Monday, December 04, 2017

The Square and the Tower – networks and hierarchies

The Square and the Tower by Niall Ferguson takes the public square in Sienna and the tall tower that looms above, as a metaphor for flat, open networks and their accompanying hierarchical structures.
My friend Julian Stodd starts his talks with a similar distinction between open, flat networks and formal, hierarchical structures (although both are networks, as a hierarchy is just one form of network). Networks tend to be more creative and innovative, hierarchies more restricted. In most contexts you need both. Ferguson’s point is that history shows that both have been around for a very long time. Indeed, he tries to rewrite history in terms of these two opposing forces. He sees history through the lens of networks, the main distinction being between disruptive networks, often fuelled by technology, such as tool making (stone axes etc.), language, writing, alphabets, paper, printing, transport, radio, telegraph television and the internet; then institutional hierarchies such as families, political parties, companies and so on. Networks come in all shapes and sizes. In terms of communities we have criminal networks, terrorist networks, jihadi networks, intelligence networks, and so on. In terms of technology, social networks, telephone networks, radio networks, electricity networks. History, he thinks, understates the role of networks. We now even have cyberwars between networks. This is age of networks.
Technologies and networks
We can trace this back to the fact that we are a species that has evolved to ‘network’. Our brains are adapted towards social interaction and groups. We, the co-operative ape, have distributed cognition and this has increased massively as technology has allowed us to network more widely. Technologies have been the primary catalysts. Nevertheless, much human behaviour has been tempered with Chiefs, Kings, Lords, Emperors and so on… hierarchical structures that lead and control, even the web is now spun by hierarchical and rapacious spiders – the giant tech companies. His analysis of Europe’s failure is interesting here, as we have Apple, Google, Facebook, Amazon, Microsoft and Netflix in the US, and Baidu, Alibaba and TenCent in China. Europe merely regulates. These Oligopolies, dominate the networks.
The study of networks goes back to Euler’s seven bridges problem with a more fulsome look at nodes, edges, hubs and clusters. What is clear is that networks are rarely open and low density. They collapse into clusters and tribes. This in itself still produces, not so much six degrees of separation (actually closer to five), as 3.57 if you are on Facebook. There is an attempt to identify common features of networks; No man is an island, Birds of a feather flock together, Weak tis are strong, Structure determines virology, Networks never sleep, Networks network, The rich get richer.
Then, by example, he takes some deeper dives into the Medicis, as he regards the Renaissance as the first of the truly networked ages. Then the age of discovery, the catalysts being navigational technology and trade networks. But the big disruptive network was the Reformation, partially caused by printing. The fact Luther did (or did not) nail his 95 theses to the door is beside the point. What matters is the printing press that allowed the spread of these ideas and freedom of expression to challenge the hierarchy of the church. The control of language through Latin and of knowledge through scripture was blown wide open.

From the Reformation came Revolutions, again fuelled by print and networks. In addition financial networks, sometimes ruled by family hierarchies, such as the Rothschilds. Scientific and industrial networks flourished giving us industrial revolutions. Intellectual networks such as The Apostles in England and the Bloomsbury Group. Marxism, Leninism, Stalinism, Maoism were infectious networked ideas.
Networks and hierarchies in organisations
Whatever the structure of your networks, communications, emails, social media posts, slack posts, blogs, stories and many other instances of social conversations will happen, over time. How does an organisation deal with all this, optimise these networks and drive performance?
First we have to recognise that social  both helps and inhibits performance. Open networks often collapse into powerful tribes of belief and power. Social activity is messy, soaked in biases and can be negative in output. Some of these tribes may be good and useful, where they generate innovation and get things done. But there’s also the crippling effects of the mob and its tribes that generate and consolidate groupthink and false beliefs. Gangs form but gangs are not often good.

A solution to this dilemma is to interrogate networks, harvest the data, objectify the process and analyse it to exclude mess and bias. One can look for insights, innovations and valid ideas, to separate the social wheat from the chaff. AI can come to the rescue here.

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