“Is Anonymity critical to discovering great music?”

 

 

So the world produces a deluge of music and this deluge clogs up ‘discovery’ platforms like YouTube and Spotify and makes discovery for newbies a near impossibility.

 

 

A fair & trusted Filter:

 

At isongU, we have spoken about the need to filter out the best songs, and this filter must be impartial, repeatable, reliable and fair. And yes, the best songs must be elevated and exposed and generate songs sales for which musicians must be fairly compensated, but that’s another story. The first step is to be sure we have indeed sifted out the absolute greatest songs.

To ensure impartially great songs at isongU, we render all songs anonymous so that there are no influencers or herds or popularity contests …the kind of things that removes all wisdom from crowds. By making the crowd impartial, we hope to make them wiser.

But is anonymous music the answer? Is anonymity the ‘format’ that will make crowds wise and drive the future of music? Or, to reverse the argument, is it the very lack of anonymity and open sharing of views that serves us today’s weak popular music offerings?

 

 

People adhere to the music tastes of others:

 

The following is from a study from almost 10 years ago, the results of which appeared in the New York Times here:  nytimes.com/3

     In an experiment, social scientists at Columbia University simulated an online music   marketplace that included 14,341 participants recruited from teenage interest Internet sites. The researchers provided half the group with a list of obscure rock songs and encouraged them to listen and download the ones they liked.

The teenagers received no other information and did not know who else was participating. The songs were a sampling from a Web site where many virtually unknown bands post their own music.

By tallying song downloads, the investigators produced a rough rating of the songs’ quality.

When the other half of the teenagers browsed the same songs, they saw, alongside the titles, the number of previous downloads for each song by other members of their group. And they tended to download at least some of the songs previously chosen, resulting in a top 25 chart significantly different from that of the original group.

By running several simulations of this experiment, the researchers showed that song popularity was not at all predictable when people could see what their peers were doing. Good quality songs tended to do better than poorer ones, but not always: a song called ”Lockdown” by 52Metro ranked first in one simulation and 40th out of 48 in another.

”A small group of people making decisions at the beginning had a large influence” on how the songs were ultimately ranked, said Duncan Watts, who, along with Matthew Salganik and Peter Sheridan Dodds, reported the findings in the journal Science.

With little else to guide their choices, people often look to others for cues; curiosity, perhaps along with an urge to affiliate with the group creates a kind of cascade effect in favor of the songs first chosen, Dr. Watts said.

 

 

Anonymity is the only hope for fairness:

 

This experiment clearly shows how, even among small groups, it becomes a popularity contest and decisions are readily swayed. In conclusion, we believe that the first step towards creating an unbiased, fair filter that always repeatedly gives us the highest quality music is to render all songs anonymous. That way, all songs (and all artists) get treated as equals.