Critical Systems Talk: The Secret Life of (our) Data: Measuring and Mapping Society with Hyper-Resolution

Big Data is a buzzword for a technological megatrend, an economical disruption, but perhaps more importantly, a forceful agent for societal change. The change is so fundamental that we may fail to realize its full reach, even when acknowledging threads to privacy or the rising power of data-hungry organizations. This is in particular true for personal data, which gets collected at massive scale and at hyper-resolution accuracy. We are in a crisis, at a point of fundamental change, a technological singularity, perhaps, that will shape the workings of our society in ways that challenge not only our understanding, but also our imagination. What is urgently needed today is critical thinking, maybe even a new critical theory, as we are faced with mechanisms of power and social control that by their very nature tend to camouflage themselves.

In this talk, Thomas Hofmann will aim to take known surface truths in the general area of collecting data about human activity on massive scales and relate them to technological advances and novel methods of data modeling. The goal is to expose the very nature of data in a digital society and to make visible the principles and mechanisms that are at work. We need to understand why and how we are all subjected to measurement and how this leads to a historic, instantaneous, and predictive mapping of our society. We need to understand the secret life of (our) data, if we want to continue living in a society that guarantees personal freedom and democratic participation.


Thomas Hofmann is Full Professor at the Department of Computer Science at the ETH Zürich. After studying computer science and philosophy, he received a PhD in computer science from the University of Bonn in 1997. He held postdoctoral positions at the Massachussets Institute of Technology as well as the University of California at Berkeley and the International Computer Science Institute. He worked as first Assistant and then Associate Professor of Computer Science at Brown University, was Director at the Fraunhofer Institute IPSI as well as Professor at the Technical University Darmstadt. In 2001 he founded Recommind and from 2006 to 2013 he was Director of Engineering for Google Switzerland. His research areas include machine learning, information retrieval, natural language processing, data analytics, big data, knowledge management. See Hofmann's website.



The talk is followed by a joint lunch.



2A54 at IT University of Copenhagen