Throughout history, people have wished to know what the future holds for them. We may often wonder whether we need to bring an umbrella on the way to the laboratory, or what life might be like when we retire. This curiosity about the future has eventually led us to try to construct forecasts. Now with modern computing power, the number of possibilities for forecasting has skyrocketed. Recently I have been exploring the wonderful world of modelling social phenomena and working to understand how human development, a truly complex system, could be modelled. But once we have this understanding, how can we convey it to the people who want or need to predict human development?
Some systems are harder than others to make a prediction about. For social systems, interactions between variables are especially difficult to model. This is due to their tremendous complexity and possibly disruptive changes in technology and policies that could completely change social dynamics.
In a recent paper by Shyam, Viktoria, Richard and David (S. Ranganathan et al. Bayesian dynamical modelling in the social sciences 2014) a new method was developed for modelling dynamical systems in the social sciences. This new method has been used to study the relationships between gross domestic product (GDP) democracy development and child mortality, to name a few. In an upcoming paper, this methodology is used to quantify, test and model the newly UN adopted set of Sustainable Development Goals. In this paper, they find goals that are consistent, but also conflicting. I recommend having a look to explore their findings yourself. You will find it here (The Sustainable Development Oxymoron: Quantifying and Modelling the Incompatibility of Sustainable Development Goals)
We are now working on a visualisation tool to make findings like these, and future studies more accessible to the general public. Politicians and other policy makers can use this tool to get an idea about what impact their decisions actually might have in a more quantifiable way.
Emil Rosén and I have built a web application where you can see the global historical development of GDP and child mortality visualised on a world map using a Google API. What we also have included is a forecast about what the future might hold, including confidence intervals. Everything built with scientific models is underneath the hood. In our opinion, this is a useful way of visualising and increasing accessibility of scientific findings. If you click on specific countries on the interactive world map you will also get additional figures for more in-depth exploration and comparisons. Go in and have a look for yourself.