(Note: This is a piece is part of a larger exploration I’m working on around serendipity. You can find all the articles here.)
It would be impossible to explore serendipity and not spend a lot of time thinking about networks. Even subjectively, we equate people’s connectedness to be an indicator of their good fortune. As you might guess, this is only part of the story. I’m learning that there are some surprising elements of how networks actually foster better conditions for serendipity, here’s a few.
Strong and Weak Ties
So, as is pretty well documented, networks are made up of strong and weak ties. To understand how these ties play with serendipity, it’s good to think about what sort of data flows they facilitate. Strong ties are the deeper relationships that exist in your life. It’s likely that you have similar values as your strong ties, and that they might connect you to new opportunities. As Reid Hastings recently blogged, “if you’re looking for opportunity, you’re really looking for people.”
When we’re searching for serendipity (which is different than opportunity), it turns out strong ties might not be as helpful as weak ties. Because of the redundancy, they become a bad place to look for new stimulus. For serendipity, the weak ties are much more valuable as they’re likely to contain a less considered point of view, or a divergent thought.
As a side note: Through this lens on networks, the design process and the view on serendipity are almost identical. If you want new ideas and inspiration, go to a place you would never expect; you’re looking for extreme examples of style. If you stay with familiar sources of inspiration, it’s going to be very hard to move past previous thought.
For fun, LinkedIn has a great app that visualizes your network based on the connections you’ve created in their service. It’s pretty interesting to see the major grouping and the proportions in your connections.
The Myth of the Maven
One of the more interesting stories I came across in my research was this story of a Yahoo researcher disproving Malcolm Gladwell’s maven concept set forth in his famous Tipping Point text. In 2008, Duncan Watts published a paper that proved that it wasn’t actually a small, powerful group of influencers in that encouraged massive change. The masses basically adopted something when they collectively wanted it.
While this is unfortunate for Gladwell, it leads us to this reminder that networks themselves have a preference, and they collectively filter and promote. In the infancy of the net, it was predicted that one day we would have a great collective discourse that would drive change. Sadly, this never happened, the networks propensity to act as a hive mind leaves us more polarized than curious. So given the limits of our own networks it becomes important to work across many desperate networks.
When we think about how networks filter for content, we’ll do better spending time where there’s a large amount of anonymity and the community acts as a meritocracy. With these principles, you’re dialing down the social influencers and dialing up the influencers based on their ideas. Dribbble, Pinterest, and Svpply are sort of designed to function this way; they allow people to navigate content based on weak ties and function largely on merit (rather than influence.) So these are digital examples that encourage serendipity. While Eric Schmitt is known for referring to Google as a “serendipity engine“, I can’t agree – there’s been so much work to refine and hone that search algorithm, you won’t walk away with anything except exactly what you were looking for.
Growth through Steroids
As we think about how technology is changing how we experience serendipity, one of the first places my mind goes is this explosive growth in our networks. It’s distorting the way we think about the people we know. Casual connections become recorded into permanence as technology helps us track everything.
We’ve blown way past Dunbar’s number of 150 (at least in our online friend metrics.) And thanks to Facebook, the six-degrees of separation is down to 4.74. Beyond the connections, these networks have become social spectacle in their own right as we track each other’s relationships and careers. And as tacit concepts like networks become more explicit, taking on different roles in our lives, we begin to use them for different purposes and distort some of the underlying principles. (See: Klout.com)
There’s a consistent “inversion theme” running through most of this research. The things I perceive to be the most important aren’t usually as impactful as what initially appear to be edge pieces. While the network is an important deciding factor of what you experience, what is convenient doesn’t really seem to yield what you hope (the network has an inbred opinion.)
To combat all this, you have to have the natural curiosity to find new inspiration that fuels this recombination that births serendipity. Also, to actively work with serendipity and force new collision means that you always have to work with the meta level; how/why you’re solving the problem you’re working on is as important as the actual problem you solve…