How Music Got Free: The End of an Industry, the Turn of the Century, and the Patient Zero of Piracy
by Stephen Witt · 15 Jun 2015 · 315pp · 93,522 words
’s real achievement was figuring out that you could run this process iteratively. In other words, you could take the output of his bit-assignment algorithm, feed it back into the algorithm, and run it again. And you could do this as many times as you wished, each time reducing the number
New Laws of Robotics: Defending Human Expertise in the Age of AI
by Frank Pasquale · 14 May 2020 · 1,172pp · 114,305 words
that the parents had made the whole massacre up), something is deeply wrong online. The core problem is a blind faith in the AI behind algorithmic feeds and a resulting evasion of responsibility by the tech leaders who could bring bad actors to heel. Tech behemoths can no longer credibly describe themselves
The Big Fix: How Companies Capture Markets and Harm Canadians
by Denise Hearn and Vass Bednar · 14 Oct 2024 · 175pp · 46,192 words
and manipulating it for the benefit of multibillion-dollar firms. Social media has brought many benefits and connected the world as never before, but curated algorithmic feeds also led to rampant disinformation and electoral interference, increasing political polarization, and severe negative effects on the mental health of young teens and children. Our
Filterworld: How Algorithms Flattened Culture
by Kyle Chayka · 15 Jan 2024 · 321pp · 105,480 words
it, is how tech companies monetize the constant absorption of our personal data, an intensification of the attention economy. And yet for all that data, algorithmic feeds oftentimes misunderstand us, connecting us to the wrong people or recommending the wrong kinds of content, encouraging habits that we don’t want. The network
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. THE FLATTENING OF CULTURE In order to understand how Filterworld shapes our experiences, we have to understand how it came to be. The dominance of algorithmic feeds is a relatively recent phenomenon. In the early days of social networks like Twitter, Facebook, Instagram, and Tumblr, the sites’ content feeds were more or
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consequences but to deconstruct it. In doing so, we can determine ways to escape it and resolve the omnipresent atmosphere of anxiety and ennui that algorithmic feeds have produced. We can dispel their influence only by understanding them—by opening the cabinet of the Mechanical Turk to reveal the operator inside. CHAPTER
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created different tunes each time the software ran. Lovelace was envisioning how culture could be both molded and perpetuated by the new technology, the way algorithmic feeds do today. Lovelace was early in discovering that manipulating such mechanical commands could be its own form and self-expression. In the 1990s and 2000s
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machine. The differences between platforms became more prominent and more relevant moving into the mid-2010s, as social media and streaming services doubled down on algorithmic feeds and they began to dominate the user experience. We users fundamentally do not understand how algorithmic recommendations work on a day-to-day basis. Their
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then present it in a coherent way. Recommendations were the goal: recommending a piece of information, a song, an image, or a social media update. Algorithmic feeds are sometimes more formally and literally labeled “recommender systems,” for the simple act of choosing a piece of content. The first wholly mainstream Internet algorithm
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social network environment are monitored, and those interactions are used to select additional items of media content for the user. All the elements of the algorithmic feed are present in this passage—a system that anticipates a piece of content’s relative importance to an individual user, determined by surveillance of content
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data points; they are collections of data packaged and interpreted in specific ways by Facebook. It’s hard to track the evolution of Facebook’s algorithmic feed because it is constantly updated, and the company reveals details only intermittently. What we do know about it beyond official announcements comes down to investigative
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people on these platforms, every interaction, every moment of passive consumption, is mediated by algorithmic recommendations. Even if some users can opt out of an algorithmic feed, their participation contributes to the data that fuels other users’ recommendations. The dragnet is inescapable. Social networks and streaming services have become the primary way
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the next provocative news headline or hypnotic entertainment release. Today, it is difficult to think of creating a piece of culture that is separate from algorithmic feeds, because those feeds control how it will be exposed to billions of consumers in the international digital audience. Without the feeds, there is no audience
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—the creation would exist only for its creator and their direct connections. And it is even more difficult to think of consuming something outside of algorithmic feeds, because their recommendations inevitably influence what is shown on television, played on the radio, and published in books, even if those experiences are not contained
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, for a piece of culture to be commercially successful, it must already have traction on digital platforms. Boffone’s career, too, has been shaped by algorithmic feeds. When he began learning TikTok dance moves with his teenage students and posting videos of them online, he quickly accrued hundreds of thousands of followers
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this year in my work than in the previous ten years combined,” Boffone told me. Boffone’s experience follows a fundamental rule of Filterworld: Under algorithmic feeds, the popular becomes more popular, and the obscure becomes even less visible. Success or failure is accelerated. “A traditional Instagram post, the life of it
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as early as 2013, when she saw several museum exhibitions highlighting the work of artists who were critical of automated surveillance and data collection. While algorithmic feeds had only just begun entering mainstream experience, events like the 2010 Flash Crash, caused by algorithmic stock trading, and technology like facial recognition had implanted
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time to engage with, and benefits from the surprise that comes from the unfamiliar, then it seems that technology could not possibly replicate it, because algorithmic feeds run counter to these fundamental qualities. When recommendation algorithms are based only on data about what you and other platform users already like, then these
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the Internet makes what other people are consuming so immediately public. (If you didn’t post about it, did you really watch a TV show?) Algorithmic feeds further reinforce the presence of that mainstream, against which our personal choices are evaluated. Taste is inescapable; it involves “the most everyday choices of everyday
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most fertile ground for culture. While the magazine fashion editor may periodically use their ability to pick out and promote a previously unheard voice, the algorithmic feed never will; it can only iterate on established engagement. We users have less chance of encountering a shockingly new thing and deciding for ourselves if
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the social code: wearing something unexpected or strange, even at times challenging your own taste. It’s something that no automated recommendation alone can approximate. Algorithmic feeds are a double-edged sword: A marginalized fashion designer might find a way to game the Instagram algorithm and spark their own popularity without waiting
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it—has never been so influenced by data and the granular measurement of attention. AMBIENT CULTURE While Nigel Kabvina thrives on the pressure of an algorithmic feed and keeps surfing it to higher follower numbers and opportunities for sponsored content, the same forces are acting on all kinds of creators. Just as
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in through AirPod headphones provide ambient chatter, noise that represents social stimulus without real-life social contact. In so many cases, the culture disseminated through algorithmic feeds is either designed to produce a sensory void or to be flattened into the background of life, an insidious degradation of the status of art
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the new network of digital geography, wired together in real time by social networks. They were authentic to the Internet, particularly the 2010s Internet of algorithmic feeds. In 2016, I wrote an essay titled “Welcome to AirSpace” for the Verge, describing my first impressions of this phenomenon of sameness. “AirSpace” was my
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cultural discussions of the day. The 2016 election of Donald Trump, a hyperactive Twitter user, as president was likely the turning point. Not only were algorithmic feeds becoming more pervasive, but social networks became host to the parallel public-opinion battles of “the resistance,” the loose liberal coalition against Trump that adopted
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hardcore fans’ desires—but the end result is close to meaningless in terms of emotional impact or creative expression. Rather than encouraging original artistic achievement, algorithmic feeds create the need for content that exists to generate more content: films that provide ready-made GIFs of climactic scenes to share on Twitter or
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trending topic. Things start out with genuine interest, but by the thousandth video about it, it has nothing to do with the thing itself.” The algorithmic feed alienates the superficial symbol of the book from its actual value as literature. Algorithmic curation can alienate consumers, too. Eleanor Stern, a writer and recent
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, for example, but can’t alter the equation of the recommendation algorithm. We don’t have enough alternative options to navigate the Internet outside of algorithmic feeds, in part because the Internet is now so dominated by just a few companies. STRUCTURAL MONOPOLIZATION Our experiences online today are heavily centralized. Consumers are
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content, particularly as it opened up to non-college populations. Friends’ status updates became interspersed with group notifications, news articles, and advertisements, filtered by the algorithmic feed. The company pioneered this kind of collision of content, less because users demanded it and more because it served its own interests—like Walmart or
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biggest incumbent could be threatened by a tiny newcomer, simply because of a slight technological evolution—like Snapchat’s ephemeral posts or TikTok’s wholly algorithmic feed—or the unavoidable fact that people simply get bored, and technology, like fashion, must constantly change to maintain its hold over its users’ attention. Still
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, let alone stability, because Twitter had no real responsibility to its users. PUBLISHING VERSUS PROMOTING Just as digital platforms aren’t responsible for explaining their algorithmic feeds, they also don’t take responsibility for what the feeds promote—they separate themselves from the outcomes of their recommender systems. They can do that
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of millions of people consume all forms of media, from entertainment to news. Social networks displaced traditional publishers by absorbing advertising revenue; siloing content into algorithmic feeds; and mediating the relationship between publishers and their consumers. The consequence is that traditional media companies have been decimated, losing most of their revenue when
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for the consequences of their intentional ranking decisions, I think they would get rid of engagement-based ranking,” Haugen told a Senate panel in 2021. Algorithmic feeds help automatically distribute misinformation and can speed ideological radicalization, feeding users ever more extreme content in a single category. The problem with Section 230 is
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companies themselves aren’t liable, the systems are only regulated internally, and users are left to fend for themselves, short of basic content moderation. If algorithmic feeds mistreat us or contribute to an abusive or exploitative online environment, we, as users and citizens, have little recourse. One of our only possibilities is
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level. Regulation offers political solutions for what is often observed as a political problem. It’s true that some of the most visible problems of algorithmic feeds broach the political, with issues of free speech, harassment, technologically encoded bias, and industrial capitalism. But in Filterworld, the feeds impact more mundane aspects of
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apartment for unusually late-night, unusually long dog walks. In the following weeks, I discovered that the Internet wasn’t really designed to function without algorithmic feeds anymore. These feeds worked like vital shipping lanes, ensuring various forms of content reached their intended targets without either the creator or the consumer having
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and physical are constantly mediating our interpersonal relationships. An entire philosophy was encoded in the unpretentious and yet rigorous way that Antonelli ordered her selections. Algorithmic feeds, in fact, could fit in as objects in that exhibition. On the appointed day, I took the Amtrak train from D.C. to New York
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that follows, the curator’s selection stimulates our senses to consider what’s in front of us. This kind of holistic sensitivity is something an algorithmic feed is incapable of replicating. To explain her approach, Antonelli walked me into gallery 216, which mingles design and architecture with some visual art, featuring many
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space,” Antonelli said. (An apt description of Filterworld as a whole, where nothing stands out.) “That’s where the algorithm becomes your antagonist,” she continued. Algorithmic feeds disrupt curated juxtapositions and make it that much harder to interpret the broad swath of culture, to figure out which themes join things together and
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over ambient synth washes.) Just like the generic Instagram design aesthetic of minimalist interiors, music has settled into a generic style under the pressure of algorithmic feeds. “Everything sounds like a loop, with one-dimensional sounds. Rhythm is a more dominant characteristic than melody,” Cavalconte said, citing the “bedroom pop” of Billie
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sense to restrict access. As social networks emerged, companies like Facebook, Twitter, and YouTube absorbed more of the advertising revenue by capturing users’ attention with algorithmic feeds and selling their own ads, forcing creators and publishers to game the system. Only in recent years have we begun to realize that selling attention
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intimidating even than listening to a classical radio station. It is very much possible to host enormous bodies of culture online without the help of algorithmic feeds; after all, culture itself offers a kind of algorithm to follow, as each artist influences and inspires others, referencing and building on history. Those are
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itself was wholly unprecedented.) Sony sold hundreds of thousands of them. Suddenly, music could envelop the listener wherever they went, whichever music they chose. Like algorithmic feeds, the Walkman was a dramatic form of personalization. In a 1984 article for the journal Popular Music titled “The Walkman Effect,” the Japanese musicology scholar
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has become unremarkable can its effects be judged. We see the same process happening in our own time with the globalization of digital platforms and algorithmic feeds, an inextricable pair of technologies that change our perceptions just as the invention of photography did. Culture has to follow the dominant modes of perception
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era. While a twentieth-century building might have been designed to be photographed, the twenty-first-century work of art is “designed for reproducibility” through algorithmic feeds, like Patrick Janelle’s cortado glamour shots on Instagram or Nigel Kabvina’s cooking videos on TikTok. They each contribute and conform to a generic
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people deciding to abstain. In the meantime, by the dictates of capitalism, Filterworld is required to grow constantly. To plateau or shrink is to fail. Algorithmic feeds are different from other iterations of technological innovation because they do not just present us with an unusual new format to consider, like camera film
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screen. They also try to anticipate our individual cultural desires for us in personalized recommendations using the newfound tools of data surveillance and machine learning. Algorithmic feeds stand between the human creators and the human consumers, making an infinite series of decisions about culture. The technology has never been applied so widely
Twitter and Tear Gas: The Power and Fragility of Networked Protest
by Zeynep Tufekci · 14 May 2017 · 444pp · 130,646 words
protests, but the algorithm was not showing the story to me. It was difficult to assess fully, as Facebook keeps switching people back to an algorithmic feed, even if they choose a chronological one. As I inquired more broadly, it appeared that Facebook’s algorithm—the opaque, proprietary formula that changes every
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and why they see it. Broadcast television can be monitored by anyone to see what is being covered and what is not, but the individualized algorithmic feed or search results are visible only to their individual users. This creates a double challenge: if the content a social movement is trying to disseminate
Better Living Through Criticism: How to Think About Art, Pleasure, Beauty, and Truth
by A. O. Scott · 9 Feb 2016 · 218pp · 65,422 words
crediting the real difficulty of being right. The desire for a shortcut—whether in the form of an unshakable worldview or a set of nifty algorithms—feeds the suspicion that every assertion is a scam, and is therefore vulnerable to simple debunking. The essential modesty and rigor of the scientific method is
No Filter: The Inside Story of Instagram
by Sarah Frier · 13 Apr 2020 · 484pp · 114,613 words
time Taylor Swift, in a crisis on the site. (Instagram might have resolved to prioritize its regular users in product builds, with changes like the algorithmic feed, but it was still listening intently to celebrities about their needs, reasoning that doing so was good for the brand, as the celebs’ problems also
Zucked: Waking Up to the Facebook Catastrophe
by Roger McNamee · 1 Jan 2019 · 382pp · 105,819 words
personalization, interactivity, sharing, or groups. In the context of Facebook, filter bubbles have several elements. In the endless pursuit of engagement, Facebook’s AI and algorithms feed each of us a steady diet of content similar to what has engaged us most in the past. Usually that is content we “like.” Every
Ten Arguments for Deleting Your Social Media Accounts Right Now
by Jaron Lanier · 28 May 2018 · 151pp · 39,757 words
the most common form of online myopia is that most people can only make time to see what’s placed in front of them by algorithmic feeds. I fear the subtle algorithmic tuning of feeds more than I fear blatant dark ads. It used to be impossible to send customized messages to
Facebook: The Inside Story
by Steven Levy · 25 Feb 2020 · 706pp · 202,591 words
Netflix, 171, 175, 239 net neutrality, 233 network effect (Metcalfe’s law), 67 News Feed of FB advertisements in, 138, 181, 295–98, 475, 477 algorithms feeding and filtering, 127–28, 142, 163, 172, 260–61, 385, 391 and Cambridge Analytica, 399 and content publishers, 387–90, 391 criticisms of, 385–86
This Is for Everyone: The Captivating Memoir From the Inventor of the World Wide Web
by Tim Berners-Lee · 8 Sep 2025 · 347pp · 100,038 words
The Twittering Machine
by Richard Seymour · 20 Aug 2019 · 297pp · 83,651 words
Programming Collective Intelligence
by Toby Segaran · 17 Dec 2008 · 519pp · 102,669 words
Hands-On Machine Learning With Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
by Aurélien Géron · 13 Mar 2017 · 1,331pp · 163,200 words
Enshittification: Why Everything Suddenly Got Worse and What to Do About It
by Cory Doctorow · 6 Oct 2025 · 313pp · 94,415 words
Messing With the Enemy: Surviving in a Social Media World of Hackers, Terrorists, Russians, and Fake News
by Clint Watts · 28 May 2018 · 324pp · 96,491 words