The 10th anniversary of the music streaming service Spotify, marks a period of significant change in the way that music is consumed. These changes have been widely discussed over the last decade, with questions about the ongoing relevance of CDs and vinyl, the legality of downloading, the damage to the industry and artists of free music and so on. Yet services like those provided by Spotify may not only be changing how we listen to music, they are also active in shaping our actual music tastes.
It is common now for music, TV and film providers to deploy algorithmic systems that attempt to predict and then recommend other cultural forms that we might also enjoy. This is something with which we are now very familiar; recommendations have become a routine part of cultural consumption. Algorithms, which are the parts of code that make decisions, use the data produced by peoples’ cultural consumption to predict tastes and prioritise music, TV, films, games and so on that fit with those tastes. We see this as being a process by which our existing tastes and preferences are anticipated by these apparently intelligent systems.
Given the way that systems are now guiding the culture we encounter, we have to wonder if they are also now actively shaping and possibly even changing the very tastes that they are attempting to predict. The result would be something like a self-fulfilling prophecy, with the recommendations we are made shaping both our consumption and the tastes and preferences that we form. In the case, the power of the algorithm is in its ability to decide on the cultural forms that we encounter. Those encounters are likely to then define our cultural landscape, defining the culture that we become aware of and that becomes visible to us. Naturally the things that pass through our orbit or our consciousness are the things that we are more likely to attach meanings to or to create a connection with. In the current cultural landscape – which is diverse, baffling and fragmented – these algorithms help us to navigate the chaos by enabling culture forms to find us. These algorithms make the unfathomable complexity of culture manageable for us. At the same time though, by making those choices on our behalf they are coming to dictate a good deal of the things we then experience. If we think about the music we listen to – or indeed the books we read, the films we watch, the games we play, and so on – then we might be able to reflect on how much of that has been a product of the activity of algorithms. Some would question the accuracy of those algorithms to predict taste, yet even where those choices might seem odd to us the algorithms are still defining the culture that we encounter.
There has not necessarily been a great deal of agreement in the past about where our cultural tastes and preferences come from. For some they are seen to be innate part of a core personality, for others our tastes are the means by which we are able to construct or build and communicate a more fluid identity. In more sociological terms, it has been argued that our music and cultural tastes are a product of our family and friendship groups, or that they may even be both a product and marker of our social class. But the anniversary of Spotify, which is indicative of the decade or so in which we have lived with the many other algorithmic systems through which we consume culture, might suggest to us that there is something else going on with the formation and maintenance of our cultural tastes. These systems are now so embedded in our cultural consumption that they will inevitably implicate the way in which are tastes are formed. Beyond understandings of cultural tastes as being a product of our personality or our social background, it might be that the active infrastructures in which our cultural lives are lived are also having a bearing on what we like and the tastes we develop. It is not just our listening practices then that may be transformed by Spotify, such services may also be changing the connections and attachments that we have with that music.
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