Deepfake is the creative art of replacing someone in a video with the image of someone else usually with the intention of spreading wrong information or giving a false order. For example, a deepfake of President Vladimir Zelensky was created during the Russia-Ukraine war, ordering Ukrainian troops to surrender and return to their families. Deepfake is considered a form of cybercrime in many countries because another person’s identity is unauthorisedly used to spread false information or for any other malicious purposes.
The word, deepfake was derived from two English words ‘Deep’ and ‘Fake’ with the ‘deep’ part stemming from deep learning. Deep learning is a higher level of machine learning that attempts to simulate the human brain (IBM, 2020) and has the ability to extract progressively higher features from data. Many deepfakes are now more difficult to detect because of the level of detail and sophistication implemented especially by experts. Deepfake poses a lot of risk to individuals and countries as it could also affect national security. This can be seen from some real-life use of deepfake discussed below:
- President Vladimir Zelensky orders Ukrainian troops to surrender
- An official confessing to offering bribes to a Burmese politician
- President Ali Bongo’s new year speech that sparked a military coup.
Potential Risks
The more deepfake technology advances, the easier it might become to implicate or frame an individual. As seen in the examples above, deepfake could spark wars between countries. This along with other national security threats could be instigated from the malicious use of deepfake technology.
As the knowledge and awareness on this increases, it may also be possible for people to falsely claim that their words or actions are deep fakes even though they have indeed said or done those things. E.g., things said in one-on-one interviews, or accidental video captures of them in a compromising position, doing something illegal, etc. It is also possible to use deepfake to change words spoken in real interviews to something else in a way that the lip movement synchronises perfectly with the new false words.
The technology could also be maliciously used to damage business reputations through fake customer reviews, false accusation of key personnel at a target company or organisation etc. It could also be used to damage an individual’s reputation as it may be difficult to tell that the video or ‘evidence’ is fake. Spreading hate speech and false news may also be easier especially when combined with the power of social media.
Google recently banned the training of AI systems that can be used to generate deepfakes on its Collaboratory platform (TechCrunch, 2022).
Some Tools That Can Be Used to Generate Deepfakes
- Artificial Intelligence [AI]
- Deepfakes Web
- Photoshop
- ReFace App
- FaceApp
- Face Swap
- DeepFace Lab
Some other notable personalities that have been deepfaked:
This world is getting really scarier to live in. The good thing is that deep fake can be used with good intentions. The bad thing is that it can be used with bad intent.
Scarier indeed Ayomipo! Yes, you are right. Just like we have mentioned before on this platform; life is binary. To every thing, there is a corresponding other side.
It is not a bad thing that technology is advancing but people should learn or be human enough to use it for good reason.
Thanks, Tibzy, but people would always be people 😀
I’m sure there’s going to be BIG business for the company who builds tech on identifying deepfakes. I never came across this term before reading this post.
True, there is potential business (or research) opportunity on tech that would allow us successfully and reliably distinguish deepfakes from real images.
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