Latest news with #LizPelly
Deccan Herald
2 days ago
- Entertainment
- Deccan Herald
What fills your silences?
In Mood Machine: The Rise of Spotify and the Costs of the Perfect Playlist, Liz Pelly writes about Spotify from multiple angles: from the perspective of artistes, record labels, Spotify execs, and listeners.
NDTV
11-05-2025
- Entertainment
- NDTV
Spotify's Secret Scheme Of Ghost Artists And Fake Playlists To Slash Royalties Revealed
Spotify has been promoting ghost artists to avoid paying royalties to real artists, a report in Futurism, citing a new book, has claimed. In an excerpt from the book, Mood Machine: The Rise of Spotify and the Costs of the Perfect Playlist, author Liz Pelly revealed that the Swedish music platform has a secretive internal programme that prioritises cheap and generic music. The programme called Perfect Fit Content (PFC) involves a network of affiliated production firms and a team of employees secretly creating "low-budget stock muzak" and placing them on Spotify's curated playlists. First piloted in 2010, PFC became Spotify's biggest profitability scheme by 2017. As per Ms Pelly, by engineering such a situation, Spotify was aiming to grow the percentage of total streams of music that is cheaper for the platform. "It also raises worrying questions for all of us who listen to music. It puts forth an image of a future in which, as streaming services push music further into the background, and normalise anonymous, low-cost playlist filler, the relationship between listener and artist might be severed completely," she wrote. By 2023, the team overseeing the PFC model were responsible for hundreds of playlists. More than 150 playlists with titles such as "Deep Focus", "Cocktail Jazz" and "Morning stretch" were populated entirely by PFC content. One of the jazz musicians told Ms Pelly that he was approached by Spotify to create an ambient track for an upfront fee of a few hundred dollars. However, he was told that he wouldn't own the master rights to the track. The musician agreed, but once the track started raking in millions of streams, he realised he may have been duped. 'Soulless music' Social media users slammed Spotify for the move, with many stating that the platform was digging its own grave with such actions. "Going to be nothing but soulless AI music in a few years. That's one easy way to never pay royalties again lol," said one user, while another added: "Once you notice these artists it's pretty easy to ID them even just from listening to the music." A third commented: "I deleted my Spotify and cancelled the subscription." This is not the first instance when Spotify has come under scrutiny for its shady activities. In February, a report in The Guardian highlighted that Spotify's Discovery Mode allowed artists to be noticed by listeners in exchange for a 30 per cent royalty reduction.
The Guardian
12-03-2025
- Business
- The Guardian
Spotify is trumpeting big paydays for artists – but only a tiny fraction of them are actually thriving
Since 2021, Spotify has published its Loud & Clear report, corralling data points to show how much money is being earned by artists on the streaming service. There is much talk of 'transparency' – perhaps the most duplicitous word in the music industry's lexicon – but this year's report feels very different, coming as it does alongside the publication of author Liz Pelly's book Mood Machine, a studs-up assault on streaming economics in general and Spotify in particular. Then there is the unfortunate timing of the news, as recently unearthed by Music Business Worldwide, that Spotify co-founder and CEO Daniel Ek has cashed out close to $700m in shares in the company since 2023 while Martin Lorentzon, the company's other co-founder, cashed out $556.8m in shares in 2024 alone. Meanwhile artists scream of widening financial inequalities and accuse streaming services of doing better from artists than artists are doing from streaming services. So there's a strange tang to the numbers being pushed today, as Spotify announces its 2024 report. 'We think [the report] helps us contribute to the larger understanding of what happened in music the year before,' says Spotify's Sam Duboff, who carries the unwieldy title of global head of marketing & policy, music business. It does contribute in that way, but only to a point. Loud & Clear, just like Spotify Wrapped each December, is a marketing tool, trumpeting just how fantastic Spotify is. It proffers multiple talking points, the biggest being that Spotify – which claims it holds a quarter of the recorded music market globally – paid out $10bn in royalties last year (and almost $60bn in its lifetime). Duboff says 2024's report is 'particularly symbolic, because it's exactly 10 years after the low point of the recorded music industry', when downloads had failed to fill the void created by the collapse of the CD market and the rise of piracy. He says Loud & Clear aims to show 'how many more artists are able to participate in the massive royalty pools' generated by streaming. $10bn is a hefty number, but it needs to be closely examined. This money, around two-thirds of its total income, is what Spotify has paid through to record labels and music publishers. Spotify cannot be held responsible for egregious label and publisher contracts, but it needs reiterating that only a portion of that $10bn will make its way to the people who wrote and recorded the music. The company also says this $10bn is 'more than any single retailer has ever paid in a year' and is '10x the contribution of the largest record store at the height of the CD era'. That may be true, but it says less about Spotify's benevolence and more about how streaming's market share has mostly consolidated into the hands of four global heavyweights – Spotify, Apple, YouTube and Amazon. Don't like those numbers? Spotify has others. Some land well. Others, when contextualised, land like a cake flung from the top of a skyscraper. As with live music, a handful of megastars are sponging up most of the money. There are now over 200 artists each generating over $5m a year from Spotify, up from just one act a decade ago; Duboff says the top 70 acts are generating at least $10m each. We get a better insight into the hard scrabble for smaller artists when Spotify says its 10,000th-ranked artist generated $131,000 last year – up from $34,000 a decade ago – and that 1,500 acts each generated over $1m in royalties in 2024. This is a heartening rise, but last year, Spotify said there were 225,000 'emerging or professional recording acts' (its terminology) on the service globally. That means just 4.4% of professional or near-professional acts stand a chance of generating at least $131,000 a year, while 0.6% are in with a shot of generating $1m or more. A solo act at this level might be encouraged by the potential income, but a band with four or five members will need to heavily rely on income from gigs and merchandise. Spotify has asserted that 2024 was 'another record year' for songwriters, with $4.5bn paid to music publishers (who distribute royalty payments to songwriters) over the past two years. But given Spotify has been accused in the US, by the Mechanical Licensing Collective (MLC), of trying to reduce its payments to songwriters by reclassifying its premium subscriptions as 'bundles' as they contain access to audiobooks, this claim will not be warmly welcomed by everyone. The MLC took legal action last May but in January this year a judge granted Spotify's motion to dismiss the lawsuit. 'The court agreed that Spotify Premium's definition as a bundle was accurate,' says Duboff. 'We added audiobooks, which has been a huge value to subscribers a year or two ago. All four major streaming services operate bundles and we're no different.' To Spotify's credit, it publishes this report annually to allow everyone to pick through some of its (albeit carefully curated) numbers. None of the other streaming services do this, and record labels most certainly do not. 'Five years in, we always pictured all the streaming services would start reporting data like this,' says Duboff. 'It's a knowable fact how much each streaming service is paying out to the music industry. And we think artists deserve to know what the revenue opportunity on each platform is. It's crazy to me in 2025, with the amount of data available on the internet, that there still is so much that's opaque in the music industry.' The music industry creates and benefits from this lack of transparency. Without record labels and publishers revealing exactly how much of this money flows to artists, Loud & Clear's numbers feel like fireworks sent up to draw our attention away from tombstones.
Yahoo
11-02-2025
- Entertainment
- Yahoo
The Paradox of Music Discovery, the Spotify Way
Your preferred video-streaming service depends largely on what you want to watch—but what you want to watch won't always stay in view. Series and movies hop from platform to platform as rights lapse or get awarded to higher bidders; even streamers' homegrown offerings can disappear to free up bandwidth or save on licensing fees. By comparison, music-streaming services are bastions of stability—and because music streamers generally offer the same catalog, barring the occasional protest, they have to differentiate themselves in other ways. Tidal and Qobuz trumpet their hi-fi offerings; YouTube Music infuses its catalog with the output of the world's largest video site; Apple Music offers a karaoke mode. And Spotify has its playlists. In Mood Machine: The Rise of Spotify and the Costs of the Perfect Playlist, a new book from the journalist Liz Pelly, the playlist is the locus for many of Spotify's troubling practices. Pelly began her project after a music-industry contact suggested that she investigate how the company's official playlists were shaped by the major labels. The book's title suggests a critical corporate biography, but it's more like a siege campaign, with Pelly pounding away at nearly every aspect of Spotify's business: its rosy origin story, its entanglements with the big recording companies, the power dynamic of its relationship with independent artists. Her biggest swings are aimed at Spotify's recommendation framework: the back-end machinations that silently power the playlists available to its 600 million users. You may not agree with Mood Machine that Spotify's mixes are an existential threat to the way people discover music, but you may marvel at how much effort goes into recommending a song that sounds like a different song you liked three months ago. The company brands itself as the ultimate curator, which is amusing considering that, for years after its 2006 founding, Spotify had little interest in playlists at all. Initially, Pelly says, the company was content to let its subscribers (and a galaxy of third-party music-discovery services) churn out genre guides and road-trip soundtracks. By 2013, Spotify users had created 1 billion playlists. That year, Spotify acquired the playlist company Tunigo, registering a shift in its marketing strategy. On top of access to its library—which, again, was practically the same as its competitors'—Spotify was now offering expertise. Millions of people started to follow professionally curated playlists such as Viva Latino and RapCaviar, which were constantly updated with the buzziest tracks. In 2015, Spotify rolled out Discover Weekly, its personalized recommendation playlist; the next year, users began receiving up to six personalized playlists a day. All of this may have felt like a bounty to anyone who came of age when discovering music was much more difficult. Before the internet, the methods of finding new sounds were decentralized and not equally accessible: terrestrial radio, cable television, music magazines, cool older sisters. Maybe your town could support an alt-weekly with a robust arts section; maybe it had at least one independent record shop. But any approach would cost money and time. Often, you would hear a cult artist or album praised in the most compelling language—and because you couldn't actually find the music in the real world, it would remain an object of speculation for years. Spotify wasn't created for this type of obsessive. Initially, it wasn't created for any music fans. As Pelly notes, the business started like many other 21st-century tech companies: as an ad service looking for a delivery mechanism. ('Should it be product search? Should it be movies, or audiobooks?' Spotify's co-founder Martin Lorentzon, who made his fortune in affiliate marketing, is quoted as recalling.) Other streaming services such as Imeem, PressPlay, and Spinner had tried countering the pay-to-own model of Apple's iTunes Store. The major labels negotiated tentative treaties with these early players, capping monthly streams and making only some of their content available. But by the mid-2000s, it was clear that these were merely half measures. Spotify settled on its model at just the right time: Reeling from plummeting CD revenue and the rise of file sharing, the music industry was suddenly open to software offering access to tens of millions of songs, engineered to play tracks instantly and without limits. The major labels signed over their libraries in exchange for massive concessions: dedicated advertising space, guaranteed minimum revenues, shares in Spotify's business. The biggest labels—Sony, Universal, and Warner—were betting that Spotify could make a product more compelling than piracy. The bet paid off. As Spotify became the most successful music streamer on Earth, the American music industry stanched the bleeding, and revenues rebounded to pre-internet levels. Once Spotify built its audience, it wanted to keep users on its app as long as possible. According to Mood Machine, the company's data indicated that a huge portion of its streams came from 'passive listening,' an increasing percentage of which involved functional music: songs designed to enhance everyday activities—meditation, answering emails, even sleeping—without sticking out too much. Where other services had experimented with exclusives from pop A-listers, Spotify's playlist editors began churning out 'chill' mixes populated with songs from mostly anonymous ambient- and instrumental-hip-hop producers. These artists found that placing the right song on the right functional playlist could pay their rent, though a 'hit' rarely implied an active fandom outside the platform. Playlists enabled musicians to earn a living without cutting in record labels or PR pros, one former editor tells Pelly, 'but that didn't help them fill a one-hundred-fifty-cap venue or sell merch.' [Read: The diminishing returns of having good taste] The great chill-out boom is just one stop on Mood Machine's fascinating history of Spotify's official playlists. At first, they were made by professionals hired for their taste and judgment. In 2017, Spotify introduced 'algotorial' playlists, a slightly knotty process through which the company's algorithms generated a pool of songs based on their particular emotional and sonic qualities, editors whittled these songs into a manageable playlist, and the algorithms then sorted these editor-selected songs into an ideal order. Noting the popularity of TikTok's 'For You' feed, Spotify leaned even harder into algorithmic recommendations. Click on a mood-focused or genre-specific mix, and you'll usually get a version that was 'picked just for you.' In practice, this means tracks that share enough of those characteristics with tracks you've already played. In a data-drunk era, this is what passes for discovery. Like so many other products influenced by machine learning, Spotify's playlists can't generate something new—say, a wholly fresh and unheard sound—for its users. They instead offer the flash of recognition, rather than the mind-scrambling revelation that comes only when you hear something you'd never expected. Because they're all drawing from the same massive catalogs, the music streamers are conduits—between artist and listener, or listener and song. In a library north of 100 million tracks, you'd think it would be easy work finding candidates for playlists such as 'lofi autumn beats' and 'Bossa Nova Dinner.' But around 2016, as Mood Machine details, Spotify developed the Perfect Fit Content initiative, partnering with licensing companies that paid studio pros to bang out easy-listening ditties for the streamer—in essence, replicating popular playlist sounds on the cheap. (Spotify has not disputed the existence of the PFC program.) In recent years, Spotify developed its Discovery Mode program, in which labels exchange a portion of a song's royalties for priority status on an algorithmically generated playlist—with no disclosure to the listener. Pelly argues convincingly that this is the streaming version of payola: the illegal practice of promoting songs on the radio without disclosing the payment. (Payola laws apply only to terrestrial radio stations.) But in a crowded marketplace with fewer revenue streams, enough artists enrolled that, according to Pelly's reporting, Spotify's internal Slack channels were lit up with glee. Mood Machine is at its most compelling when peeking into Spotify's internal strategies and its employees' real-time reckoning with their implications. This is also where Pelly overplays her hand. In the conclusion, she analyzes two alternatives to the Spotify model: streaming services run by public libraries, and cooperatives of independent musicians. Spotify's playlists—atomized, contextless—clearly run counter to her ethos, which is rooted in community building and intentional listening. 'At a certain point, a streaming listener may very well come to believe that what the machine suggests is indeed what they like, not because it's true, but because they can see or feel no other option,' she writes. But less clear is whether the company's playlists are truly changing how the median listener approaches music discovery. Users are still generating hundreds of millions of their own playlists, mined from one of the largest collections of songs available in history. Mood Machine persuasively demonstrates how Spotify guides its users down certain roads—but it's not impossible to choose a detour. [Read: Spotify doesn't know who you are] Today, Spotify boasts that one-third of its users' discoveries come 'via personalized recommendations in algorithmic contexts.' Like video streamers' triumphant press releases about how many hours were spent watching their 'hit' movies, the statement strains credulity. Is a discovery a song the user favorites—or just doesn't skip? And how could Spotify possibly know if someone had never heard a given song before? In any event, the company's cited percentage is eerily similar to one given in its 2018 IPO filing, which Pelly summarizes: 'Spotify-owned playlists, both editorial and algorithmic, then accounted for over 31 percent of users' listening'—less than half of all listening done through playlists. In raw minutes, that's a staggering sum. But even by Spotify's accounting, it's just one part of the streaming user's diet—often supplemented, still, with radio and physical media. At one point, Pelly gives a potted history of Muzak, drawing sharp parallels between Spotify and the bygone mood-music purveyor: their self-serving audience research, their tendency to generate palatable versions of the now sound. Anonymous label owners share concerns about Spotify promoting 'emotional wallpaper' and 'the watered down pop sound'; Pelly accuses the company of merely 'filling the air to drown out the office worker's inner thoughts.' The possibility that this office worker might click on a playlist of more interesting sounds—say, amapiano or noise-pop—is not the book's concern. Neither, for that matter, are some of Spotify's more controversial programming decisions that go beyond music—such as its nine-figure deal with the wildly popular podcaster Joe Rogan. (However objectionable prefab piano jazz may be, Rogan's critics would argue that his 'just asking questions' conspiracism has done far more to hurt society than cheap music has.) Still, it would be disingenuous to claim that cloud-based listening hasn't altered music discovery. For the obsessives, the streamers are a sort of last-mile service: a way to dig into something you encountered off-platform. Yet those encounters are becoming rarer. Music-video budgets have tightened, radio playlists have shortened, alt-weeklies and newspapers have closed, and no one's publishing the kinds of comprehensive reference books that used to come from AllMusic, Rolling Stone, and Spin. Some streamers offer openly human curation—Apple's radio stations, Tidal's blog—but that's just one aspect of their role as warehouse, marketer, broadcaster, and guide. There's never been this much music available to this many listeners; the ecosystem for discovery shouldn't feel this fragile or be this centralized. Mood Machine casts Spotify as the apex predator of this new ecosystem, which, according to Pelly, has the same old vulnerabilities. 'The problems faced by musicians,' she writes in the concluding chapter, 'aren't technological problems: they're problems of power and labor.' She's correct that Spotify is not a town square but a walled garden. Although your average music fan will always tend toward legible rather than challenging sounds, a functional cultural scene depends on well-maintained, materially rewarding, and diverse avenues for finding new music. Barring a global data-center failure—admittedly not a remote possibility, with the widespread implementation of AI sucking up more and more energy—the streaming model may be with us for the foreseeable future. We are surrounded at all times by an ocean of sound, but Spotify is content to leave us stranded on our islands. Article originally published at The Atlantic
Atlantic
11-02-2025
- Entertainment
- Atlantic
The Paradox of Music Discovery, the Spotify Way
Your preferred video-streaming service depends largely on what you want to watch—but what you want to watch won't always stay in view. Series and movies hop from platform to platform as rights lapse or get awarded to higher bidders; even streamers' homegrown offerings can disappear to free up bandwidth or save on licensing fees. By comparison, music-streaming services are bastions of stability—and because music streamers generally offer the same catalog, barring the occasional protest, they have to differentiate themselves in other ways. Tidal and Qobuz trumpet their hi-fi offerings; YouTube Music infuses its catalog with the output of the world's largest video site; Apple Music offers a karaoke mode. And Spotify has its playlists. In Mood Machine: The Rise of Spotify and the Costs of the Perfect Playlist, a new book from the journalist Liz Pelly, the playlist is the locus for many of Spotify's troubling practices. Pelly began her project after a music-industry contact suggested that she investigate how the company's official playlists were shaped by the major labels. The book's title suggests a critical corporate biography, but it's more like a siege campaign, with Pelly pounding away at nearly every aspect of Spotify's business: its rosy origin story, its entanglements with the big recording companies, the power dynamic of its relationship with independent artists. Her biggest swings are aimed at Spotify's recommendation framework: the back-end machinations that silently power the playlists available to its 600 million users. You may not agree with Mood Machine that Spotify's mixes are an existential threat to the way people discover music, but you may marvel at how much effort goes into recommending a song that sounds like a different song you liked three months ago. The company brands itself as the ultimate curator, which is amusing considering that, for years after its 2006 founding, Spotify had little interest in playlists at all. Initially, Pelly says, the company was content to let its subscribers (and a galaxy of third-party music-discovery services) churn out genre guides and road-trip soundtracks. By 2013, Spotify users had created 1 billion playlists. That year, Spotify acquired the playlist company Tunigo, registering a shift in its marketing strategy. On top of access to its library—which, again, was practically the same as its competitors'—Spotify was now offering expertise. Millions of people started to follow professionally curated playlists such as Viva Latino and RapCaviar, which were constantly updated with the buzziest tracks. In 2015, Spotify rolled out Discover Weekly, its personalized recommendation playlist; the next year, users began receiving up to six personalized playlists a day. All of this may have felt like a bounty to anyone who came of age when discovering music was much more difficult. Before the internet, the methods of finding new sounds were decentralized and not equally accessible: terrestrial radio, cable television, music magazines, cool older sisters. Maybe your town could support an alt-weekly with a robust arts section; maybe it had at least one independent record shop. But any approach would cost money and time. Often, you would hear a cult artist or album praised in the most compelling language—and because you couldn't actually find the music in the real world, it would remain an object of speculation for years. Spotify wasn't created for this type of obsessive. Initially, it wasn't created for any music fans. As Pelly notes, the business started like many other 21st-century tech companies: as an ad service looking for a delivery mechanism. ('Should it be product search? Should it be movies, or audiobooks?' Spotify's co-founder Martin Lorentzon, who made his fortune in affiliate marketing, is quoted as recalling.) Other streaming services such as Imeem, PressPlay, and Spinner had tried countering the pay-to-own model of Apple's iTunes Store. The major labels negotiated tentative treaties with these early players, capping monthly streams and making only some of their content available. But by the mid-2000s, it was clear that these were merely half measures. Spotify settled on its model at just the right time: Reeling from plummeting CD revenue and the rise of file sharing, the music industry was suddenly open to software offering access to tens of millions of songs, engineered to play tracks instantly and without limits. The major labels signed over their libraries in exchange for massive concessions: dedicated advertising space, guaranteed minimum revenues, shares in Spotify's business. The biggest labels—Sony, Universal, and Warner—were betting that Spotify could make a product more compelling than piracy. The bet paid off. As Spotify became the most successful music streamer on Earth, the American music industry stanched the bleeding, and revenues rebounded to pre-internet levels. Once Spotify built its audience, it wanted to keep users on its app as long as possible. According to Mood Machine, the company's data indicated that a huge portion of its streams came from 'passive listening,' an increasing percentage of which involved functional music: songs designed to enhance everyday activities—meditation, answering emails, even sleeping—without sticking out too much. Where other services had experimented with exclusives from pop A-listers, Spotify's playlist editors began churning out 'chill' mixes populated with songs from mostly anonymous ambient- and instrumental-hip-hop producers. These artists found that placing the right song on the right functional playlist could pay their rent, though a 'hit' rarely implied an active fandom outside the platform. Playlists enabled musicians to earn a living without cutting in record labels or PR pros, one former editor tells Pelly, 'but that didn't help them fill a one-hundred-fifty-cap venue or sell merch.' The great chill-out boom is just one stop on Mood Machine 's fascinating history of Spotify's official playlists. At first, they were made by professionals hired for their taste and judgment. In 2017, Spotify introduced 'algotorial' playlists, a slightly knotty process through which the company's algorithms generated a pool of songs based on their particular emotional and sonic qualities, editors whittled these songs into a manageable playlist, and the algorithms then sorted these editor-selected songs into an ideal order. Noting the popularity of TikTok's 'For You' feed, Spotify leaned even harder into algorithmic recommendations. Click on a mood-focused or genre-specific mix, and you'll usually get a version that was 'picked just for you.' In practice, this means tracks that share enough of those characteristics with tracks you've already played. In a data-drunk era, this is what passes for discovery. Like so many other products influenced by machine learning, Spotify's playlists can't generate something new —say, a wholly fresh and unheard sound—for its users. They instead offer the flash of recognition, rather than the mind-scrambling revelation that comes only when you hear something you'd never expected. Because they're all drawing from the same massive catalogs, the music streamers are conduits—between artist and listener, or listener and song. In a library north of 100 million tracks, you'd think it would be easy work finding candidates for playlists such as 'lofi autumn beats' and 'Bossa Nova Dinner.' But around 2016, as Mood Machine details, Spotify developed the Perfect Fit Content initiative, partnering with licensing companies that paid studio pros to bang out easy-listening ditties for the streamer—in essence, replicating popular playlist sounds on the cheap. (Spotify has not disputed the existence of the PFC program.) In recent years, Spotify developed its Discovery Mode program, in which labels exchange a portion of a song's royalties for priority status on an algorithmically generated playlist—with no disclosure to the listener. Pelly argues convincingly that this is the streaming version of payola: the illegal practice of promoting songs on the radio without disclosing the payment. (Payola laws apply only to terrestrial radio stations.) But in a crowded marketplace with fewer revenue streams, enough artists enrolled that, according to Pelly's reporting, Spotify's internal Slack channels were lit up with glee. Mood Machine is at its most compelling when peeking into Spotify's internal strategies and its employees' real-time reckoning with their implications. This is also where Pelly overplays her hand. In the conclusion, she analyzes two alternatives to the Spotify model: streaming services run by public libraries, and cooperatives of independent musicians. Spotify's playlists—atomized, contextless—clearly run counter to her ethos, which is rooted in community building and intentional listening. 'At a certain point, a streaming listener may very well come to believe that what the machine suggests is indeed what they like, not because it's true, but because they can see or feel no other option,' she writes. But less clear is whether the company's playlists are truly changing how the median listener approaches music discovery. Users are still generating hundreds of millions of their own playlists, mined from one of the largest collections of songs available in history. Mood Machine persuasively demonstrates how Spotify guides its users down certain roads—but it's not impossible to choose a detour. Today, Spotify boasts that one-third of its users' discoveries come 'via personalized recommendations in algorithmic contexts.' Like video streamers' triumphant press releases about how many hours were spent watching their 'hit' movies, the statement strains credulity. Is a discovery a song the user favorites—or just doesn't skip? And how could Spotify possibly know if someone had never heard a given song before? In any event, the company's cited percentage is eerily similar to one given in its 2018 IPO filing, which Pelly summarizes: 'Spotify-owned playlists, both editorial and algorithmic, then accounted for over 31 percent of users' listening'—less than half of all listening done through playlists. In raw minutes, that's a staggering sum. But even by Spotify's accounting, it's just one part of the streaming user's diet—often supplemented, still, with radio and physical media. At one point, Pelly gives a potted history of Muzak, drawing sharp parallels between Spotify and the bygone mood-music purveyor: their self-serving audience research, their tendency to generate palatable versions of the now sound. Anonymous label owners share concerns about Spotify promoting 'emotional wallpaper' and 'the watered down pop sound'; Pelly accuses the company of merely 'filling the air to drown out the office worker's inner thoughts.' The possibility that this office worker might click on a playlist of more interesting sounds—say, amapiano or noise-pop—is not the book's concern. Neither, for that matter, are some of Spotify's more controversial programming decisions that go beyond music—such as its nine-figure deal with the wildly popular podcaster Joe Rogan. (However objectionable prefab piano jazz may be, Rogan's critics would argue that his 'just asking questions' conspiracism has done far more to hurt society than cheap music has.) Still, it would be disingenuous to claim that cloud-based listening hasn't altered music discovery. For the obsessives, the streamers are a sort of last-mile service: a way to dig into something you encountered off-platform. Yet those encounters are becoming rarer. Music-video budgets have tightened, radio playlists have shortened, alt-weeklies and newspapers have closed, and no one's publishing the kinds of comprehensive reference books that used to come from AllMusic, Rolling Stone, and Spin. Some streamers offer openly human curation—Apple's radio stations, Tidal's blog—but that's just one aspect of their role as warehouse, marketer, broadcaster, and guide. There's never been this much music available to this many listeners; the ecosystem for discovery shouldn't feel this fragile or be this centralized. Mood Machine casts Spotify as the apex predator of this new ecosystem, which, according to Pelly, has the same old vulnerabilities. 'The problems faced by musicians,' she writes in the concluding chapter, 'aren't technological problems: they're problems of power and labor.' She's correct that Spotify is not a town square but a walled garden. Although your average music fan will always tend toward legible rather than challenging sounds, a functional cultural scene depends on well-maintained, materially rewarding, and diverse avenues for finding new music. Barring a global data-center failure —admittedly not a remote possibility, with the widespread implementation of AI sucking up more and more energy—the streaming model may be with us for the foreseeable future. We are surrounded at all times by an ocean of sound, but Spotify is content to leave us stranded on our islands.
