Editorial Introduction to Issue 48 of CSIMQ: Reducing Uncertainty of Complex Socio-Technical Systems

Abstract

This issue of CSIMQ continues the examination of different characteristics of complex socio-technical systems, such as the relationship between psychological and technical factors in the automation of routine tasks, hidden insights from data analytics, and reducing uncertainty in complex and distributed systems. The first two studies examine automation of routine tasks and operations to reduce resource consumption such as energy, human labor, and time. Both studies consider Higher Education Institutions as their primary application areas. The next articles are devoted to applications of artificial intelligence-based solutions to infer hidden states in e-commerce sentiment analysis and to predict future events to better prepare for infrastructure failure mitigation in the energy sector. The issue concludes with research on rule analysis in complex, decentralized environments.