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 behaviour. Thus, we live in an unprecedented historic moment where the availability of vast amounts of behavioural data, combined with advances in machine learning, are enabling us to build predictive computational models of human behaviour.
In this talk, I will show examples of how those computational models of human behaviours 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 liveable 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 infrastructures towards increased algorithmic transparency and accountability, and the creation of living labs for experimenting and co-creating data-driven policies.
About the speakers
Dr Bruno LepriAffiliation: Bruno Kessler Foundation
Bruno Lepri leads the Mobile and Social Computing Lab at Bruno Kessler Foundation (Trento, Italy). Bruno has also recently launched an alliance between MIT Connection Science and Bruno Kessler Foundation. He is also the Head of Research of Data-Pop Alliance, the first think-tank on big data and development co-created by the Harvard Humanitarian Initiative, MIT Media Lab, Overseas Development Institute, and Flowminder. In 2010 he won a Marie Curie Cofund post-doc fellowship and he has held a post-doc position at MIT Media Lab. He holds a Ph.D. in Computer Science from the University of Trento. He also serves as consultant of several companies and international organizations. Recently, he co-founded Profilio, a startup active in the field of AI-driven computational marketing. His research interests include computational social science, personality computing, urban computing, network science, machine learning, and new models for personal data management and monetization. His research has received attention from several international press outlets and obtained the James Chen Annual Award for best UMUAI paper and the best paper award at ACM Ubicomp 2014. His work on personal data management was one of the case studies discussed at the World Economic Forum.