UNDERSTANDING AND REWIRING ORGANIZATIONS, CITIES, AND SOCIETIES: A COMPUTATIONAL SOCIAL SCIENCE PERSPECTIVE
The almost universal adoption of mobile phones, the exponential growth in the usage of Internet services and social media platforms, and the proliferation of digital payment systems, wearable devices, and connected objects has led to the existence of unprecedented amounts of data about human behavior. Thus, we live in an unprecedented historic moment where the availability of vast amounts of behavioral data, combined with advances in machine learning, are enabling us to build predictive computational models of human behavior. In my talk, I will show examples of how those computational models of human behavior can be used to better understand and to design more efficient companies, cities, and societies, For example, I will present some recent works where we have leveraged mobile phone data, credit card transactions, Google Street View images, and social media data in order (i) to infer how vital and livable a city is, (ii) to find the urban conditions that magnify and influence urban life, (iii) to study their relationship with societal outcomes such as poverty, criminality, innovation, segregation, and (iv) to envision data-driven guidelines for helping policy makers to respond to the demands of citizens. Finally, I will also discuss key human-centric requirements for a positive disruption of these novel approaches including a fundamental renegotiation of user-centric data ownership and management, the development of tools and participatory infrastractures towards increased algorithmic transparency and accountability, and the creation of living labs for experimenting and co-creating data-driven policies.