Introduction

In order to respond effectively to the challenge of preparing a sustainability transition, major changes in the socio-economic system of modern society will have to be envisaged. Some earlier and simpler environmental problems could be tackled, for example, by reducing toxic by-products of a few production processes. However, responses to prospects of, for example, climate change will require large shifts right at the heart of our industrialized cultures, especially in the manner in which we use energy and produce greenhouse gases in the process. Referring to reduction scenarios discussed in the context of the Intergovernmental Panel on Climate Change (IPCC), Kempton (1991) has stressed that “if world leaders decide to reduce greenhouse gas emissions by two-thirds, such a large reduction will require consumer and worker co-operation as well as citizen consent that major societal changes are worth the effort.” Responses to global environmental change will only be effective if they have clear public support.

Understanding the reactions of citizens to prospects of climate change and related policy options is thus a central element in developing effective climate policies. Studies on this issue can build upon a large body of research on environmental consciousness and behavior in general (see, e.g., the comprehensive overview by Brand 1997). In the last few decades, a variety of studies have focused specifically on perceptions of climate change issues (see, e.g., the overview by Jaeger et al. 1993; and by Thompson and Rayner 1998).

Introduction

This chapter looks at how computer models were used in IA Focus Groups within the study discussed in this volume. In these groups, different computer models – ranging from complex and dynamic global models to simple accounting tools – were used in the second phase of the procedure. Based on a total of 52 IA Focus Groups with citizens, conducted in six European and one US cities, selected empirical results are presented. The analysis of the results focuses on the added value of using computer models during the meetings of such groups, the lessons learned about the models themselves and the ways in which they are used.

The terminology in this field is far from clear. For the purpose of this chapter, we define computer models as all kinds of software tools that include a realistic representation of some social, economic or environmental processes. Integrated Assessment Models (IAM) are included in this definition, but also simpler and non-dynamic tools. On the other hand, by this definition, we are excluding computer games (SimCity and the like) and educational software with text only.

Why use computer models in participatory processes for sustainability science in general, and Integrated Assessment (IA) in particular? We hypothesize that computer models are powerful tools for promoting a numbers of insights about complex sustainability issues like climate change. Computer models provide direct access to expertise and due to their flexibility and interactivity might be better able to support learning processes and decision-making.