Popular Music, Big Data and Ethics
Many of the ways in which popular music is produced, distributed
and consumed have altered considerably over the last two decades, and largely
as a result of digital and internet technologies. We are by no means at the end
of this 'digital revolution' in popular music, with much still in a state of
turmoil and flux as businesses, artists and consumers alike grapple with the
new and emerging landscapes. It's an exciting time to be researching in this
field. My PhD focusses primarily on music listening in the digital age, and
does so through the collection of user data through The Harkive Project. This is an on-line,
crowdsourced method of gathering stories from music listeners about the detail
of their everyday music consumption that I developed as part of my MA studies
at Birmingham City University. Since 2013 the project has gathered over 7,500
stories, from people all over the world.
By gathering (what I hope is) useful data from music listeners, I
am engaged in much the same activity that media companies and rights holders involved in the music
industries are currently focussing a large amount of attention and resources
on. Data collection and analysis is rapidly becoming a key element in the
business of popular music, as illustrated by the recent acquisition by Apple of
MusicMetric in a deal reported to by
worth US$50M. This raises ethical concerns on my part, in that the data I
collect has potential uses beyond the purely academic, and is one of the two
main reasons why I am keen to attend this seminar.
The other reason is that due to
the scale and voracity of industrialised data collection in a wider societal
sense, issues and questions related to data protection, use, monetisation,
ownership, access, surveillance, storage and archives are of growing interest
to academics in a number of fields.
The realm of data is of particular interest to scholars of Popular Music
because of its growing influence on matters related to the production,
distribution and consumption of music, and it is here that my own area of
research intersects with the wider debates. As such I am very much looking
forward to hearing what the panel and delegates have to say on these matters.
In terms of my position, I would
start with Sterne (2012) and Milner (2010), who, in their explorations of the
development of recording and audio technologies, have argued that the idea of a
recording, however advanced, being capable of capturing a true representation
of reality, is a fundamentally flawed one. For Sterne (2006), the gaps between the zeros and
ones in digital recording - its flaws, in other words - are precisely where the
interesting questions lie.
The affordances of zeros and
ones are exactly what the service offered by Shazam
uses to do its work in telling millions of listeners each day the name of the
song they are listening to. Shazam is one such company that is heavily
influencing music production and distribution through the monetisation of the
data it collects via its relationships with industrial clients such as record
companies. This represents a further rationalisation of process in the music
industries as it chases increasingly granular revenue streams with increasingly
granularised techniques. However, a similar service, HitPredictor, armed with
both granular data and an algorithm that analyses the ‘hit potential’ of a
song, entirely failed to predict the success of All About That Bass, one of the
biggest hits of 2014. Building on Sterne’s observation above, is it possible
that the failures and blind spots of Big Data
are more interesting than its successes?
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