Sep. 28 2011

The algorithms by which things like Facebook decide what to show you and what to hide are totally opaque. There’s this kind of weird, big lie about how an algorithm is not a form of editorial control. Google will say ‘we have organic search results’ in contrast with what Alta Vista used to do, where they would take payment to put a result first. It’s ‘organic’ because it’s done with math, but actually it’s editorial by another name. All the companies that do editorial by algorithm claim that there’s something about math that makes it free of bias and will.

Cory Doctorow (via azspot)

always knew i hated math.

May. 13 2011

but when sophisticated mathematics is applied, they believe the imperfections go away by some mathematical magic. But this is not magic. What really happens is that the mathematics is used to disguise the problems and intimidate people into ignoring them—a modern, mathematical version of the Emperor’s New Clothes.

Aug. 01 2010

Nov. 14 2009

Nov. 21 2008

Mathematically speaking, “Napoleon Dynamite” is a very significant problem for the Netflix Prize. Amazingly, Bertoni has deduced that this single movie is causing 15 percent of his remaining error rate; or to put it another way, if Bertoni could anticipate whether you’d like “Napoleon Dynamite” as accurately as he can for other movies, this feat alone would bring him 15 percent of the way to winning the $1 million prize. And while “Napoleon Dynamite” is the worst culprit, it isn’t the only troublemaker. A small subset of other titles have caused almost as much bedevilment among the Netflix Prize competitors. When Bertoni showed me a list of his 25 most-difficult-to-predict movies, I noticed they were all similar in some way to “Napoleon Dynamite” — culturally or politically polarizing and hard to classify, including “I Heart Huckabees,” “Lost in Translation,” “Fahrenheit 9/11,” “The Life Aquatic With Steve Zissou,” “Kill Bill: Volume 1” and “Sideways.”

So this is the question that gently haunts the Netflix competition, as well as the recommendation engines used by other online stores like Amazon and iTunes. Just how predictable is human taste, anyway? And if we can’t understand our own preferences, can computers really be any better at it?

Sep. 18 2008