Lessons from Zelenskyy Deepfake

Personal reflection about the societal impact of deepfakes

Deepfake is a type of visual deception created by a deep learning model, generative adversarial network (GANs) to be specific, that can algorithmically transpose the “skin” of one human face in a video on to the movements of another.

Here is an example

In Gods Behind the Masks, we are introduced to the tumultuous world of deepfakes. The story unfolds in Lagos, Nigeria, where a young video producer is caught in the middle of a technological warfare between two ethnic groups, where one group is allegedly creating deepfakes to nudge public opinion in their favor. The protagonist, who has prior experience in creating deepfakes, has been manipulated and blackmailed into tarnishing the name of a prominent political leader by creating a compelling deepfake in response. The riveting storyline revolves around the ethical dilemma of the protagonist, torn between choosing what he was hired for and protecting his nation’s integrity.

We are seeing a version of this being played out in Ukraine but it is neither the first nor the last time we will be seeing the use of deepfake with malice in mainstream media. However, it is pertinent that we engage in conversations and initiatives that can put tools and policies in places to combat deepfakes. Some of the suggestions are mentioned by the authors in Gods Behind the Masks, which I will summarize below.

In the effort to combat deepfakes, a low entry barrier solution would be to invest in the development of anti-deepfake softwares, analogous to anti-virus softwares, that can be installed in websites, apps and devices to scan the media content for deepfakes. But this is obviously going to create a tug of war between deepfake makers and deepfake detectors where the side with more computational power is always going to have an edge. A more sustainable solution would be to use blockchain technology to authenticate every phone and video ever taken when it is uploaded to the internet but this would need all the devices to use it, meaning we will need significant advances in blockchain technology for this to become a reality. Above all, we should also need regulatory changes, penalizing individuals and organizations that are responsible for deepfakes.

Though it may seem that there is nothing good about deepfakes and we should refrain ourself from developing these technologies in the first place, the underlying technology, GANs, has tremendous potential in many fields, such as biometrics, media, healthcare, climate change , drug discovery and many more. As such, we must make concerted effort, involving AI practitioners, journalists, and policymakers to make sure we put systems in place that can ameliorate deepfake induced malice. We should also create public awareness about the capabilities and dangers of deepfake so that they can naturally start building good habits around browsing and trusting content from reputable sources.

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