It’s not information overload, it’s filter failure.
My father is an artist, art historian, and conservator of painting. One of his roles when I was growing up in the 80s, was Curator of Painting at the Prince of Wales Museum in Mumbai. I had the unique privilege of being exposed to a range of art as a result. Art from the great Indian contemporary painters like M.F. Hussain and Sabavala, to the European greats like Rubens, to painted, sculpted, and gilded masterpieces from ancient India.
I realized back then, that this was an unbounded and fascinating world filled with millions of creations. It took a bit longer to realize that I had by my side, one of the best “filters” for helping me discern the attributes of great art: my father and his band of fellow scholars. When they pointed to a piece of art and agreed (or disagreed) that it was great (or not), it came from years of training, observation, and research, culminating in what we might call discerning taste. If they had an algorithm to identify art they liked, it was only in their sub-conscious, intuitive, matured over time and complex like a fine wine. Equally interesting were their stories associated with the art and artists; bringing them to life, adding a whole other dimension to the decision. Suddenly, a somewhat imperfect piece of art became worthy of restoration or acquisition with the backdrop of story and history.
Somewhere along the way we lost this expert human filter to the online world and need to bring it back.
Today we are squarely in the world of big-data-driven recommendations for appreciating restaurants, movies, art, wines, travel destinations and more. Terabytes of user-generated likes, ratings, and reviews are generated everyday, inundating us, swaying our decisions this way and that with algorithmically extracted patterns from the “wisdom” of anonymous crowds. This is classic “Yelp” mode and we are in the middle of an epic “filter failure” (Clay Shirky) compounding the information overload.
I am excited about the promise of algorithms powered by big data, but I also believe that in the frenzy to search for an algorithmic solution for all recommendations, we are missing the “human filter”. The human filter is a an expert “in the know”. The human filter angle makes recommendations interesting, makes for serendipity, makes it possible to change our minds and evolve our tastes faster than the algorithm can keep up. It makes us who we are.
As the parent of nine-year old, Los Angeles was largely Disneyland and Universal to me. Having read the restaurant reviews by Jonathan Gold (restaurant critic and self-proclaimed “Belly of Los Angeles”), I want to check out at least a few of his 99 essential restaurants in LA the next time I visit. Had it not been for hyperlocal foodie and 7x7SF.com contributor Antonia Richmond, I would never have discovered El Zocalo and their $2 Tacos in the Bernal neighborhood of San Francisco, and Michelle Syracuse has me intrigued about Amba in Oakland. Of course, such curators or experts have always existed but the new crop of online and social media tools for creating, managing, and distributing “curator generated content” have brought them to the forefront. Suddenly, why Google would buy Zagat and Frommer’s makes sense. In the words of HuffPo about the Zagat acquisition, “Zagat provides Google with much-needed, trustworthy content that can be used to fill out and differentiate Google’s products.” How interesting that both these icons of great recommendations for food and travel started off as purveyors of highly curated content, particularly in the case of Frommer’s, something that he experienced and documented first hand.
At LikeStream, we are building a new service for restaurant recommendations that you can trust. National, local and hyperlocal experts along with the friends you already know are a key and integral part of a new social recommendation system we are building. We are the opposite of the algorithmic black box; transparent, direct, and trustworthy. We are not just about content and ratings; we are about letting you pick your social and local context as well.