Fresh off the news that Reddit brought the banhammer down on r/deepfakes and a worried direct message from a friend on Twitter, I realised I should probably go and find out what 'deepfakes' actually are. Turns out, I probably didn't want to know.
The 'deepfake' phenomenon is so fresh that a Wikipedia search doesn't even bring up a result, so it's kind of definition-less at present. Let's try to define it.
Deepfake (noun): A fake pornographic video generated using machine-learning neural-networks, often used to swap celebrities faces into hardcore porn.
The deepfake phenomenon started shortly after Motherboard shed light on a reddit user, named 'deepfakes', who was posting pornographic videos of celebrities such as Gal Gadot, Taylor Swift and Scarlett Johansson. Using open source machine-learning tools freely available from places like Google, 'deepfakes' was able to swap the personalities faces into hardcore pornographic videos - creating fake porn of the stars.
The software is based on libraries where huge numbers of photos are stored. The machine learning program is able to pluck the correct images out - the right angles, expressions - and matches them to the video, creating a fake video that can, in some instances, look highly convincing.
The name itself feels like it may have arisen from the 'DeepFace' AI program, a machine learning neural network for facial recognition that Facebook uses to match faces online. Similarly, to create deepfakes, a machine learning algorithm takes a face - usually a celebrity - and places their face within another video. As Motherboard calls it, this is 'AI-Assisted Fake Porn', and it has been proliferating extensively online over the past couple of months.
Though it started with one Reddit user, several apps have been made publicly available that allow users to create their own 'deepfakes'.
Now, terrifyingly, the tools do to this are no longer out of reach of the average internet user with an okay PC. Anyone can do this now and that raises some huge ethical questions.
In a move already countering the proliferation of these fakes, a raft of websites have recently deemed the deepfakes as non-consenual and banned them from their platforms, including PornHub and Gfycat.
The challenge going forward will be how we distinguish between the fake and reality - a problem that we're already encountering in the daily news cycle. For now, there's no quick fix, but technology will need to advance to the point that fakes can be easily distinguished, and snuffed out, before they proliferate across the web.
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