Last week I wrote about Twitter, a flawed and difficult-to-grasp social media technology that nonetheless becomes addictive once you get the hang of it—so much so that it’s quickly changing the way many people communicate. This week I’m going to write about Hunch, a flawed and difficult-to-grasp social media technology that nonetheless becomes addictive once you get the hang of it—so much so that it’s bound to change the way many people make certain kinds of decisions.
The product of a New York City startup founded by Flickr co-creator Caterina Fake, Hunch is designed to help us all cope with the problem of choice. Where should I go on vacation? Should I drop out of college or get my degree? What cool new video game should I buy? What’s the best sleep aid for me? Which New York City museum should I visit?
For almost any personal decision, chances are that someone else has already thought it through and can list the leading possibilities. But while the Web offers plenty of community sites where you can solicit such advice—I reviewed a bunch of them, including Yahoo Answers, back in 2006—Hunch has added an ingenious twist. It’s the “decision tree,” an algorithm that guides you through a big choice by asking you to make lots of smaller, easier ones.
Hunch has decision trees for roughly 1,300 topics so far. Each poses a series of multiple-choice questions. Your answer at each point determines which branch of the tree you’ll follow, until you wind up at a single recommended answer. A simple decision might involve only one or two questions, while a complicated one can have a dozen or more. Decision trees are devised by users themselves—in fact, if you feel like you’re an expert on something, Hunch encourages you to build a tree yourself, or help improve existing trees by adding new questions.
There’s an important wrinkle, however, that makes exploring Hunch more than just a process of clicking through a bunch of mathematically preordained decision trees. The site remembers how you’ve answered other questions, and over time, it builds up a picture of your preferences. That information is factored into the final recommendation, and might even override your answer to a specific question within a tree.
As an example of all this, here are the questions you’ll see for the topic “Should I buy an Amazon Kindle?”—which, as regular readers of this column know, is a decision I’ve been struggling with myself.
• Do you have a commute that allows you to read during it?
• Do you frequently travel with more than two books in tow?
• Do you subscribe to any major newspapers in print versions?
• Do you wish you could dynamically resize the text of print publications?
• For now, photos appear in black and white on the Kindle. Is this ok?
• Are you concerned with conserving paper in order to save trees?
• Do you get a particular sense of satisfaction from storing a book you’ve read on a bookcase?
• Are you clumsy with personal electronic devices like cell phones?
• Does having quick access to a dictionary/wikipedia seem valuable?
• Do you have several books at once on your nightstand?
When I went through this tree mechanically answering “Yes” to every question, Hunch told me that there was a 92 percent chance that the right answer for me is “Yes, you should buy a Kindle.” I couldn’t find anything on the Hunch site that explains how these percentages are calculated, but I’m guessing that the other 8 percent represents
