Urban Serendipity - Manufacturing good luck using network science
A Talk by Orit Gal (Entrepreneur, advisor, senior lecturer in Strategy & Complexity, Regents University London)
About this Talk
Serendipity is the unintentional discovery of beneficial resources; in cities, this is all about discovering other people – random collisions between strangers leading to flows of ideas, resources, and, at times, further friendships and collaborations. This talk will cover how we can increase urban serendipity and maximize positive social encounters. You'll learn about network science principles that you can apply to complex graph analysis and forge better outcomes.
Jeffery West famously described cities as simply the manifestations of their underlying human networks. From a social evolutionary perspective, they have evolved to maximise human collaboration and innovation across ever larger groups of people.
Urban networks feed on a density of interactions between strangers. Yet today's technological advances in the ways we work, live, and play have taken out many positive friction points via which previous serendipitous collisions occurred - from the daily trip to the shops, queuing for errands, simply being bored on commutes, or asking someone for directions or a lighter.
With 75% of humanity expected to live in cities by 2040, the big question is, how can we harness our new ways of living to introduce new serendipitous enablers?
We'll quickly overview our study, which aims to identify new patterns in network behavior within the urban space. You'll hear how city leaders can use those patterns to encourage positive social friction using both physical and digital design.
You'll learn why all complex systems thrive best within Goldilocks conditions across multiple dimensions or systemic functions. With the right network structures, degrees of freedom, and information flows, such systems are perfect connectors that maximise opportunities. This is the true magic of cities and high-performing networks.
Join this talk and learn how to use network and graph theory to understand urban data, uncover patterns for complex problem-solving, and promote better outcomes.