Vincent Marchau

TL;DR: Examination of the processes sheds light on ways to improve the usefulness of TFA to a variety of potential users, from corporate managers to national policy makers, to better inform technology management as well as science and research policy.

TL;DR: In this paper, the authors focus on both the theory and practice associated with the tools and approaches for decisionmaking in the face of deep uncertainty, and present an open access book on decision making in deep uncertainty.

TL;DR: In this article, an extensive review of the literature that builds on Walker et al. (2003) is presented, which can be used to assess and communicate uncertainties in model-based policy analysis studies.

Abstract: Decisionmaking for the future depends on anticipating change. And this anticipation is becoming increasingly difficult, thus creating anxiety when we seek to conform short-term decisions to long-term objectives or to prepare for rare events. Decisionmakers, and the analysts upon whom they rely, have had good reason to feel decreasing confidence in their ability to anticipate correctly future technological, economic, and social developments, future changes in the system they are trying to improve, or the multiplicity and time-varying preferences of stakeholders regarding the system’s outcomes. Consider, for example, decisionmaking related to the consequences of climate change, the future demand for and means for providing mobility, the planning of mega-scale infrastructure projects, the selection of energy sources to rely on in the future, the role of genomics in health care, or how cities will develop. Or think of rare events like a natural disaster, a financial crisis, or a terrorist attack. 1.1 The Need for Considering Uncertainty in Decisionmaking Decisionmaking for the future depends on anticipating change. And this anticipation is becoming increasingly difficult, thus creating anxiety when we seek to conform short-term decisions to long-term objectives or to prepare for rare events. DeciV. A. W. J. Marchau (B) Nijmegen School of Management, Radboud University, Nijmegen, The Netherlands e-mail: v.marchau@fm.ru.nl W. E. Walker Faculty of Technology, Policy & Management, Delft University of Technology, Delft, The Netherlands P. J. T. M. Bloemen Staff Delta Programme Commissioner, Ministry of Infrastructure and Water Management, The Hague, The Netherlands e-mail: pieter.bloemen@deltacommissaris.nl S. W. Popper Pardee RAND Graduate School, RAND Corporation, Santa Monica, CA, USA © The Author(s) 2019 V. A. W. J. Marchau et al. (eds.), Decision Making under Deep Uncertainty, https://doi.org/10.1007/978-3-030-05252-2_1 1 2 V. A. W. J. Marchau et al. sionmakers, and the analysts upon whom they rely, have had good reason to feel decreasing confidence in their ability to anticipate correctly future technological, economic, and social developments, future changes in the system they are trying to improve, or the multiplicity and time-varying preferences of stakeholders regarding the system’s outcomes. Consider, for example, decisionmaking related to the consequences of climate change, the future demand for and means for providing mobility, the planning of mega-scale infrastructure projects, the selection of energy sources to rely on in the future, the role of genomics in healthcare, or how cities will develop. Or think of rare events like a natural disaster, a financial crisis, or a terrorist attack. These topics are all characterized by what can be called “deep uncertainty.” In these situations, the experts do not know or the parties to a decision cannot agree upon (i) the external context of the system, (ii) how the system works and its boundaries, and/or (iii) the outcomes of interest from the system and/or their relative importance (Lempert et al. 2003). Deep uncertainty also arises from actions taken over time in response to unpredictable evolving situations (Haasnoot et al. 2013). In a broad sense, uncertainty (whether deep or not) may be defined simply as limited knowledge about future, past, or current events (Walker et al. 2013). With respect to decisionmaking, uncertainty refers to the gap between available knowledge and the knowledge decisionmakers would need in order to make the best policy choice. This uncertainty clearly involves subjectivity, since it relates to satisfaction with existing knowledge, which is colored by the underlying values and perspectives of the decisionmaker (and the various actors involved in the decisionmaking process). But this in itself becomes a trap when implicit assumptions are left unexamined or unquestioned. Uncertainty can be associated with all aspects of a problem of interest (e.g., the system comprising the decision domain, the world outside the system, the outcomes from the system, and the importance stakeholders place on the various outcomes from the system). The planning for the Channel Tunnel provides an illustration of the danger of ignoring uncertainty. Figure 1.1 shows the forecasts from different studies and the actual number of passengers for the rail tunnel under the English Channel. The competition from low-cost air carriers and the price reactions by operators of ferries, among other factors, were not taken into account in most studies. This resulted in a significant overestimation of the tunnel’s revenues and market position (Anguara 2006) with devastating consequences for the project. Twenty years after its opening in 1994, it still did not carry the number of passengers that had been predicted.1 Climate change presents a fundamental challenge to bringing analytical insight into policy decisions because of deep uncertainties. Climate change is commonly mentioned as a source of deep uncertainty. The question of assigning probabilities to future scenarios of climate change is particularly controversial. While many argue that scientific uncertainty about emissions simply does not allow us to derive reliable probability distributions for future climate states, others counter by saying that the 1The projected traffic growth is still far from being achieved, “In 2017, about 21 million passengers, on all services, have travelled through the Channel Tunnel” http://www.eurotunnelgroup.com/uk/ eurotunnel-group/operations/traffic-figures/.