“A total and complete dipshit.” That’s what Barack Obama seemingly called President Trump when he appeared in a short clip for BuzzFeed Video’s YouTube channel in April 2018. Here was a sharp gibe, uncharacteristic of the ex-President. Except, as Jordan Peele’s appearance soon revealed, it wasn’t Obama who was speaking. Instead, a vocal impersonation had been layered over a computer-generated image of his face – one which moved to eerily mimic the words being said. Here was a new genre of fabricated video, where pre-existing visuals of a targeted face are inputted into a create a realistic reproduction that can be manipulated for the creator’s ends. A deepfake.

While some people noticed that something was off about the way Obama looked and sounded, many others were initially fooled or at least confused by the clip. The incident demonstrates how good the generative algorithmic subset of the artificial intelligence used to create a deepfake is. And, scarily, the machine learning processes that help synthesize them are just getting better and more accessible, progressively requiring fewer source materials and extending to manufactured voices too. Every day, it becomes easier to forge people. And these forgeries can damage individual lives (as in cases of targeted pornography), but can also pose risks on the global-scale by undermining public trust in information sources generally considered to be reliable. 

Today, we’re at a point where experts are playing catch-up to identify what’s real and what’s not. When the Gabonese President appeared to the public in a video-address to quell reports about his ill-health on New Year’s Day 2019, for example, many citizens and critics questioned its authenticity. A definitive answer on whether or not it is a deepfake remains elusive. And yet, its uncertain origins spurred a failed coup a week later. In any other time in history, a recording would be undeniable proof of something, just as the photograph had promised at its inception. But human innovation has transformed yet another medium of communication for the worse. What Photoshop did to photography, deepfakes do to film. And suddenly, a source and sphere of information is heavily compromised.

No doubt, deepfakes are a tremendous feat of human intelligence, showing how much of what we perceive can be influenced by others. Their rapid proliferation also represents the wonders of a democratized digital world. However, in developers’ quest to enhance our ability to control older audio-visual technologies with more sophisticated tools, they create dangerous, false information that threatens society. This is because people either believe a fabricated product and are influenced negatively by it, or they don’t and turn skeptical towards all products, losing their trust in the institution of production itself. Essentially, this maps onto the idea that people make decisions based on some collection of information, but deepfakes delegitimize a fundamental mode of information-collection.

 There is a strong connection between this and the value of trust in our lives. In Trust in Society, Karen S. Cook notes that “trust plays a significant role in the functioning of social groups and societies,” and also links trust to order and stability. Trust is foundational to relationships within and with an organized collective. In a sense, we need to trust people and institutions to both preserve ourselves, and the democratic society we inhabit. If lost, instability and a loss of connections ensue. For example, in a simplified hypothetical, if you called the police while your house was getting burgled and they did not show up you would suddenly doubt the institution that promises you safety in a city. Repeated failures would make you lose faith in the promise of security implicit in many societies today. You might move to a different location, and definitely buy yourself a weapon for protection. In short, you would try disentangling from one area of your interaction with society.

Now, as people who turn to the media to locate ourselves in a social space, we are strongly influenced by the books we read, the songs we hear, and the news we view. A newspaper is a good source of information about a politician’s opinions, a voice recording of her is better, but a live feed of her saying something is closest to the best basis for trusting that she actually said it. Why? Because our eyes and ears combine to form the primary points of input for our experiences, and short of actually interacting with people face-to-face, videos are the best simulations of “being there.” That is not to say that skepticism and critical thinking are not important to being educated consumers – we should question the truth and implications of a politician’s position. But, historically, we could distrust an equivocator without qualms about the way we heard her hedging. Our faith in the medium remained.

The moment we reach manipulation technologies like deepfakes, however, a gateway into a world where no one can ever know if someone said something or not opens up. Suddenly, our trust in social institutions of communication begins to evaporate.

Hence, lawmakers in America are scrambling to regulate deepfake technologies. Why, inductively, notable figures across science and programming are worrying about the numerous ways artificial intelligence could harm society. Because they have the potential to fundamentally alter our experience of reality on an unprecedented scale, with unbelievable speed – in fact, the term “deepfake” is only a few years old and the technology has only existed for five years. And the fear everyone has of progress pursued without conscience or broader consideration is amplified in the interconnected present, where rapid, mass consequences arise from limited, specialist development. It is the same fear that made Plato distrust the memory-weakening potential for writing in Phaedrus or the Luddites destroy the job-stealing industrial machines – that of the price of progress. For technology to change lives, it must bury the way life was once lived.

 Deepfakes, on a philosophical level, destabilize the trust in truth essential for us to know things or even believe in our ability to know things. They give people the power to make anyone say anything. And if anyone can say anything, then we might as well say nothing at all – or stop listening, at the least. Because a functioning society needs people to trust people. It needs some truth. And that is getting harder to find with each passing day. In this sadder sense, deepfakes are a natural extension of the post-truth world of alternative facts, a rabbit-hole that goes all the way down to artificially intelligent robots that can look like your favorite pop star or a notorious demagogue, spewing hate or inciting violence in-person. A sorry sight indeed. Regardless, it is unlikely technology will slow down. Between progress and the past, we only look back, never turn.

In such tumultuous times, the only way to resist a breakdown of social order is to build defenses. Governments should incentivize the development of programs that identify deepfakes, the masses must be educated about the existing misinformation threat, and corporations must invest in checks that filter potential fake content before it goes live. The end goal is a practicable ethical framework that preserves people’s faith in the institutions of communication. We must fight the good fight, or risk losing it all.

Karno Dasgupta is a student at NYUAD, majoring in Literature and Creative Writing.

In The Human Condition, Hannah Arendt distinguishes between the categories of “work” and “labor.” She differentiates between two types of human worker: the “homo faber who makes and literally ‘works upon’” and the “animal laborans which labors and ‘mixes with.’” In this conception, work is the creation of some product “which outlasts its own activity and forms a durable addition to the human artifice,” while labor “needs to be reproduced again and again in order to remain within the human world at all.” Arendt concludes this meditation on the nature of work by arguing that art, in her opinion, is the most durable creation that humans can make, and thus the best form of work

How then, might Arendt classify work done by someone like Jing Zi, a young Chinese woman whose job is to live stream herself for 7 hours a day? In a 5-minute documentary video about her done by Noah Sheldon, Jing Zi goes through the motions of her typical content. She puts on makeup, plays with cute video filters, sings karaoke, and eats lunch that one of her fans ordered in for her. The woman is an employee of a media company in Beijing, that hosts other live streamers like her, and provides them with individualized filming sets and promotions in exchange for a percentage of the profit. Jing Zi regularly makes more than 10,000RMB ($1454) a day.

In fact, Chinese live streaming is one of the world’s fastest growing industries: in 2018 the number of users reached 456 million people and Deloitte valued market at $4.4 billion. The Chinese are dedicating their time, love, and money to their favorite streamers in extents that are unfathomable within the Western framework of internet celebrity.

In the West, internet concept creators often follow the “influencer” model of internet celebrity. They post some content on a variety of internet platforms such as Facebook, Twitter, Instagram, and YouTube, and attract a large following of people who engage with their content through comments, likes, and shares. None of these interactions, however, directly earn money for the content creator. Instead, their stream of income is usually a combination of merchandise sales, paid subscriptions on platforms like Patreon, and sponsored advertisements, in which companies reach out to them and provide a flat rate per post based on the number of followers.

Chinese live-streamers, while also trying to amass a large following and often working with advertisers, are in a very different position. Their main source of income is directly built into the platform: viewers during a live stream can buy “gifts” for the streamer, which appear as little animations on the screen in real time, and are purchased with actual currency deposited onto the app account. The streamers tend to respond to the gifts in real time, engaging with the users who pay larger sums and thanking them directly. In some platforms, there are added benefits, such as gaining the host’s contact information after reaching a certain monetary threshold in gifts.

Incomes of the most popular streamers can reach over $100,000 dollars a month, and even the less successful hosts earn many times the average salaries of college graduates in China. Many of these internet celebrities originally come from the working class, but through their popularity are able to obtain rich and lavish lifestyles. Their situation is in stark contrast to the rest of China’s population, as there is very little social mobility in terms of wealth, as the working class do not have the same educational and professional opportunities as the wealthy, who have stayed rich for generations. In fact, many of these working class viewers even impede their financial prospects, as they donate significant portions or even the entirety of their salaries to their favorite live streamers.

This seemingly irrational behavior is caused by the desire to keep one of their own rich, since the working class audiences are well aware that they could never reach those levels of financial success themselves. Furthermore, they are drawn to the live streams to feel less lonely: the changing economic and geo-social makeup of China, especially through increasing urbanization, has left many young people disconnected from their families and communities, and isolated in large but lonesome cities.

The live streams are an attractive form of escapism: hosts mostly stream boring content, like eating on camera, chatting, or simply going about their daily commute. Nonetheless, in some cases viewers tune in for up to 8 hours at a time, spending their entire day in virtual company with likeable hosts.

This particular medium, however, is very unique compared to other popular forms of internet content. Live streams are transient: the video is not recorded or uploaded for potential later viewing, all that exists is the here and now. In Internet Celebrity: Understanding Fame Online, Crystal Abidin writes that such “always-transient content” is “largely motivated by the followers’ cultivations of perpetual ‘FOMO,’ or the ‘fear of missing out.’” The immediacy creates a sense of exclusivity, and heightens the effect of virtual connection between the audience and the hosts.

Can Arendt’s conception of work and labor be applied to this occupation? Live streams do not have inherent market value or practical use. Instead, they are an evolution of other kinds of internet visual content (pictures and videos), which can be viewed as art and are often judged to aesthetic standards that resemble the approach to artistic products. In this case, lack of usability can also be viewed as proof of artistic status. However, the transience of live streams complicates this category. While the hosts technically create something new, the durability lies not in the content itself but in the audience that the content generates. The direct product, the stream, gets consumed in its very process of creation. There is no “true reification,” so this supposedly artistic project becomes a labor process of toiling every day on the clock, the live stream both becoming the means to an end and an end itself that must be repeated ad infinitum.

In this vein, the categories of “labor” and “work” appear insufficient. Perhaps, we should take the new types of vocations that the internet has brought about, such as live streamers, seriously. A different conception of work may be in order.

Ria Golovakova is a senior at NYUAD, majoring in Literature and Creative Writing. She is interested in exploring and writing about the many manifestations of modern culture and how the forces that shape society today may differ from those of the past.