In 2017, Spotify faced criticism for allegedly promoting “fake” artists on its platform—musicians characterized by vague online personas and generic, often instrumental music. These artists were accused of being artificially inflated by Spotify, appearing on popular playlists with millions of streams but little to no recognizable fanbase. This phenomenon led to a broader debate about the nature of music consumption on streaming platforms. However, as musicologist K. E. Goldschmitt points out, the concept of “fake” music is not entirely new; it taps into a long history of music created specifically for functional purposes rather than artistic expression.
The History of Mood Music
The idea of creating music specifically designed to evoke certain moods or emotions has a long history. One of the earliest examples is Muzak, a company founded in 1934 that became synonymous with background music, particularly in commercial settings like offices, elevators, and retail stores. Muzak’s goal was to create a soothing and pleasant atmosphere that would improve productivity, reduce stress, and subtly influence the behavior of those who heard it. This genre of music, often referred to as “functional music,” was carefully crafted to be unobtrusive, blending into the background while subtly shaping the environment.
Muzak’s influence extended beyond mere ambience, with specific playlists designed for different times of the day, each engineered to maintain or alter the mood and energy levels of its listeners. By the mid-20th century, this concept of mood music had spread into homes through radio and early television, reinforcing the idea that music could be a tool for managing emotions and environments rather than just a form of artistic expression.
The Rise of Spotify’s Mood-Based Playlists
Spotify’s mood-based playlists can be seen as a modern continuation of Muzak’s legacy, but with the added twist of personalization. Unlike traditional radio or Muzak, Spotify uses algorithms to analyze user data, tailoring playlists to individual tastes and listening habits. Playlists like “Chill Hits,” “Deep Focus,” and “Peaceful Piano” are designed to match specific activities or emotional states, from studying and working to relaxing and unwinding.
Spotify’s playlists are carefully curated by both human editors and algorithmic recommendations, ensuring that the music aligns with the intended mood. This approach has proven incredibly popular, with mood-based playlists often outperforming those focused solely on genre or artist. For instance, “Lo-fi Beats,” a playlist designed to provide a calm and ambient backdrop for work or study, has become a staple for millions of users seeking an unobtrusive soundtrack to their daily routines.
The Controversy Surrounding “Fake” Artists
Despite their popularity, Spotify’s mood-based playlists have sparked controversy, primarily due to the prevalence of so-called “fake” artists—musicians who seem to exist solely within these curated playlists without any visible public presence, fanbase, or touring history. Critics argue that many of these artists are not real, independent musicians but rather anonymous producers or in-house creators commissioned by Spotify to generate content cheaply and efficiently.
This practice has raised questions about transparency and the integrity of Spotify’s platform. By filling popular playlists with these anonymous, royalty-free tracks, Spotify can reduce the amount it pays in royalties to major labels and well-known artists. This strategy has been criticized as undermining genuine artistry and prioritizing algorithmic appeal over musical innovation.
Furthermore, the lack of identifiable creators behind these tracks feeds into a broader critique that mood-based playlists promote a superficial, formulaic approach to music. Instead of fostering a deeper connection with artists or the music itself, these playlists prioritize immediate emotional impact and background utility, often at the expense of traditional music discovery.
The Appeal of Mood-Based Music
Despite the criticisms, mood-based music has a broad appeal, and its popularity continues to grow. For many listeners, the primary value of mood-based playlists lies in their convenience and the personalized experience they offer. They allow users to find the perfect soundtrack for any situation without the need to actively search for specific songs or artists. This shift reflects broader changes in how music is consumed in the digital age: for many, music is increasingly seen as a tool for managing everyday life rather than a medium for active engagement.
Mood-based playlists also serve as a form of escapism, providing an easy way to relax, focus, or energize, depending on the listener’s needs. In a world of constant stimulation and stress, these curated playlists offer a predictable, reliable source of comfort, much like Muzak did in mid-20th-century offices. Whether it’s to create a calming environment, maintain concentration, or simply fill silence, mood-based music has found a receptive audience among those seeking simple, low-effort ways to enhance their daily lives.
The Impact on Artists and the Music Industry
The rise of mood-based playlists and the presence of “fake” artists have significant implications for the music industry, particularly for independent musicians and traditional artists. As mood-based playlists grow in popularity, they are reshaping the way artists think about creating music. Many artists are now considering how their music might fit into playlists as much as traditional radio or album releases, adjusting their creative processes to align with the mood and utility-driven demands of the streaming ecosystem.
However, this shift can be a double-edged sword. While it opens new avenues for exposure, it also means that artists are increasingly competing against algorithm-generated music designed to be generic and inoffensive—qualities that make it ideal for background listening but potentially bland and unmemorable. This dynamic challenges artists to balance creativity with commercial viability in a landscape where the most successful tracks are often those that seamlessly blend into the background.
The Future of Music Streaming
The future of music streaming appears poised to continue evolving toward more personalized, mood-driven content. As technology advances, streaming platforms like Spotify are likely to refine their algorithms further, offering even more precisely tailored playlists that cater to individual moods, times of day, and activities. This hyper-personalization could lead to a fundamental shift in how we perceive and engage with music, emphasizing emotional and functional value over traditional genres and artist loyalty.
This trend raises important questions about the future of artistic integrity and the role of technology in shaping cultural consumption. While mood-based playlists and algorithmic curation offer undeniable convenience and appeal, they also challenge us to consider what we lose when music becomes more about utility than expression. As streaming platforms continue to navigate this balance, the music industry will need to grapple with the implications for both artists and listeners.
The controversy surrounding Spotify’s “fake” artists highlights the complex relationship between technology, commerce, and artistic expression. While critics may lament the rise of formulaic, mood-based music, its popularity is a testament to the changing ways we interact with music in our daily lives. As streaming platforms like Spotify continue to blur the lines between art and function, the music industry must adapt, finding new ways to support creativity and authenticity in a world increasingly driven by algorithms. The case of Spotify’s mood-based playlists serves as a reminder that, while music’s role may be evolving, its power to connect, soothe, and inspire remains as vital as ever.
Keywords: Spotify, fake music, mood-based playlists, streaming platforms, music industry, technology, commercialization, artistic expression, consumer preferences, music consumption, algorithmic curation, personalization, functional music.
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