The science of complex systems provides the framework for understanding patterns of behavior, and their emergence, at multiple scales in social and other types of systems. The analytical toolsets provided by AI and Machine Learning are good to recognize and measure such patterns in the data. The combination of pattern recognition and generation mechanisms provides an opportunity to advance our understanding of the complexity of real systems. Ultimately, we could benefit from such complexity, rather than being endangered by it, design better technologies, decisions and strategies.
- Show new ways to model complex and social systems by means of big data analysis, machine learning and AI.
- Explore new ways to analyze the data, taking into account the complexity of underlying systems.
- We would like to address how to formulate the right questions and retrieve the relevant information.
The opportunities available from big data and machine learning could solve challenging problems but we must analyze and interpret the data properly. Wrong assumptions and simplified views could separate modeling from reality. We expect to raise awareness about interventions in complex systems, the risk we face when societies become global, the opportunities that are created, and the role of complexity in data analytics.