INTRO: We’re living in the age of big data. We now know exactly how many times the average person blinks per year; how many steps we’ve taken in a day; how long it take us to get from point A to point B to the T.
With our culture becoming increasingly quantified, a number of artists are turning data into music. Brian Foo is one of these composers. His latest piece – a music video – takes us on a musical journey of median neighborhood income data in New York, by way of the 2 train. Dasha Lisitsina tunes in.
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[Ambi. Fade under]
That’s the sound of the 2 train, or rather Brian Foo’s version. The journey starts off pretty quietly in Flatbush Avenue, Brooklyn – median income per year: $37, 000. [Ambi: fade up, fade under]. Foo’s piece comes with visuals that chart the subway stops.
[Fade up.]
We’re now on the edge of Brooklyn… Hoyt St, Borough Hall…we’re crossing into Manhattan…we’ve hit Wall Street – median income: about $125,000 . The music is loud and cacophonous throughout much of Manhattan.
[Fade up. Fade under.]
Foo took sound samples from the subway and bits and pieces from New York musicians – 63 sounds in total.
FOO: And for each instrument I gave it a different value, like a price essentially. And basically what the algorithm does is it goes through each station and assigns each station a budget based on the median income of the area and then with that budget it can buy as many instruments as it can afford, in the order of soft to loud.
So by the time we hit Chambers St. – median income $200,000, the climax of the piece – it sounds like this [Fade up. Fade under] Harlem, 135th St sounds like this. [Fade up. Fade under]. Manhattan – the financial capital of the world – is also the place with the greatest income inequality in America.
FOO: It’s something you see all the time, like on the subway. If you take the subway like three different boroughs, you can kind of tell when somebody’s going to get off at a certain stop.
Foo says making music of this data has an emotional impact.
FOO: Put it this way, a chart never made me cry or like put a chill through my body. Whereas music does do that, or it can do that.
DUBOIS: Music is very good at political impact.
That’s Luke DuBois, another artist who uses data. He says he usually despises drab journalistic data visualization. But visual art made from data: good. Music: even better.
DUBOIS: It’s easier to emotionally manipulate someone with music than with a painting. You fall in love to songs. You don’t fall in love to a set of pastoral prints on your wall.
Through his own work DuBois aims to close the gap between the hard cold data and the lives behind it.
DUBOIS: What I try to do…mine’s about finding a good metaphor to really drive home that data is not abstract, that it actually represents people. I call it ‘heart data’.
That’s heart as in I heart NY.
DUBOIS: Data that is factual that can hurt.
In a way, it’s not really surprising artists are taking inspiration from what’s happening in our culture. We’re now obsessed with quantifying everything, even ourselves. But data – the measured recording of the observed world – pre-dates computers and has been a part of music since the beginning.
DUBOIS: The thing that is new is…the idea of like I’m gonna take the U.S. Census and I’m gonna turn it into like sound, which is mapping or transcoding. That’s kind of unusual, that’s sort of new.
We’re now in the Bronx [Fade up. Fade under] Here the music dies down again.
Dasha Lisitsina, Columbia Radio News.