deepfake technology

What is Deepfake?

A Brief Intro…

Deepfake is a technology used for producing or changing video contents so that the video presents stuff that didn’t occur. The term deep fake was first coined in 2017 by a Reddit user named “deep fake”. Deepfake is a combination of “deep learning” and ”fake “. It is a technique that is used for synthesizing human images using the technology of artificial intelligence.

Deepfake video is created by using two competing AI systems — one is called the generator and the other is called the discriminator. Virtually, the generator creates a fake video clip and then asks the discriminator to deduce whether the clip is real or fake. The generator and discriminator together form the generative adversarial network called the GAN, modern and unique machine learning technique.

Deepfake works by incorporating and superimposing existing images and videos onto source images or videos using the GAN Network.

The GAN network is established by identifying the desired output and creating a training dataset for the generator. Once the generator starts producing enough output, videos are fed to the discriminator.

This technique generates new data while using the same statistics as the training set.

Uses of deepfake

  • Celebrity pornographic videos
  • Revenge porn
  • Fake news
  • Malicious hoaxes

Typically the use of deepfakes has been negative. Fake news is of course a large concern, but also a lot of adult content utilizing name and/or likeness has been created. Imagine top mainstream media faces and names being passed off as skip the games escorts or other types of sex workers.


So far deepfakes have been developed largely in two major fields:

  • Academic research: academic projects have focused on creating more realistic videos and on making techniques simpler, faster, etc. The “Synthesizing Obama” program, disseminated in 2017, modifies video footage of former President Barack Obama to illustrate him grimacing the words contained in a separate audio track. The earliest landmark project was the Video Rewrite program, published in 1997, which modified existing video footage of a person speaking to depict that person mouthing the words contained in a separate audio track.
  • Amateur development: in 2017 Reddit community users created many deepfakes that revolved around celebrities’ faces swapped on the bodies of porn actors. As time passed, the Reddit users made many big fixes in those created deepfake videos which then increased the problem as it became more difficult to distinguish between the original and the fake videos.


Deepfakes have been used to misinterpret the speeches of famous politicians on video portals and chat rooms.

Deepfake App

In 2018 an app similar to the deep fake was launched, by the name of FakeApp, which helps users to conveniently swap faces and share fake videos. This app uses the GPU network and at least 3 to 4 GB of storage space for its purpose. The main victims of this app are celebrities, but they can also include common people.


  • The manipulation of images and videos using artificial intelligence has become a dangerous mass phenomenon, the motivation behind deepfake pornography is to insult and control women.
  • Today it takes no time to corrupt things with new technology. The problem with deepfakes is that it’s hard to tell the difference between truth and deception, and which video content is authentic.
  • Many websites promised to delete and block deep fake videos, for example, twitter and gfycat.

As the generator gets better at creating fake video clips, the discriminator gets better at spotting them. Conversely, as the discriminator gets better at spotting fake video, the generator gets better at creating them.

Up until today, video content has been more difficult to alter in any significant way. Deepfakes are created through AI, however, they don’t compel the substantial skill that it would take to create a practical video otherwise. Unfortunately, this means that just about anyone can create a deepfake to facilitate their selected strategy. One threat is that people will take such videos at face value; and that people will stop believing in the certainty of any video content at all.

It’s been feasible to alter video footage for decades, but doing it took time, highly qualified artists, and a lot of wealth. Deepfake technology can change the game. As it formulates and develops, anyone could have the capacity to make a persuading fake video, including some people who might seek to “weaponize” it for political or other violent purposes.

Deep fake makes it just as easy to create a fake video of an imminent emergency alert warning attack, or destroy someone’s marriage with a fake sex video, or disrupt a close election by dropping a fake video or audio recording of one of the nominees days before electing starts.… Read More

fake news facebook

How is Facebook Attempting to Combat “Fake News”?

Every individual out there that is using the social media understands the importance of accurate and reliable information. False news is very harmful and can cause damage to an entire community. Fake news not only misinforms the world but also erodes trust. Fake news on Facebook is not a new phenomenon and the tech company is taking measures to curb the rising number of fake news on its platform. Facebook is using several techniques to fight against the spread of false news in different ways.

Disrupting economic incentives

Most of the false news that you will find online are financially motivated. One of the most effective approaches is removing financial incentives for traffickers who misinform the public. It has been found that most of the fake news is financially motivated as it aids the spammers make money by masquerading as legit publishers and post hoax that get people to visit their sites most often. Some of the key measures that Facebook has taken include:

using the community to identify false news and third party so as to be able to check the organizations ability to limit the spread which can be very uneconomical.

  • Facebook has also made it very possible for people who post fake news to buy ads on their platform through the use of strict policies.
  • Facebook is also using machine learning in detecting fraud and assisting the response team in enforcing policies that are against inauthentic spam accounts.
  • Facebook is also updating the detection of fake accounts which makes spamming even harder.

Building new products

Facebook is constantly building and testing new products in an aim to identify and limit the spread of fake news. IT is very hard for Facebook to distinguish between Fake and real news and most importantly it is not their role. They cannot be held as the judges of news in that they receive millions of posts every single time on their platform. Facebook has always relied on the community and third parties in working for better ways to identify and prevent the spread of fake news on Facebook platform. Facebook has been able to achieve this through:

  • Ranking improvement where Facebook is taking crucial measures to improve the online community news feed. Facebook has been able to find that people will share an article that they find interesting and were very much unlikely to share an article that doesn’t interest them. Such kind of an article is often misleading and Facebook has done a great job in reducing the number of misleading contents.
  • Facebook relies on the online community to determine the kind of information that is valuable and the kind that is not valuable. Any news that is flagged false by the online Facebook community shows up lower in the news feed.
  • Through working with partners Facebook has been able to provide a lot of information which can help you decide what to what to trust and share. Facebook has started a program that works independently with third party fact checking organizations to identify the credibility of a story before it is flagged as true or false.

Help people make informed decisions

Facebook has made a strong commitment in ensuring that the number of false news is reduced to zero. It has also taken the right steps to address the problem in case hoaxes are encountered. It is exploring ways in which people can get more context about stories so that they can make an informed decision about the kind of information they read on their platform. Some of the areas that Facebook has focused on include;

Facebook has made recommended efforts in its fight against fake news by partnering with news organizations in the development of new products, tools and services for journalist and help people get better information so that they can make the right choices. Facebook has also joined a group of over 25 funders and participants which include academic institutions, tech industries and non profit organizations in helping people make an informed decision about the information that they read online.


With the steps that Facebook has taken one might wonder whether, any of the steps will help to stop fake news. Through its efforts the overall magnitude of misinformation on Facebook has reduced by a great margin. There is always a fake news on the web whether it is on Facebook, google, twitter or any social media. The only challenge is quantifying the extent of the problem and the kind of damage it is able to cause. For instance, during the France election surveys carried by Facebook was able to establish that almost 90% of the news that was spread online was fake. As much as the techniques used to fight the spread of false information was very effective but still most of the misleading information were widely spread through the social media.

Gatekeeper or content distributor

It is only governments that have the legal right to regulate the freedom of speech however. Facebook is not a government but it is always making decisions about the kind of information that can be made public through their platform. For instance, Facebook removed the historic photo of Napalm Girl photo and other violent videos from their platform. Facebook polices all the content that are available on their platform. It prohibits violent imagery, nudity from the social network and is constantly evaluating the kind of content that should be allowed.

Facebook has had a great challenge in its attempts to combat Fake news online. Facebook leaked a document to the guardian regarding a violent and grossly conduct on a woman. It is violent and upsetting and Facebook viewed this as a form of self-expression hence therefore permissible. However, they found themselves in hot soup when their editors were accused of suppressing conservative news in their trending topics and this forced Facebook to return to algorithms. Such changes have transformed Facebook into the business of content distribution other than a social network site. … Read More