10.04 Cooperation in Situations of Radical Uncertainty
Aim of the project
Ideally policy interventions are justified by appropriate ethical considerations and empirical support. External shocks can put pressure both on existing policies, and on the development and implementation of new policies, thereby re-shaping the balance between the epistemic and the ethical dimension of informed decision making. This becomes particularly pressing in cases of radical uncertainty, i.e., situations in which we lack important information about the probabilities or nature of the possible outcomes of our decisions. Taking advanced models of rational choice and collective decision making as normative guideline, and using policy making regarding COVID-19 as case study, the research investigates the pros and cons of different heuristics for situations of radical uncertainty.
Concretization
Policy making in the context of sustainable cooperation involves an interplay between epistemic and evaluative considerations. This interplay is subject to study both in philosophy (philosophy of science, moral and political philosophy) and the sciences and is underscored by the importance of evidence-based policy making. Key questions are: what kind of results and insights best support the design of evidence-based policy making, how are the values of cooperation identified, and how can the policy-making process be organized socially to ensure that it is sufficiently informed by empirical insight, and not hampered by collective misperceptions of risk?
In times of crisis that are characterized by radical uncertainty, that is, by the absence of relevant information about the possible consequences of our decisions, the role division between scientific researchers and decision-makers is challenged. For example, policy makers may decide to disregard scientific advice under the pressure of public opinion. Conversely, scientists may be pushed into the role of decision makers, and policy makers may co-opt them to motivate or justify their policies, thereby possibly disregarding existing procedural safeguards for control. In practices of evident-based policy, the dividing lines between the domains of fact and value will inevitably get blurred but in the face of radical uncertainty natural mechanisms for balancing these domains can fail if there is a lot at stake.
To illustrate, possible indications of failures in the response of the Dutch government to the recent COVID-19 crisis are:
- Evidence-based decision making: Closure of primary schools was largely motivated by public unrest, despite the RIVM’s early findings indicating that children played only a minor role in the transition of corona infections. Here public sentiments and the opinion of medical professionals exerted different pressures on the decision process.
- Coherence: In the early stages of the pandemic, protective face masks were deemed ineffective for the general public but effective for medical care workers.
- Procedural transparency: It was not clear on the basis of which heuristics for decision making in situations of uncertainty the Outbreak Management Team gave its advice about interventions.
- Legitimacy: Statisticians and scientists criticized governmental and advisory bodies (RIVM, OMT, Ministry of Health, etc.) for failing to seek help with data analysis and not upholding standards of Open Science. The various governmental bodies were under pressure to send unambiguous signals to the general public, and were struggling to represent uncertainties adequately while at the same time maintaining their authority in the public sphere.
Taking the recent COVID-19 crisis as its primary case study, this research project will develop and analyze heuristics for collective decision making under radical uncertainty.
Research design
This project investigates the practice of evidence-based policy making from the point of view of normative adequacy. We take individual choice theory to provide a useful starting point for the analysis of decision making under uncertainty but also argue that it should be expanded so as to be able to yield guidelines for situations of radical uncertainty and for its collective nature. Collective and emergent decision dynamics will be analyzed, and their role in policy-making will be evaluated.
- The project will start with a reconstruction and appraisal of the decision-making processes during the COVID-19 crisis. Questions of particular interest here are:
What decision-theoretic principles were implicitly adopted by the decision-making bodies, e.g., the OMT and RIVM, and which values were considered? - Which facts were presented as value-free, and how did these purportedly neutral facts impact the political decision making?
- Which decision procedures were used and how did they affect the legitimacy of the decisions?
- How did the decisions coming from experts and institutions shape collective risk perception and what impact did the resulting opinions have on policy decisions?
The main part of the project will consist of the development of a theory of policy making under radical uncertainty in a multi-agent context. It will give a precise description of the nature of these situations, will make clear how epistemic and evaluative considerations are incorporated in it, and what kind of decision rules ('heuristics') can be defended for the cooperation between the agents involved. In the concluding part of the project, the resulting account will be used to assess the policies regarding financial support for firms and businesses in the face of a global external shock like COVID-19.
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PhD
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Helena Slanickova
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Supervisors
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Dr. C. M. F. (Chloé) de Canson
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Dr. F. (Francesca) Giardini
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Prof. dr. J.W. (Jan-Willem) Romeijn
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Prof. dr. M. (Martin) van Hees
- Discipline
Philosophy, Sociology - Location
University of Groningen, Faculty of Philosophy, Department of Theoretical Philosophy - Period
Started January 1, 2022
Literature
Cartwright, N. (2007). Hunting causes and using them: Approaches in philosophy and economics. Cambridge University Press.
Cartwright, N., & Hardie, J. (2012). Evidence-based policy: A practical guide to doing it better. Oxford University Press.
Douglas, H. (2009). Science, policy, and the value-free ideal. University of Pittsburgh Pre.
Kay, J., & King, M. (2020). Radical uncertainty: Decision-making beyond the numbers. WW Norton & Company.
Solomon, M. (2015). Making medical knowledge. Oxford University Press.