I’d like to tell the story of a paradox: How do we bring the right people to the right place at the right time to discover something new, when we don’t know who or where or when that is, let alone what it is we’re looking for? This is the paradox of innovation: If so many discoveries — from penicillin to plastics – are the product of serendipity, why do we insist breakthroughs can somehow be planned? Why not embrace serendipity instead?
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The final piece is the network. Google has made its ambitions clear — as far as chairman Eric Schmidt is concerned, the future of search is a “serendipity engine” answering questions you never thought to ask. “It’ll just know this is something that you’re going to want to see,” explained artificial intelligence pioneer Ray Kurzweil shortly after joining the company as its director of engineering.
One antidote to this all-encompassing filter bubble is an opposing serendipity engine proposed by MIT’s Ethan Zuckerman. In his book, Rewire, he sketches a set of recommendation and translation tools designed to nudge us out of our media comfort zones and “help us understand whose voices we’re hearing and whom we are ignoring.”
As Zuckerman points out, the greatest threats to serendipity are our ingrained biases and cognitive limits — we intrinsically want more known knowns, not unknown unknowns. This is the bias a startup named Ayasdi is striving to eliminate in Big Data.Rather than asking questions, its software renders its analysis as a network map, revealing hidden connections between tumors or terrorist cells, which CEO Gurjeet Singh calls “digital serendipity.”