Abstract
Due to its high demands on information input, traditional decision theory is inadequate to deal with many real-life situations. If, for instance, probabilities or values are undetermined, the standard method of maximizing expected values cannot be used. The difficulties are aggravated if further information is lacking or uncertain, for instance information about what options are available and what their potential consequences may be. However, under such conditions, methods from philosophical analysis and in particular argumentation analysis can be used to systematize our deliberations. Such methods are also helpful if the framing of the decision problem is contested. The argumentative turn in policy analysis is a widened rationality approach that scrutinises inferences from what is known and what is unknown in order to substantiate decision-supporting deliberations. It includes and recognises the normative components of decisions and makes them explicit to help finding reasonable decisions with democratic legitimacy.
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Notes
- 1.
We use “policy” to refer to “[a] principle or course of action adopted or proposed as desirable, advantageous, or expedient; esp. one formally advocated by a government, political party, etc.” (http://www.oed.com; meaning 4d). However, we do not restrict the use of “policy” to public policies only. In this chapter we neither distinguish between “policy analysis” and “decision analysis” nor between “policy/decision analysis” and “policy/decision support”. Decisions on policies are normative decisions on whether a course of action is e.g. permissible or mandatory. Therefore, in philosophy, policy decisions are analysed as practical decisions, which means that practical arguments which use normative principles are required in order to justify them (Brun and Betz 2016).
- 2.
This is a case of the “test of alternative causes”, see (Hansson 2016).
- 3.
Some attempts have been made to subdivide this large category. However many of these attempts are philosophically unsatisfactory since they unsystematically mix different criteria for subdivision, such as the source of lack of knowledge and the type of knowledge that is uncertain. “Model uncertainty”, for instance, refers to the type of information that is uncertain, namely in this case the model of the decision problem. A model or parts of it could be uncertain for various reasons. One kind of source could be lack of information regarding e.g. parameterizations, the temporal and spatial grid, how to set up the model equations, etc. Another kind of source could be the problem itself, in cases when it is conceived as a system with intrinsic variability as in the case of modeling climate change. For details on model uncertainty in decision support see e.g. Walker et al. (2003).
- 4.
We call the traditional approach of decision theory and policy analysis a reductive approach, because this approach has to disregard most types of uncertainties in order to make the decision accessible to a specific type of formal analysis. The traditional approach is also called “probabilism” (Betz 2016) because it assumes that all relevant probabilities are available.
- 5.
Many attempts have been made to represent uncertainties in somewhat more resourceful formal structures such as probability intervals, second-order probabilities etc. Some of these methods provide a better representation of some aspects of (epistemic) uncertainty than what classical probabilities can do. However, they obviously cannot capture the many other indeterminate factors in complex decisions such as uncertainties about values, about the demarcation of the decision and about its relationship to other decisions by the same or other agents. There is also a trade-off: the richer a formal representation is and the more it deviates from traditional probability functions, the more difficult is it to use it in unequivocal decision rules such as (adapted versions of) expected utility maximization.
- 6.
Since we use “rationality” in a wider sense for decisions under great uncertainty and not in the restricted sense of traditional decision theory, we also use terms like “reasonable” and “sound” for the normative assessment of decisions.
- 7.
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Hansson, S.O., Hirsch Hadorn, G. (2016). Introducing the Argumentative Turn in Policy Analysis. In: Hansson, S., Hirsch Hadorn, G. (eds) The Argumentative Turn in Policy Analysis. Logic, Argumentation & Reasoning, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-319-30549-3_2
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