Hyejin Youn, Ph.D. Kellogg School of Management

Abstract: In this talk, I will talk about two most defining characteristics in our society: urbanisation and innovation. On one hand, ever-expanding urban built environments are centre of population growth, economic engine, and energy consumption. On the other hand, our technology advances increasingly rapidly, transforming both physical and social infrastructures into better or worse contingency. Therefore, understanding fundamental dynamics at the both ends, and bridging them can provide valuable insight into the nature of challenges of sustainability. But, how we can do this? With an increasing volume of data and computational power, these dynamics are now directly quantified, measured, and analysed. Furthermore, the accessibility of detailed data opens up the possibility to recontextualise mathematical and computational tools hitherto implemented only in natural science into complex social and economic systems, whereby their microscopic dynamics can be expressed in a systematic and comprehensive way. The talk will give a few empirical analyses that show how this new approach has uncovered interesting nature of the dynamics. Take urban studies for example. We now have access to each city's economic fabric such as where people live and work, and how and when they commute between them; their average wages and income levels; their associated occupations and workplaces, and sets of skills that are required to accomplish a task; and what kind of topics that are communicated. Analysing these datasets reveals that cities, operating intricate interactions, nonetheless exhibit self-similar patterns, and thus their quantities are expressed by a set of simple scaling laws.Take another example of innovation, commonly recognised as an important source of wealth creation, economic growth, and societal change, and perhaps, one of the main reasons for city's existence. There are growing empirical data to identify the dynamics of innovation, such as, to name a few, scientific publication, patent data, and Google n-gram. Piecing these datasets together amounts to a good representation of technological change as combinations of existing ideas. It has been observed that the combinatorial landscape is modulated, and the structural change demarcates technological eras. Under this framework, coupled with human society data, we can look at the interplay between human society and technological change at all levels. One example, which will be shown in this talk, is how to predict technological unemployment in urban areas. The task requires us to collect and maintain large, complex datasets, and to bring together and coordinate experts of different fields - computation, mathematics, economics and sociology.

Biography: Hyejin Youn is an Assistant Professor of Management & Organization Department at the Kellogg School of Management, and a core faculty at NICO, the Northwestern Institute on Complex Systems. She is also Royal Society of Arts fellow, and an external fellow at London Mathematical Laboratory, London, UK. Prior to joining Kellogg, she worked at University of Oxford, Harvard University, and MIT Media Lab, and Santa Fe Institute, as a research fellow. Hyejin received her PhD in Physics in 2011 from Korea Advanced Institute of Science and Technology (KAIST). She was a Principal Investigator of the project a National Science Foundation grant (USA) to study Technological Change from the Map of Capabilities.