Big data has imperceptibly changed the everyday life. More and more decisions are done automatically by neural networks trained on big data. This cognitive automation challenges human agency and ask us to rethink what it means to be human in machine learning era. In social sciences and humanities, the human agency is challenged by big data in different way: we can’t observe patterns in millions of digitized images and texts, or millions of hours of ethnographic video without computers trained to detect some things and blind to many overs.
Many uses of big data and machine learning are clearly beneficial to society and cities. Analysis of human mobility can help to improve city services and guide new urban development. Analysis of satellite imagery allows us to estimate levels of economic development and poverty in many world areas where such statistics are not available. Other use of data frighten people in many counties – surveillance systems that analyze face data, Chinese social ratings (approved by majority educated people living in biggest Chinese cities), behavioral advertising (showing us product ads based on predictions about our interests) and the use of exactly the same techniques in election campaigns.
The initial very optimistic view of endless possibilities opened up by data and data science for social and cultural research is replaced today by a more moderate view. If quantitative and big data methods are only part of a researcher toolbox, when we should use them? How to combine different methods for observing, analyzing, and representing everyday life in urban settings? And what exactly is a “city” today? It is not sufficient to say that old categories (“leisure”, “work”, “home”, “city” ...) have blurred, become diffused, and no longer always work. Instead, we may need to develop new categories to see our cities today. Can some of these categories and concepts come from the new worlds of big data and data science? How to bring together ethnography and measurements, explorative view and mathematical predictions, experience and data?
We invite you to talk about these questions in Tyumen on October 10-11.
The conference is designed to have sufficient time for conversations and discussions between speakers and the audience. The invited speakers cover a range of academic and practical disciplines – urban studies, sociology of culture, fashion studies, data visualization, design, data science and media theory.