Does this person exist? I challenge you.

4

October

2020

5/5 (1)

Does this person exist? I challenge you.

During the last years, artificial intelligence technologies have improved a lot. Using several new techniques, for example generative adversarial networks, AI systems are now capable of producing images and videos which look almost identical to normal photography.

Generative adversarial networks exist of two different AI networks which are designed to compete against each other. One of these networks is trained to produce extremely realistic images, whereas the other network is trained to detect fake images. The former network will be rewarded for undetected fake images, whereas the latter network will be rewarded for detecting fake images. Based on this model, both networks are continuously competing against each other and improving the ability to do their respective tasks.

Two of the most known examples of generative adversarial networks are the generation of fake images and DeepFake videos. A really interesting but also scary example of the generation of fake images is the website thispersondoesnotexist.com. Every time you refresh this website, you will be shown another face which is uniquely generated.. While sometimes the images show obvious inconsistencies such as visual inconsistencies, other images can barely be identified as fake.

Within the near future, it will become difficult to find the difference between real and fake images. This can have severe consequences, the impact of fake images of politicians can be really big. For example, a fake image of a presidential candidate visiting a prostitute can have a permanent impact on their reputation.

How do we currently recognize the difference between real and fake images? The most common characteristics of fake images generated by GAN’s are inconsistent backgrounds, weird clothing, ears or earrings which aren’t matching and strange hairs. Do you think that you are capable of recognizing the differences between real and fake images?

I would like to challenge you. I have made a collection of 5 images, can you identify which images are real and which are fake? Please let me know in the comments!

Person A:
https://gyazo.com/d096f8b1bd9479b3b3c41a82927fe6a9

Person B:
https://gyazo.com/a94b8142b19b2d38edbe2ca3932ad8ad

Person C:
https://gyazo.com/9afcbe9ceae191b8091543f71c33a6ff

Person D:
https://gyazo.com/bd807f03a20b17d9430dcbc317f7675a

Person E:
https://gyazo.com/f48038b1006fa97d7975bd8e3c04daa9

Sources:
thispersondoesnotexist.com

Goodfellow, Ian; Pouget-Abadie, Jean; Mirza, Mehdi; Xu, Bing; Warde-Farley, David; Ozair, Sherjil; Courville, Aaron; Bengio, Yoshua (2014). Generative Adversarial Networks (PDF). Proceedings of the International Conference on Neural Information Processing Systems (NIPS 2014). pp. 2672–2680.

Imagined by a GAN (generative adversarial network) StyleGAN2 (Dec 2019) – Karras et al. and Nvidia

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Trump VS Biden, who will decide? The voters? Russia? Or maybe Facebook?

25

September

2020

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Imagine browsing on Facebook, and every 10 posts you receive an ad telling you how bad Biden really is. You start with a video talking about his age and memory, auto-play will then show you a video talking about him laundering money and an hour later you are watching videos incriminating him of sexual harassment. Could this influence your vote during the next election? Most likely, it can (Bovet, 2019).

Social media platforms have gathered a lot of data about their users, this data provides these platforms and advertisers with a lot of power (Scott, 2018). Ad companies can use data to detect how they can manipulate you into voting for them. They can use for example your emotions to select the perfect ad for you which can trigger your emotions, and thus potentially make you vote for them (Scott, 2018). One of the scandals during the last election was with the company Cambridge Analytica, a company which retrieved data of over 50 million Facebook users (Lomas, 2020). This company not only claimed to have made Trump win in 2016, they also report using personal data and psychological reports to influence media in over 65 countries (Lomas, 2020).

Social media election manipulation is not only done by the American politicians, there can also be influences from other countries, for example with the Cambridge Analytica scandal with the Russian influence on the 2016 elections (Lomas, 2020). Despite the reports from Facebook that they are attempting to exclude external and fake political news from their platform, journalists have shown that it is still easy to utilize fake news to manipulate voters in other countries (Martins, 2019)

With over 70% of the Americans using Facebook, the company can reach the majority of the American people, and Facebook can control everything they see. Decisions on what users see – or cannot see – are not just made by ad companies, a major part of these decisions are also made by Facebook (Rhodes, 2020). If wanted, social media companies could also utilize this functionality to push their opinions onto their users, for example by only showing them videos which are positive about their preferred candidate.

Social media can be used to manipulate elections in many ways, the rise of data will potentially allow for even more direct types of manipulation. Who will be deciding this election? Nobody knows. But will people attempt to manipulate voters? Definitely.

Bovet, A., & Makse, H. A. (2019). Influence of fake news in Twitter during the 2016 US presidential election. Nature communications, 10(1), 1-14.
https://time.com/5197255/facebook-cambridge-analytica-donald-trump-ads-data/
Scott, B. (2018). Facebook’s New Controversy Shows How Easily Online Political Ads Can Manipulate You. [online] Time. Available at: https://time.com/5197255/facebook-cambridge-analytica-donald-trump-ads-data/.
Rhodes , L (Producer). (2020). The Social Dilemma [Netflix documentary]. Retrieved from https://www.netflix.com/
Lomas, N. (2020). Facebook data misuse and voter manipulation back in the frame with latest Cambridge Analytica leaks. [online] TechCrunch. Available at: https://techcrunch.com/2020/01/06/facebook-data-misuse-and-voter-manipulation-back-in-the-frame-with-latest-cambridge-analytica-leaks/.
Martins, F. (2019). Facebook lies to Dutch Parliament about election manipulation. [online] Available at: https://www.bitsoffreedom.nl/2019/05/21/facebook-lies-to-dutch-parliament-about-election-manipulation/ [Accessed 24 Sep. 2020].

‌Image: https://lectrr.be/en/cartoon/2018_03_19_Verkiezingsmanipulatie_Manipulation_electorale_Election_manipulation

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