« PREVIOUS ENTRY
More of my NYT mag ideas-pieces: “Airborne Humans”
Here’s yet one more of my essays in this week’s New York Times Magazine’s “Year in Ideas” issue:
Hit Song Science
When Norah Jones released her first album, she was a long shot at best. ”Come Away With Me” was filled with mellow, sultry tunes — precisely the opposite of the histrionic diva pop crowding the charts. Virtually no one expected Jones to score a major hit.
No one, that is, except for a piece of artificial intelligence called Hit Song Science, a program that tries to determine, with mathematical precision, whether a song is going to be a Top 40 hit. When the scientists fed Jones’s album into that computer, alarm bells went off: the program predicted that eight tracks would hit the charts. ”We were like, whoa, that’s funky,” says Mike McCready, the C.E.O. of Polyphonic HMI, the Barcelona-based company that developed the software application. A few months later, Jones’s album went multiplatinum — and Hit Song Science had proved it could pick a hit as well as Clive Davis.
But how? At the heart of the program is a ”clustering” algorithm that locates acoustic similarities between songs, like common bits of rhythm, harmonies or keys. The software takes a new tune and compares it with the mathematical signatures of the last 30 years of Top 40 hits. The closer the song is to ”a hit cluster,” the more likely — in theory — that the kids won’t be able to resist it. Yet the weird thing is, songs that are mathematically similar don’t necessarily sound the same. The scientists found that U2 is similar to Beethoven, and that Van Halen shares qualities with the piano rock of Vanessa Carlton. Even more bizarrely, 50 Cent’s throbbing rap tune ”If I Can’t” correlates with ”(There’s) No Gettin’ Over Me,” a twangy country ditty by Ronnie Milsap.
This year, several record companies began using Hit Song Science to help pick which songs on an album to promote. Others are now using it in the studio, taking a rough mix of a new song, checking to see how hit-worthy it is, then tweaking it until it has ”good mathematics,” as McCready puts it. He can foresee a day when most major hits will have been vetted by algorithms.
Which is, depending on how you look at it, either a wonderful breakthrough for science or an incredibly bleak statement about the music industry. Critics for years have complained that record labels produce only bland albums that mimic what’s already popular. But Hit Song Science takes that trend to its logical absurdity: it does not merely aim at the middle of the road — it calculates it, with scientific precision. — Clive Thompson
I'm Clive Thompson, the author of Smarter Than You Think: How Technology is Changing Our Minds for the Better (Penguin Press). You can order the book now at Amazon, Barnes and Noble, Powells, Indiebound, or through your local bookstore! I'm also a contributing writer for the New York Times Magazine and a columnist for Wired magazine. Email is here or ping me via the antiquated form of AOL IM (pomeranian99).
ECHO
Erik Weissengruber
Vespaboy
Terri Senft
Tom Igoe
El Rey Del Art
Morgan Noel
Maura Johnston
Cori Eckert
Heather Gold
Andrew Hearst
Chris Allbritton
Bret Dawson
Michele Tepper
Sharyn November
Gail Jaitin
Barnaby Marshall
Frankly, I'd Rather Not
The Shifted Librarian
Ryan Bigge
Nick Denton
Howard Sherman's Nuggets
Serial Deviant
Ellen McDermott
Jeff Liu
Marc Kelsey
Chris Shieh
Iron Monkey
Diversions
Rob Toole
Donut Rock City
Ross Judson
Idle Words
J-Walk Blog
The Antic Muse
Tribblescape
Little Things
Jeff Heer
Abstract Dynamics
Snark Market
Plastic Bag
Sensory Impact
Incoming Signals
MemeFirst
MemoryCard
Majikthise
Ludonauts
Boing Boing
Slashdot
Atrios
Smart Mobs
Plastic
Ludology.org
The Feature
Gizmodo
game girl
Mindjack
Techdirt Wireless News
Corante Gaming blog
Corante Social Software blog
ECHO
SciTech Daily
Arts and Letters Daily
Textually.org
BlogPulse
Robots.net
Alan Reiter's Wireless Data Weblog
Brad DeLong
Viral Marketing Blog
Gameblogs
Slashdot Games