Entries in Hunch (3)


On Second Thought, Hunch Revisited; Or, are preferences portable?

Addendum: Hugo has clarified our conversation, please read the comments.

Are preferences portable? Since my recent post about all the sites I love that track my tastes and make recommendations accordingly and my subsequent musing about the weakness of generic Q&A sites, I had the pleasure of a dinner conversation this weekend to shake all my thoughts up.

On the one hand, the former (sites like Pandora and Amazon) are niche and probably derive the power of their accuracy from that focus. The latter (sites like Hunch.com and Yahoo Answers) I found struggle to be all things to all people and fail in the process. I wondered: is it possible to combine the accuracy of niche sites with the breadth of generic sites? In other words, would bringing my finely honed Pandora music preferences over to Amazon help in their book recommendations which in turn could help with my Netflix movie recommendations? Over time with a successful universal ID that knows all my tastes, many decision engine questions could be rendered moot.

Hunch.com Chief Scientist Hugo Liu was not so optimistic. His experience as a "taste researcher" suggests that preferences are not portable. Amazon "knowing" my music tastes, he suggests, has a neglible impact on the power of their book recommendations to me compared with their data on what people who bought my most recently purchased book also bought. I wonder, then, why Hunch tries so hard to "get to know" you to inform their recommendations on a wide variety of topics. Hugo has discovered some pretty interesting, and perhaps revealing, correlations from the Hunch data, for example, that people who like to dance regularly overwhelmingly seem to also prefer Macs over PCs. Curious, yes, but how much should this discovery impact their recommendations?

More surprisingly, Hugo questioned the value of web personalization at all and suggested that it could even be dangerous. On New York Times, for instance, I am pretty happy using the "Most Popular" box as my guide to the top stories. Do I need personalized "Just for You" results? What would happen if Google started filtering my search results according to what I would be most likely to like? Personalization comes at what price of objectivity?


Wikipedia founder Jimmy Wales joins Hunch, but the decision-making engine still falls short 

Hunch, the decision-making help site, scored a major publicity coup this week as Jimmy Wales, founder of Wikipedia, joined its Board of Advisors. I was an early beta user and initial fan of the site, impressed that my exploration of the question, "What credit card is best for you" led me 5 sub-questions later directly to my credit card of choice. Other questions were not quite so useful, but as the site is built by the community, it seemed reasonable that it would be weak in its early days.

Six months later, Hunch users have added considerable depth to the site, contributing 50,000 decision outcomes to help other guide other users of the site. Hunch combines this user feedback with machine learning tools to help you explore a wide range of questions from whether or not you should visit Russia to which military service you should join.

Wales described his reason for joining Hunch:

I’ve always been intrigued by the potential intersection of community-based, user-generated web platforms and algorithmic, machine-based ones. Wikipedia and Wikia have proven to do a pretty darn good job with the former. Search engines clearly do a great job with the latter. But until recently I hadn’t seen a great example of how the two approaches could come together, co-exist and truly complement each other to form something greater than the sum of the parts – which I believe is the future of the web. (Allow me to call it now: this is what we are going to come to call Web 3.0.)

This "intersection" has actually been well established by PayPal and Palantir, as we learned at Tap the Collective. And while I like the idea of applying it to decision engines, unfortunately Hunch still falls really flat. I just explored the site for the first time in months and the answers were just as random as during the beta period. The top "hunches" for what I should get my dad for Christmas were a shower radio and a margarita mix set. It said that 99% I should visit Russia. I put literally zero value on these suggestions.

As far as mechanisms to leverage the community to help you make decisions, I far prefer the model of Aardvark, which reaches out to your network to help you drive to very specific answers. Last month I got a chat from a guy in California asking me if I had an insights into a confusing part of The Angel's Game, a book that I had just finished days earlier and loved. We ended up corresponding several times. Now that's an amazing way to get a personalized response.


Hunch, a website to help you make decisions on...anything

If you have a big decision to make, whether it's who you should vote for or whether you should ditch your facial hair, there are many tried and true ways of coming to an answer. My favorites include reading the opinions of "experts" who I trust, informally polling my friends, and asking my mom. My mom and my friends are great, but may not always be the best sources of advice. How to get a broader opinion to inform my decision making?

Enter Hunch, an internet platform that aims to help you improve your decision making by getting to know you generally ("do you believe that alien abductions are real?") and by asking you related questions to to your main question of choice. The site creates a decision tree, informed by the results of all of its users, to use the "wisdom of crowds" to give you an informed and personalized recommendation.

From founder Caterina Fake (of Flickr fame):

Hunch is a decision-making site, customized for you. Which means Hunch gets to know you, then asks you 10 questions about a topic (usually fewer!), and provides a result -- a Hunch, if you will. It gives you results it wouldn't give other people...On Hunch, people can create a Topic (as we call it) that acts like a human expert, getting to a decision by asking relevant follow up questions and weighing trade offs. We think that it can ultimately save people lots of strenuous cognitive labor: not everyone who buys a computer needs to become a computer expert.

The site is currently open to those who request an invitation, and as someone who is consistenty struggling to be more decisive, I am glad to have tried it. The first question that I explored, "which credit card should I own?", led me to an answer by asking seven related questions--are you willing to pay an annual fee? do you want your rewards to be in travel, cash back, or points? what is your bank preference, if any? what is your credit score? etc.." It took me about 30 seconds to answer these questions and then the site produced a #1 recommendation: the Chase Freedom Card. That IS my credit card of choice! The decision that took me hours of online research, informal polling of my friends, time sitting around making sure this was the right card for me was answered on Hunch in 30 seconds. Wow.

This success made me excited to delve into my source of eternal pondering: "what city should I live in?" This time I answered only four questions related to the size of the city I would prefer, the amount of cold weather that I can stand, my regional preference, and whether I would mind living in a high cost area. I gave pretty open answers to all and my #1 result was....Philadelphia. #2 was Portland, Oregon. #3 was Wilmington. Why these three? Mystery.

The site, like most recommendation platforms, will only get stronger as the user base expands. Ms. Fake announced recently on her blog that users have answered 4.3 million questions since the site was launched (users could begin requesting invitations to use the site as of March 27). The recommendation algorithm, developed by MIT machine learning experts, is pretty powerful. Its strength also comes from offering cross-domain recommendations. I rely heavily on Amazon recommendations for books and iTunes recommendations for music, and I would love to see my preferences in those different spheres interact. For now, the site is pretty bare bones and only 500 topics are offered. I'll still be calling up my mom for those big decisions in the short term, but maybe Hunch will eventually supplant her wisdom.