In many instances, companies have leveraged structural advantages to achieve seemingly unassailable positions in their relative markets. Streaming services that host user-generated content (UGC) have significant advantages over other services due to copyright ‘safe harbours’, which has led to the dominance of services like YouTube. We have been... See more
To prevent a future where cultural output is shaped by economic power alone, this report calls on digital services, rightsholders, regulators, and policymakers to take shared responsibility for ensuring that the streaming ecosystem supports innovation, inclusivity, and sustainable growth .
While changes to a market are expected as it evolves, the interconnectedness of music streaming means that impacts are felt throughout the entire ecosystem. This is to say that there is a responsibility for all parties concerned to transparently engage in wider consultation before such impactful decisions are made. There is a shared responsibility... See more
The study estimates that the music industry has lost over £10 million in revenue to AI-generated content, but this is likely just the tip of the iceberg. Consider that one North Carolina musician, with a relatively small-scale operation, was allegedly able to generate hundreds of thousands of fake tracks, rack up billions of plays, and syphon off... See more
New technologies may be disruptive to the existing population of working musicians, but even more irresistible to the general public than new technology are new forms of music, which may introduce new classes of musicians who don’t fit neatly into the existing professional categories. Take the rise of rock and roll.
For most of recorded history, there were two ways of making a living as a musician. You could work for a patron—the court, the church, an individual aristocrat—or you could sing for your supper, sometimes literally, as an itinerant minstrel. Then, by the turn of the twentieth century, a third option opened, that of recording artist, in which little... See more
Abstract: The growing field of “critical algorithm studies” often addresses the cultural consequences of machine learning, but it has ignored music. Te result is that we inhabit a musical culture intimately bound up with various forms of algorithmic mediation, personalization, and “surveillance capitalism” that has largely escaped critical attention. But the issue of algorithmic mediation in music should matter to us, if music matters to us at all. This article lays the groundwork for such critical attention by looking at one major musical application of machine learning: Spotify’s automated music recommendation system. In particular, it takes for granted that any musical recommendation – whether made by a person or an algorithm – must necessarily imply a tacit theory of musical meaning. In the case of Spotify, we can make certain claims about that theory, but there are also limits to what we can know about it. Both things – the deductions and the limitations – prove valuable for a critique of automated music curation in general."