ABSTRACT
As our understanding of cognitive biases grows, these biases clearly present challenges for accurately forecasting global politics. What does that mean for the path forward? This chapter lays out a new framework for thinking about forecasting and the factors that lead to bias in how we view the world. Three questions are critical. First, what are the things that can be forecast versus those that cannot? Predicting human-driven events such as mass killings or wars is extremely complex. Second, who is doing the forecasting – individuals or groups – and with what incentives for accuracy? Third, how are they doing the forecasting, e.g. what methodology? Some forecasting involves individuals or groups using historical analogies to derive expectations about how countries will behave. Other methods include crowd-sourced forecasting or even machine learning. Breaking down these three questions helps reveal some possible biases that influence forecasting, and thus more and less accurate ways of viewing the world. This has significant relevance both for academia and for the policy world.
