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Most of our networked world is a pool of buzzing, fresh interaction - not only hard to predict, but constantly on the sharp edge of making something new. Scientists like Holland call this “emergence”, the way that bottom-up interactions — between cells or chips or traders or cars - create a larger order, often something that was not there before. The fundamental uncertainty of this process means it’s often excluded from the way we look at the world. It’s easier to assume a predictable, linear, complicated logic is at work. An “a leads to b and c” sort of logic: revolution leads to freedom which leads to democracy, for instance. That such predictions are often wrong - and that we’re so often surprised by events in economics or politics - is a reminder that compicated systems are often complex, lit with mechanisms that almost gleefully snap off the fingers of meddling, confident planners. Too often we look at some puzzle - Iraq, income inequality - and think itis merely “complicated.” We should know better. “Macro models failed to predict the crisis and seemed incapable of explaining what was happening to the economy in a convincing manner,” the European Central Banker Jean-Claude Trichet lamented in the aftermath of 2008s cascading, complex financial crises, when markets and officials discovered that the problem with their system was not merely that it was “too big to fail” but also “too connected to manage” - and possibly “too complex to comprehend.” Trichet sounded a little shell-shocked. “As a policy maker during the crisis I found the available models of little help. In fact, I would go further: In the face of the crisis, we felt abandoned by the conventional tools.”1"4 This sense of abandonment comes from an attempt to use a mechanical way of thinking in age of complexity. 145 When you think an air force can simply pound an insurgency to sand or that some old reliable business should survive because it rests upon billions of dollars of infrastructure, you miss the energetic creative and destructive power of complex connection. It’s not fully right to say: Networks always beat hierarchies, because of course networks have layers and structures of their own. But it’s not wrong to consider that complex systems tear easily at stiff, competitive and overly-ordered ones, even the most carefully engineered complicated ones. Think of the mafnicently ornamented dictatorships pushed to collapse in recent years. Or, can you really look at the firm where you work and feel a sense of living, flexible adaption in the face of connection? In our age, the pressure of emerging change is particularly heightened by the very nature of the digital devices themselves. The connected and algorithmic tools all around us now lend themselves to the easy and cooperative interaction. In fact, that 114 Macro models: Jean-Claude Trichet “Reflections on the nature of monetary policy non-standard measures and finance theory”, Speech at ECB Central Banking Conference, Frankfurt, 18 November 2010 115 This sense of abandonment: Michele Catanzaro and Mark Buchanan, “Network Opportunity.” Nature Physics Vol 9, March 2013 p. 121-122 or Cesar A. Hidalgo, “Disconnected! The parallel streams of network literature in the natural and social sciences”, (2015) arXiv:1511.03981 86 HOUSE_OVERSIGHT_018318