Thinking about the Future

Abstract

Abstract The five projective inference methods of statistical forecasting and modeling, technological forecasting, constructing future scenarios, configurative analysis, and robust decision-making (RDM) evaluate the possibility, attainability, and sustainability of plans or projections about the future such as a new constitution for a fledgling democratic republic in 1787–89, a transcontinental railroad in the 1860s, and a California Global Warming Solutions Act (AB 32) in 2006. This chapter considers these five approaches to the projective inference problem of portraying causal relationships leading to future outcomes. The first two (statistical and technological forecasting) ask what is likely and focus on determining the probabilities of relationships and outcomes. The second two (scenario and configurative analysis) ask what is possible and best and focus on the values embedded in outcomes. The last one (RDM) asks what must be avoided or can be adventitiously exploited and focuses on robust actions and decision-rules to produce acceptable and sustainable outcomes. These different questions and emphases lead to different methods and procedures—all of which constitute legitimate forms of projective inference based upon modern understandings of scientific method reviewed in the last part of the paper. Because projective inference is important and because it poses special problems, political methodologists should pay more attention to it and develop better methods and standards for doing it.