{"id":1342,"date":"2021-05-18T21:10:50","date_gmt":"2021-05-18T21:10:50","guid":{"rendered":"https:\/\/www.politicsphere.com\/velicia-huston-on-growing-up-and-growing-older-in-hollywood\/"},"modified":"2021-06-19T17:16:38","modified_gmt":"2021-06-19T17:16:38","slug":"deepfake-reality-of-artificial-intelligence","status":"publish","type":"post","link":"https:\/\/www.politicsphere.com\/deepfake-reality-of-artificial-intelligence\/","title":{"rendered":"Deepfake: What happens if we can no longer trust our eyes or our ears?"},"content":{"rendered":"

Deepfake is the latest trend in artificial intelligence that has been spreading across social media like wildfire. Deepfake has become a tool for revenge porn, fake news, and more recently used to create videos of people saying things they never said or doing things they never did. What are deepfakes? How do deepfakes work? And what can be done about them?<\/p>\n

What are deepfakes, and how do they work?<\/h2>\n

Deepfakes– a portmanteau of deep learning and fake\u2014 are synthetic media that faces from existing images or videos are replaced with someone else’s likeness. While faking content isn’t new, deepfakes use powerful techniques from machine learning and artificial intelligence to generate deceptive visual and audio content. The primary methods of creating deep fakes are based on machine learning and involve training generative neural network architectures, such as autoencoders or generative adversarial networks.<\/p>\n

Using an autoencoder will generate a deep learning AI program tasked with studying video clips to understand the person’s features from various angles and environments. It will then map that person onto the individual in your target video by finding common features.<\/p>\n

Intelligence researchers use a new type of machine learning known as Generative Adversarial Networks (GANs) to identify deepfakes. These networks analyze complicated algorithms on both sides to find flaws.<\/p>\n

GANs are also used as a popular method for creating deepfakes, relying on the study of large amounts of data to “learn” how to develop new examples that mimic the real thing, with painfully accurate results.<\/p>\n

How are deepfakes used?<\/h2>\n

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Several software and apps have created ways for beginners to generate deepfakes with relative ease, such as the Chinese app Zao, DeepFace Lab, FaceApp (a photo editing app with built-in AI techniques), Face Swap, and DeepNude.<\/p>\n

Deepfakes:\u00a0Cons<\/h3>\n

While the ability to automatically swap faces to create a high-quality, realistic fake video of anyone has some interesting harmless uses (such as filmmaking and gaming), this is obviously a dangerous technology with some worrying implications. One of the first real-world applications for deepfakes was to create pornography.<\/p>\n

In 2017, a Reddit user named “deepfakes” created a platform(subreddit) for porn that featured face-swapped actors. Porn (particularly revenge porn) has caused significant damage to celebrities and public figures. According to research from the Deeptrace company, pornography made up 96% of deepfake videos found online in 2019.<\/p>\n

Deepfake has transitioned from being a tool for porn to fraud and political propaganda. Imagine you’re watching the evening news and see a press conference of your Prime Minister urging people to rebel, but everything is a deepfake. Without any authentication, it is impossible to distinguish between a legitimate video and an artificial intelligence-generated false one.<\/p>\n

\u201cIn 2017, researchers from the Washington University at St Louis released a paper describing how they had created a fake video of President Barack Obama to highlight research on generative technology and what may happen if users put it to nefarious use google’s chief executive, Mark Zuckerberg, has also been the target of a deepfake video that appeared to show him credit a secretive organization for the success of the social network.<\/p>\n

One potential issue with AI-generated deepfake content is scams. It isn’t easy to know whether an imposter has replaced the person on the other side of a phone call or video conferencing session because they could be mimicking in great detail their voice and how they would have responded to certain questions or statements. Scammers used a deepfake of the voice of a tech CEO to convince one employee at the company to transfer money to their account. And this is not the first time: last year, scammers managed to defraud another company using the same trick, netting $240,000.<\/p>\n

Deepfakes:\u00a0Pros<\/h3>\n

Deepfake technology can revolutionize history lessons by making them interactive and much more engaging for students. It may also preserve historical stories since deepfakes could depict firsthand accounts from protagonists of large-scale events like World War II.<\/p>\n

For the David Beckham malaria announcement, a YouTube video of him appearing to speak nine languages was created using AI. Deepfakes allow for translated films that use the original actors. The voices sound like the original ones, and, crucially, the lip movements match up with words spoken. Deepfakes will make video and audio more accessible by bridging language barriers.<\/p>\n

The technology can synthesize realistic data to help researchers develop new ways of treating diseases without being dependent on actual patient data.\u00a0\u00a0Mayo Clinic, the MGH & BWH Centre for Clinical Data Science, and NVIDIA collaborate to create synthetic brain MRI scans using generative adversarial networks (GANs).<\/p>\n

The team trained their GAN on data from two brain MRI datasets \u2013 one containing approximately 200 brain MRIs showing tumors, the other containing thousands of brain MRIs with Alzheimer’s. The conclusion drawn by the researchers from this is that deepfake algorithms have become just as proficient at cancer detection as algorithms trained with only real images.<\/p>\n

How can we tell fake from real?<\/h2>\n

Deepfakes are becoming a common occurrence, but it’s inevitable for people to get used to spotting them. This will help prevent the fallacies of fake news from entering society and being believed as authentic.<\/p>\n

Outlined below are a few indicators that give away deep fakes:<\/em><\/p>\n