read a very different set of magazines from suburban Connecticut housewife. So there’s an algorithm that tries to figure out, “Is this a taste-driven topic or not?”
X: Well, these algorithms that influence the outcome are another element that actually bugs me a little bit about Hunch. If I’m going to take the trouble to write a really good topic, I don’t want algorithms interrupting and sending people off in different directions than the ones I planned.
CF: Yeah, there is a kind of balance between these two things. If you are a hard-core contributor, there are all of these levers you can use. You can set a question’s importance—you can say that where a hotel is located is significantly more important than its price, and set that manually. And the algorithms tend not to override human input, if there has been a significant amount of it. It will, however, trigger something on the inside of the system if the topic is not giving people good answers. If we’re finding that there is a low success rate, the question creator could potentially be wrong [about how they designed the decision tree]. So the algorithm doesn’t override human input, but it does detect when those discrepancies take place.
X: You were saying earlier that there’s an unlimited number of questions that humans might have. But on the other hand, isn’t there a fairly finite number of frequently asked questions? And in that case, how do you handle it when a contributor wants to create a topic but it turns out that somebody has already written a topic for their area of interest?
CF: When you’re creating a topic that’s already in the system, the system does de-duping, and it’s up to our content team which topics to de-dupe. We prefer that people flow through to existing topics rather than create duplicates.
X: Okay, but wouldn’t the de-duping discourage people who are fired up about contributing? They might want to write a topic about “Which macro lens should I buy for my camera,” but if it’s already been written, they’ll just go away. And if you have algorithms that can measure the success of a topic, why not just let duplicate topics compete, and keep the ones that produce better ratings?
CF: I totally get what you’re saying. There is a constant battle here between the “Let a thousand flowers bloom” model and the constrained, “We’re only going to have one Hotels in London topic” model. This is an art, not a science, and whenever we have content meetings, these are exactly the questions that come up. I’m very much of the “Let a thousand flowers bloom” school, so I’m more liberal in terms of the number of topics I think we should have. But the reason there’s such a strong tension around these very questions is that if you’re going to create a good topic, you need to concentrate the training as much as possible around one topic, so that it’s well-trained and gives people good answers, rather than spreading the algorithm’s attention over a vast number of topics. If there were 12 topics all about hotels in Paris, none of them would be very well-trained. But this is a constant source of debate internally, and the care and feeding of topics is one of the most important decisions we have to make behind the scenes.
X: I love all these technology and philosophy questions, but I also have to ask the revenue question. I don’t see any advertising on the site yet—how are you going to make money?
CF: If you do product-related searches, you’ll see that the recommended products have links to e-retailers. So affiliate revenues, commissions on sales, is our model right now. But right now we’re not really focused on revenue. We are a 10-person team, and we’ve got enough cash in the bank to last us until we get some kind of revenue.
X: Do you think Hunch has the potential to become as big as Flickr?
CF: I hope so. I think it’s a very different model. There’s a very different read/write ratio on Hunch. At Hunch, you can create a topic that thousands of people will use. Whereas on Flickr, you can upload a photograph, and only three people will ever see it, and that’s still a successful Flickr interaction. So the systems are very different in that way. Obviously, Hunch is not a social network; you don’t hang out on Hunch, whereas you can hang out on Flickr. Hunch is more similar to Wikpedia or Yahoo Answers; it’s used episodically. Although you could also argue that Flickr has become, in some ways, the world’s infinite National Geographic, a vast photo encyclopedia. I do think that Hunch has the potential to have that wide a use.
