At a time when the term “fake news” has become a household name thanks to its repeated use by President Donald Trump, deepfakes — i.e., seemingly realistic videos that are in fact manipulated — can further escalate the problem associated with distrust of media. Technologists are looking at the inherent nature of blockchain as aggregators of trust to put more public confidence back into the system.
Truth is increasingly becoming a relative term. When everyone has their own version of the truth, democracy becomes meaningless. The advent of deepfakes is surely pushing society to a point where facts can be manufactured according to one’s opinions and objectives — because in just a few years, the naked eye or ear will no longer suffice in telling whether a video or audio clip is genuine. Humanity has a huge problem to solve.
Bring together “deep learning” and “fake” and you get “deepfake” — a Photoshop job on steroids that makes use of artificial intelligence. If the algorithm of a deepfake has enough data (or footage) of an existing subject, someone else can use the tech to manipulate the video and make it look like the subject is saying or doing pretty much anything.
Social implications of deepfakes
Deepfakes have the potential to change public opinions, skew election results, trigger ethnic violence or escalate situations that can lead to war. Propaganda and fake personal attacks are nothing new but with deepfakes, the strategic contortion of information takes on a different dimension. Fueled by rapid advancements in AI and the viral nature of social media, deepfakes could potentially become one of the most destabilizing technologies to haunt humanity.
Deepfakes can become game-changers for two reasons. The first is that they represent the level of sophistication that can now be achieved through AI. But the second, more important reason is that they also represent a democratization of access to technology.
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The implications of deepfakes don’t even have to be social; they can be personal too. There is an anonymous Reddit account that became infamous for creating fake AI-assisted videos of celebrities, which are often pornographic. Although the creator’s subreddit was banned in February 2018, its videos remain in the public domain.
However, the popularity of deepfakes has spawned several other people in the same business. Celebrities are not the only ones being targeted. Widespread availability and the ease of use of the software has made it possible for anyone to generate a “revenge porn” video.
Several startups working on solving the deepfake problem have since risen, with Ambervideo.co being one of the most prominent firms. Amid the threat of fake videos delegitimizing genuine recordings, Amber is building a middle layer to detect malicious alterations and has developed both detection and authentication technology.
For detection, Amber has a software that looks at the video and audio tracks as well as the aspects within them for signs of potential modifications. Amber is training its AI to pick up on the specific patterns that are unavoidably left behind while altering a video.
The problem with this method is that it is strictly reactive, as the AI only learns from past patterns. Newer deepfake algorithms will go virtually undetected by this retroactive approach, so detection methods are deemed to lag behind the most advanced creation methods.
This is where Amber’s authentication technology comes in: Cryptographic fingerprints are imprinted on the video as soon as it is recorded. Amber Authenticate uses blockchain infrastructure to store hashes every 30 seconds, and thus any alterations to these hashes can hint at potential tampering.
Apart from software solutions like Amber, there is a need for hardware-based solutions too, and companies like Signed at Source are providing it by giving stakeholders the capability for integration with cameras to automatically sign captured data. A deepfake video with the very same signature as the victim’s camera is highly
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