversarial networks or GANs, to create videos containing a high probability of being fake.
This method of spreading misinformation raises many concerns, including the fact that the fakes can be more convincing than real videos. This makes them very difficult to detect. And if you’ve ever watched a fake video, you know how viral it can get.
A deeper problem with deepfakes is the lack of consent. This issue is especially pertinent given the technology’s origins in pornography. While companies and governments routinely collect vast amounts of data about the average internet user, most people are unaware of how many pictures of them are floating around online.
Last year, only around 7% of expert-crafted deepfake videos were made for entertainment purposes. This lack of awareness raises questions about the ability to practice reputation management.
What does the future hold for deepfake
The consequences of deepfakes are not pretty. Most of them are easily detectable but some are very convincing. This means that the technology to fight AI content will need to get more advanced. As such, we need more laws and research to help us deal with this growing problem.
In the meantime, we need to be aware of the risks of deepfake videos and educate ourselves about how to spot them. Although the problem of deepfakes is not new, tech platforms are still struggling to combat it.
In fact, tech platforms have tried to moderate deepfakes and have gotten very close to removing non-consensual pornographic ones. The biggest problem with Deepfakes is that they have become so easy to create.
Deepfakes pose a significant challenge for governments as well as our general culture and values. Brookings researchers argue that our current laws do not protect us from these malicious technologies and are not even designed to address them.
In addition to the challenges posed by deepfakes, there are significant ethical concerns about using such technologies. They can also disrupt the political system. Because they can be so destructive, it is important to build such technologies with proper oversight and partnerships.
This will help ensure that the technology is used responsibly. Several legal issues are related to the use of these systems. The future of deepfakes remains uncertain and will likely depend on how they are published and propagated.
If they are created by amateurs, social media platforms could ban them or impose community guidelines. While Facebook has tried to impose such a ban, it may be difficult to enforce. As synthetic media becomes more realistic, social media companies are faced with the impossible challenge of keeping their users safe without violating their privacy.
To combat this new hazard, companies need to have robust training programs and transparent operations. This will enable companies to recognize potentially suspicious content more easily and detect malicious media before it reaches consumers.
Breaking down information silos will allow them to identify and remove fake content. By ensuring that as many people as possible have the right information, it will become easier to spot and stop fake media from spreading.
Technological defenses to deepfakes are emerging. While they can’t completely prevent cybercriminals from creating fake content, they will help us identify them. It is important to invest in forensic methods to detect synthetic media. Governments should invest in media forensic techniques.
Until then, we can only hope that the threat will be controlled. For now, the only way to ensure that we stay safe is to trust the source and don’t share the content with the public.
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