Room B.05
Theoretical insights about decision-making under radical uncertainty
14.00 Navigating Cascades of Uncertainty – Easy as ABC?
Dr Katie Smith, Centre for Ecology and Hydrology
14.30 A dynamic decision making process for evidence based learning on megaprojects
Dr Zhen Chen, University of Strathclyde
15.00 Logical Probability: A Keynesian theoretical foundation for scenario planning
Dr James Derbyshire, Middlesex University
Room B.15
Practical insights about decision-making under radical uncertainty
14.00 The role of formal models in financial decision-making
Dr Ekaterina Svetlova, University of Leicester
14.30 How do executives navigate the radical uncertainties of building environmentally and socially sustainable businesses? A study of framing in decision-making.
Dr Catherine Tilley, University of Cambridge
15.00 How do Effective Altruism Organizations account for Uncertainty?
Dr Simon Beard, University of Cambridge
15.30 Seeking immunity from radical uncertainty in climate change adaptation
Prof Suraje Dessai, University of Leeds
Abstracts below.
No Need for Catastrophism
Iñaki San Pedro, University of the Basque Country, UPV/EHU
Catastrophic talk is commonplace in the context of climate change, especially when it comes to pushing for decision making and action regardless of the uncertainty attached to catastrophic events taking place. In this paper I argue against this sort of approach as an effective way to influence individuals’ capacities for decision making and action. I claim that catastrophe scenarios correspond to possible worlds which are epistemically too far from our present state of affairs. Thus, they are perceived as too unlikely for individuals to be aware of the state of affairs to which they correspond, which in turn diminishes individuals’ urgency for action.
Navigating Cascades of Uncertainty – Easy as ABC?
Dr Katie Smith, Drought Analyst and Modeller, Centre for Ecology and Hydrology
Investigating the uncertainties in scientific studies for decision-making can be undertaken at three levels of complexity, “ABC”. The most complex is “Analyzing” the full range of uncertainty with ensemble experiments; the simplest, “Bounding” of the uncertainty, estimates only the upper and lower limits of likely outcomes; and the intermediary, “Crystallizing” approach, sub-samples the full range of the “Analyze” approach. Typically, modellers dictate the study design, and decision-makers face difficulties interpreting the results. We must consider the applications of scientific outputs when determining our approach. This requires working with decision-makers from the outset, incorporating “D” into the “ABC”: the “Decision-centric” approach.
A dynamic decision making process for evidence based learning on megaprojects
Dr Zhen Chen, University of Strathclyde
This paper presents the author’s latest research into developing a dynamic decision making process (DMP) to support transdisciplinary decision making under uncertainty in megaproject (worth $1bn each) development and operation. The dynamic DMP integrates Analytic Network Process, Artificial Neural Network, and System Dynamics to realize high-performance considerate decision-making underpinned by transdisciplinary evidence based learning; and the novel method is based on previous research relating to megaprojects in the past over ten years. This paper focuses on the theoretical framework of the dynamic DMP with case studies to inform decision-makers to cope with radical uncertainty in megaproject development and operation.
Logical Probability: A Keynesian theoretical foundation for scenario planning
Dr James Derbyshire, Centre for Enterprise & Economic Development Research (CEEDR), Middlesex University
A long-running debate on the use of scenario planning for dealing with radical uncertainty relates to the assignment of probabilities to created scenarios. Some argue against this, suggesting probability to have fundamental flaws when it comes to radical uncertainty; others suggest probabilities are necessary to make scenarios meaningful and comparable. Keynesian ‘Logical Probability’ is a non-numerical form of probability conceived of in qualitative and comparative terms, thereby rendering it appropriate for use in scenario planning. The paper shows that Logical Probability has much to offer as a theoretical foundation for scenario planning because it combines intuition, logic and evidence.
The role of formal models in financial decision-making
Dr Ekaterina Svetlova, University of Leicester
My talk addresses the question “How do decision-makers make decisions under radical uncertainty?“ and discusses how investment professionals use financial models to “overlook” uncertainties. Based on the vast empirical materials (qualitative interviews and participant observations), I suggest understanding financial decision-making as action-like decision-making which implies that more than calculation is required in the always incomplete situation of markets. This “qualculation” (Cochoy 2008) happens in various ways and styles. I empirically open the “black box” of financial decision-making and discuss manifold cultures of model use, that is, specific practices of integrating models into genuinely uncertain financial decision-making and combining them with emotions, views and stories of their users.
How do executives navigate the radical uncertainties of building environmentally and socially sustainable businesses? A study of framing in decision-making.
Catherine Tilley & Steve Evans, University of Cambridge
Businesses are under pressure to operate more sustainably, but introducing environmental and social considerations into decision-making often introduces complexity, uncertainty and tension. Building on the literature, we propose six ways in which executives can frame these problems. We then examine 45 situations in which executives faced decisions involving sustainability considerations, and their choice of framing approach. In this sample, we find that executives use a repertoire of decision-making approaches, which are shaped by the nature of the problem and by the organisational context within which the decision is being made. We conclude with a commentary on further areas for research.
How do Effective Altruism Organizations account for Uncertainty?
Simon Beard, Centre for the Study of Existential Risk, University of Cambridge
Effective Altruism Organizations attempt to prioritize resource allocation between different interventions, across fields including public health, international development, animal welfare and human extinction. As such, they have to deal with many kinds of uncertainty, including uncertainty about the size of the direct impacts of an intervention, the relationship between direct impacts and wider systemic effects and uncertainty stemming from competing values and measurement methodologies across different fields. This paper surveys how four different Effective Altruism Organizations, CSER, Animal Charity Evaluators, GiveWell and 80,000 hours, account for uncertainty in their decision making and draws out key themes and points of conflict.
Seeking immunity from radical uncertainty in climate change adaptation
Suraje Dessai, University of Leeds
This talk will address how decision-makers should cope with radical uncertainty. In a nutshell, they should seek immunity from radical uncertainty. I will explain the philosophy behind robust-decision making and introduce new methods to characterize radical uncertainty in climate change adaptation. We developed an iterative multi-method decision-making under uncertainty approach, which includes scenario generation, co-production with stakeholders and water resource modelling, to assess the robustness of adaptation options and pathways against future climate and socio-economic uncertainties in the Cauvery River Basin in Karnataka, India. The characterization of radical uncertainty in future regional climate through structured expert elicitation of narratives will be introduced.