Science and policy in designing complex futures

Many complex systems scientists are motivated by making changes to socio-technical systems. Change also motivates policy makers. Thus, both aspire to design new systems and trajectories through time. Science has always been used to forecast the implications of policy. Traditional science predicts system states at precise points in time. Usually point predictions are impossible in the science of complex systems. Most scientists cannot perform in vivo experiments on complex socio-technical systems. They have neither the mandate nor the budget. Massive advances in ICT enable simulation as a powerful new in silico experimental methodology. However, complex systems scientists are unable to collect the huge databases necessary to plan and manage heterogeneous multilevel socio-technical systems—these data are collected by public and private agencies according to perceived policy needs. Most implemented policies are experiments, but the outcome of policy is rarely monitored from a scientific research perspective. To test in silico forecasts against in vivo observation requires data owned by policy makers, requiring completely new data collection protocols that have to be aligned with policy makers. Complex systems scientists must make an obvious added-value contribution to policy, making explicit their role as designers with their science fitting into the policy-driven process of designing, planning, managing and controlling real complex socio-technical systems. Remaining in the loop is essential for policy makers to maintain control over policy objectives as they co-evolve towards the delivered design solution and its implementation.