Much of human inquiry today is focused on collecting massive quantities of data about complex systems, with the underlying assumption that more data leads to more insight into how to solve the challenges facing humanity. However, the questions we wish to address require identifying the impact of interventions on the behavior of a system, and to do this we must know which pieces of information are important and how they fit together. Here we describe why complex systems require different methods than simple systems and provide an overview of the corresponding paradigm shift in physics. We then connect the core ideas of the paradigm shift to information theory and describe how a parallel shift could take place in the study of complex biological and social systems. Finally, we provide a general framework for characterizing the importance of information. Framing scientific inquiry as an effort to objectively determine what is important and unimportant rather than collecting as much information as possible is a means for advancing our understanding and addressing many practical biological and social challenges.
Yaneer Bar-Yam and Maya Bialik, Beyond Big Data: Identifying important information for real world challenges
Via Complexity Digest