cover image of the project
DensityDesign FSDS 2019/2020

THE MANY FACES OF DEEPFAKE

A project by Andrej Cattaneo, Ivana Riva, Noura Sammoura, Maria del Pilar Suarez Anzorena, Arthur van der Werf, Yueling Wu.

Recently there has been a lot of commotion around an emerging technology called Deepfake. This artificial technology based on deep learning allows the manipulation of content up to concerning levels or realism. However, aside from all the social-political threats, what really is out there currently?

This research digs into different platforms to explore the current situation around Deepfake. The first protocol introduces the topic by studying the differences in the vocabulary used to describe the phenomenon. One can see that the general language among top search results carries concern, but does the internet’s Deepfake content reflect this worried message brought to the public? Will the oblivious internet wanderer come across critical content, or does this darkly portrayed technology have an entertaining side as well?

From this research it has become evident that the tools to create a Deepfake are accessible to anyone, ranging from simple applications to complex programming. A study of YouTube confirmed that there is a community that creates “amusing” variations of legendary video content using Deepfake. The news about the sci-fi dangers of this technology seems rather at a distance whilst its innocence is close within reach. Aren’t these characteristics of the most dangerous threats? Content manipulation is at its most powerful when it is not recognised, and a vast amount of badly executed examples convince one that this is still easy.

Research Questions

How is Deepfake presented in article titles and subtitles according to eight different countries on Google and Baidu?

The concept of Deepfake has a rather indefinite scope, therefore the first protocol frames a reference of associated words presented by search engines in eight countries with different political, religious, and private standards. Titles and subtitles were taken from the first eight articles on Google in the United States, Argentina, Italy, Saudi Arabia, Germany, the Netherlands, and Baidu for China.

How is the phenomenon of Deepfake presented according to pictures and video screenshots from articles in eight different countries on Google and Baidu?

Search engine algorithms have a great influence on the way information is presented to the user. What do the top search results, presented by major search engines, communicate about the topic Deepfake? The visual content of twenty articles was analysed for each one of the eight countries with different political, religious, and private standards.

Whose faces are being displayed in Deepfake videos on YouTube?

What kind of Deepfakes does the most commonly visited platform for videos, YouTube, present to its visitor? What source content is used for the creation of these videos and whom are its protagonists replaced with? The top original Deepfake search results were analysed, and their substitutes were categorised by profession.

What are the applications that are associated with Deepfake in the Google Play Store and how are they categorized?

The technology used to create a Deepfake seems far out of reach, but is this true? On the internet one can find plenty of low-fi solutions, many of which can be run on a mobile phone. This protocol provides an overview of the applications in the Google Play store, how they are categorised, and which are downloaded the most.