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taste

 

On the problem of taste

When you’re choosing furniture for your home that’s supposed to express who you are, what you are also saying is you want other people to infer what you want them to infer. What if they see something different? Wouldn’t it be really depressing if you’re trying to be bohemian and instead they see you as Rush Limbaugh?

—Dr. Sheena Iyengar, Columbia University business professor & author of the famous study demonstrating the paralyzing effect of too many choices

Dr. Iyengar, who is blind, has a standing committee of friends, family and colleagues who provide recommendations on her wardrobe and interior decor. Her goal is both consensus and criticism, since she does not believe in making decisions based solely on her own taste. When making decisions about things that you hope will reflect your own style, “you cannot get to the heart of how things are going to be perceived unless you ask these [external] judges,” Dr. Iyengar believes. Of course, she remains free to ignore her committee's advice. She says, “Everyone is convinced their opinion is the truth, and that’s what I struggle against. But doesn’t everyone?"

Filed under  //   consumerism   fashion   interior design   taste  

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Searching for an algorithm for taste

http://www.nytimes.com/2008/11/23/magazine/23Netflix-t.html?pagewanted=all

This week’s New York Times Sunday magazine checks in with a few competitors in the Netflix competition. One of the contestants estimates that an accurate predition of whether someone would like the movie Napoleon Dynamite—a film that viewers seem to either love or hate—would put him 15% closer to the algorithm that would earn a $1 million prize.

When Bertoni runs his algorithms on regular hits like “Lethal Weapon” or “Miss Congeniality” and tries to predict how any given Netflix user will rate them, he’s usually within eight-tenths of a star. But with films like “Napoleon Dynamite,” he’s off by an average of 1.2 stars.

According to the article, the “Napoleon Dynamite problem” exposes the “a serious weakness of computers”: their inability to anticipate all of the factors in a person’s decision-making process.  Someone could decide to watch a movie after a Blockbuster clerk’s passionate recommendation, or to understand a cultural reference point, or simply to try something different.

Another critic of computer recommendations is, oddly enough, Pattie Maes, the M.I.T. professor. She notes that there’s something slightly antisocial—“narrow-minded”—about hyperpersonalized recommendation systems. Sure, it’s good to have a computer find more of what you already like. But culture isn’t experienced in solitude. We also consume shows and movies and music as a way of participating in society. That social need can override the question of whether or not we’ll like the movie.

An interesting read. [If You Liked This, You’re Sure to Love That | NYTimes]

Filed under  //   algorithm   math   museum website   taste  

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