Good points about how technology and distribution affect the creation of music:
For a critic, the question of how listeners acquire and consume new music can feel tangential or tedious—it’s far more exciting, after all, to talk about the music itself—but the two topics are once again becoming inextricably intertwined. Just as the advent of the commercial recording industry (and, later, the evolution of analog recording formats, from wax cylinders to 78-r.p.m. disks and long-playing vinyl records) changed the way musicians write and produce songs, so, too, has streaming. With everything now cleaved from its original time and circumstance (and, it feels worth noting, its cultural and historical context), young songwriters can cull influence from all sorts of disparate sources and make work that feels, somehow, both new and ancient.
The popularity of streaming has led to obvious changes in how music is being produced—in 2018, a pop song needs to sound excellent piping out of a laptop’s tiny speakers and on headphones—but streaming has also resurrected the idea that the medium through which an album or track is made available is as much an aesthetic choice as anything else. This past fall, on the first day of an undergraduate seminar I teach on musical subcultures, I asked my first-year students what kind of music they liked. More than one answered “SoundCloud.” When I wondered aloud if SoundCloud was actually just an online distribution platform (like Spotify, it allows its users to stream millions of songs for free) and not a genre in any traditional sense of the word, I received only blank or vaguely pitying stares, as if I had just ordered everyone to check their telegrams for news about the space race. Since SoundCloud was founded, in 2007, it has slowly become synonymous with a tender but scrappy style of rap music, as practiced by artists such as Lil Pump, the late Lil Peep, and XXXTentacion. The sound is garbled and sometimes anesthetized, but, mostly, its brazen laziness feels like a corrective to overproduced and overconsidered mainstream hip-hop. That these artists gathered on SoundCloud might be incidental to SoundCloud itself (I think it would be hard to argue that the company deliberately courted or curated them), but it nonetheless reminds me of when I was a teen-ager, and we often casually referred to labels as genres: you liked Dischord stuff, or Saddle Creek stuff, or Thrill Jockey stuff, and so on. The method of distribution mattered.
Spotify has yet to foster a creative community in the same way. It’s far too big to feel like anything other than an anonymous platform—its library already seems terrifyingly boundless, and is only growing.
A bit of the Echo Nest history and Discover Weekly:
Whitman was fascinated by the way people describe and write about music. He once studied Pitchfork reviews to measure their ratio of actual music criticism to personal musings about the writers’ lives. (“It was the style at the time,” he says now, diplomatically.) Was there a way to convert this flowery writing into usable data? If a music critic or a kid on a random blog wrote that a new indie band sounded like “David Bowie when he was in Berlin,” Whitman wanted to craft a way to algorithmically map that connection. “I wanted to have some computer program read the same thing I was reading,” he says.
Jehan (who prefers jazz to electronic) opted for a more technical approach. He was interested in deconstructing music itself, analyzing the digital signals of waveforms to categorize types of sounds. While at MIT, he developed the James Brown Machine, a computer program that, as its title implies, can compose “new” James Brown songs. After being fed dozens of actual tracks by the soul star, the computer attempts to algorithmically derive the “essence” of James Brown and output new compositions in the singer’s style. You can judge for yourself how well machine imitates man.
THE SECRET LIVES OF PLAYLISTS (June 2017)
Meet PUMA: Playlist Usage Monitoring and Analysis
Playlist culture is introducing an unprecedented dependence on data. We hear about the stacked human playlisting teams, with “genre leads” and “junior and senior curators” building thousands and thousands of playlists. (Though we never see their faces or names on the platforms—Spotify’s way of building trust in the mystified Oz-like “magic” of Spotify, rather than human intelligence needed to program playlists.) These human curators are responding to data to such an extent that they’re practically just facilitating the machine process. As BuzzFeed reported last year, Spotify uses a performance tracking application titled PUMA, or Playlist Usage Monitoring and Analysis, which “breaks down each song on a playlist by things like number of plays, number of skips, and number of saves.” PUMA also tracks “the overall performance of the playlist as a whole, with colorful charts and graphs illustrating listeners’ age range, gender, geographical region, time of day, subscription tier, and more.” In the “human curated” playlist factories, human beings essentially reproduce the work of the algorithm.
Why are so many Netflix movies so bad? (March 2018)
The medium shaping the content, again:
It’s not that these Netflix movies can’t be enjoyed while you are distracted by your phone or your tablet; it’s that they are undeniably better that way. Paying attention to Bright will only make the film worse by exposing the vast holes in the plot and how little the film’s central metaphor actually matters. The only thing that comes from scrutinizing Mute is wondering why a film about an Amish amateur private eye needed to be set in a dystopian science-fiction future. Glancing at these films occasionally, you can admire their cool production design, makeup, and effects without getting lost in the weeds of their goofy plots.