Before Google was a verb, Twitter was an avocation, and Facebook was a way to spend your evening, it was easy to know where to get your information. Step 1: Go to your local library. Step 2: search the catalog (and before that, peruse the card catalog). Step 3: compare the citations for the term you are searching to see if they came from “reputable” sources such as a major newspaper, a mass-market book by a “famous” writer or historian, or if the same facts were corroborated by different sources. How can you get similar fact-checking on Internet sources when the news itself might only be minutes or seconds old?
The easiest way to trust what you read on the internet is to rely on the old Mass Media (WSJ, NYT, etc), and ignore the web sites or sources you don’t know or trust. This is a reliable indicator for major events that are well-covered by the traditional mass media. However, the NYT doesn’t help you with the small decisions you make every day. But an interesting new web site aims to improve the ability of your personal network and of the personal networks of others to arrive at the Truth (from your perspective). Caterina Fake, co-founder of Flickr, explains that Hunch can provide the right answer for you for the question you asked.
Hunch operates on two levels. The first level, popularly known as Collaborative Filtering, can provide reliable recommendations “liked” by the crowd that are more accurate than individual predictions and produce recommendations for future “likes” based on present behavior. Hunch also asks you questions about You — so that it can take the crowd-sourced recommendations and give you a lens through which to view them that matches your personal views — and “guesses” or creates a Hunch tailored to you. This second level of filtering matches the large number of random (or not-so-random, depending upon the question) answers from the crowd with your actual likes and dislikes. I think this is the beginning of a critical thinking ability for the internet that can help you to identify unknown sources of content as valid or invalid (with the help of networks like Hunch).
What are the implications of getting a personalized version of the “Truth”?
It’s a little scary on the one hand to think that you are seeing the “Right Answer” to your question based on your likes and dislikes. On the other hand, the only person who can accurately rate an answer to your question as correct is … You. Hunch’s grand potential is that it could take the questions individual people have, distribute them to others to validate, and then take the “right answers” and syndicate them out in bulk as “crowd-sourced” news.
Imagine a world where you can ask your Hunch network to help you decide (provide you with options, not tell you what is right and wrong) whether an individual piece of content, or a personal decision to take the freeway instead of local streets, or whether the hamburger or the chicken is most fattening. Ok, you say, — what’s different about this from Mechanical Turk, Yahoo Answers!, or any one of the other answer-my-question sites that have sort of succeeded, sort of failed in the past few years?
Two differences are interesting to me that will make services like Hunch succeed: scale and mobile computing platforms. Caterina Fake has already determined how to build a large consumer service to scale. Flickr executes billions of interactions for millions of global users, and does so in a way that is pleasing to use and consume. Mobile computing platforms (I’m thinking of iPhone, but others like Android are on the way to becoming ubiquitous as well) make the idea of “asking a question” to your Answer Network more plausible at the moment that you need it.
One final thought on this issue. Could Google + Twitter produce this harmony of information, albeit in a more brute force, “ask my friends and index the result” sort of way? The folks at ReadWriteWeb recently covered this development, and it will be interesting to see where it leads. In the meanwhile, Hunch is an interesting and new way to answer the question: Can You Trust What You Read on the Internet. The answer? Maybe.