Kyle Chayka, “How The Internet Turned Us Into Content Machines” (New Yorker, 4 June 2022)

W2: Algorithm

Kyle Chayka, Filterworld: How Algorithms Flattened Culture

“Introduction”
“The Rise of Algorithmic Recommendations” (ch. 1)

See also: “The Banality of Online Recommendation Culture” (New Yorker, 30 October 2024)

It can be safely assumed that, for better or worse, in light of the events of the past twenty-four hours the Algorithm is probably the last thing one anyone’s mind right now! Nevertheless, I’m going to black-box the election and its aftermath here and stay focused on the topic at hand: the opening two chapters of Kyle Chayka’s recent book on algorithmic culture, Filterworld.

The chapters themselves are so packed with insights and references to other research sources that I’m not going to add to them here; I’m more interested in hearing your own collective response to them and discussing it with you in the coming week. Instead, I’ll limit myself here to connecting you to some of the sources on which Chayka’s own book is based, which provide an ideal starting point for anyone interested in exploring the subject for your research project later in the course.

As with Kate Eichhorn’s book about content or any of the other texts that we’re going to be dipping into in upcoming weeks, you might also be interested in continuing with the book and writing a review of it for the Book Report assignment due at the end of Week 5.

The first chapter of Filterworld is essentially the extended of mix of several articles that Chayka published as articles on his Substack blog and subsequently in The New Yorker (subscription required) in 2022. The Substack article in particular is worth taking a closer look at because it references a survey that Chayka conducted about algorithmic recommendation systems that received 125 responses. I thought it might be interesting to assign our group to answer some of the questions asked in the survey as a starting point for our discussion.

Here are the main five questions, after those requesting name and contact information. Since chapter 1 of Filterworld provides a definition of the term algorithm itself, I’ve also skipped that one here:

• Has “the algorithm,” or algorithmic feeds, taken up more of your online experience over the years? What has that change felt like?
• Do the algorithms of different platforms / feeds feel very different? Like TikTok vs Instagram, FB vs Twitter, Netflix vs Spotify…
• Have you had any particularly odd run-ins with algorithms or automated recommendations? Maybe it’s eerily accurate Instagram ads (or terrible ones), getting served the same content as a friend, missing a Netflix show, or someone surprising popping up in your feed… Describe anything that comes to mind.
• If you are a creator (artist, musician, writer, YouTuber, whatever), do you ever feel pressure to mold your work in a certain way to fit with an algorithmic feed / platform? What is that pressure like?
• Do you have any hacks / theories as to what makes a piece of content succeed in an algorithmic feed? Any tricks that you use or have used when you just want something to get attention?

You don’t have to answer all of these questions, but for your Review response this week, feel free to select one or two of them if you’d like to respond. If it brings anything to mind, the third question, about random or odd recommendations, might be the most interesting one of the set.

I’m guessing that the section of Chayka’s first chapter (not the Introduction, the second, longer chapter) that you found most interesting is about the concept of algorithmic anxiety, a term that as he explains was used by Kate Crawford in 2013, was developed in Patricia De Vries’s blog (well worth checking out!) for the Institute of Network Cultures website, and was the subject a 2018 academic paper about AirBnB.De Vries herself subsequently explored the subject in her pathbreaking study Algorithmic Anxiety in Contemporary Art (University of Amsterdam, 2020), available as an open-source publication from the Institute’s website.

As Chayka explains, De Vries’s book emerged from her research on contemporary digital artists whose work focuses on surveillance and resistance to this, notably Jill Magid and Trevor Paglen. For a survey of contemporary internet art that includes chaptes on both of these artists, see Lauren Cornell and Ed Halter’s anthology, Mass Effect: Art and the Internet in the Twenty-First Century (Cambridge ,MA: MIT Press, 2015).

De Vries has a number of interesting presentations about internet art and algorithmic culture on YouTube - I’ve created a playlist for the course and have added them to it, and encourage you to take a look. I’ll be adding more YouTube sources to the playlist as the course progresses, so add it to your bookmarks toolbar.

One other source mentioned in Chayka’s chapter on algorithmic recommendations is Taylor Lorenz’s Washington Post article about the concept of algospeak, which I’m also linking to here.

Taylor Lorenz, “Internet ‘algospeak’ is changing our language in real time, from ‘nip nops’ to ‘le dollar bean’” (Washington Post, 8 April 2022).

Taylor Lorenz is also the author of another interesting recent book about contemporary internet culture.

Extremely Online: The Untold Story of Fame, Influence, and Power on the Internet (New York: Simon & Schuster, 2023).

Well that should keep you busy for a week or two! Look forward to discussing the Filterworld chapters and any other of the above sources with you in the coming week!

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