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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
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.
References
Alexander, E. R. (1975). The limits of uncertainty: A note. Theory and Decision, 6, 363–370.
Bengtsson, L. (2006). Geo-engineering to confine climate change: Is it at all feasible? Climatic Change, 77, 229–234. doi:10.1007/s10584-006-9133-3.
Betz, G. (2010). What is the worst case? The methodology of possibilistic prediction. Analyse & Kritik, 32, 87–106.
Betz, G. (2012). The case for climate engineering research: An analysis of the “arm the future” argument. Climatic Change, 111, 473–485. doi:10.1007/s10584-011-0207-5.
Betz, G. (2016). Accounting for possibilities in decision making. In S. O. Hansson & G. Hirsch Hadorn (Eds.), The argumentative turn in policy analysis. Reasoning about uncertainty (pp. 135–169). Cham: Springer. doi:10.1007/978-3-319-30549-3_6.
Brun, G., & Betz, G. (2016). Analysing practical argumentation. In S. O. Hansson & G. Hirsch Hadorn (Eds.), The argumentative turn in policy analysis. Reasoning about uncertainty (pp. 39–77). Cham: Springer. doi:10.1007/978-3-319-30549-3_3.
Brun, G., & Hirsch Hadorn, G. (2008). Ranking policy options for sustainable development. Poiesis & Praxis, 5, 15–30. doi:10.1007/s10202-007-0034-y.
Burgos, R., & Defeo, O. (2004). Long-term population structure, mortality and modeling of a tropical multi-fleet fishery: The red grouper epinephelus morio of the Campeche Bank, Gulf of Mexico. Fisheries Research, 66, 325–335. doi:10.1016/S0165-7836(03)00192-9.
Churchman, C. W. (1967). Wicked problems. Guest editorial. Management Science, 14, B141–B142.
Doorn, N. (2016). Reasoning about uncertainty in flood risk governance. In S. O. Hansson & G. Hirsch Hadorn (Eds.), The argumentative turn in policy analysis. Reasoning about uncertainty (pp. 245–263). Cham: Springer. doi:10.1007/978-3-319-30549-3_10.
Dryzek, J. S. (1993). Policy analysis and planning: From science to argument. In F. Fischer & J. Forrester (Eds.), The argumentative turn in policy analysis and planning (pp. 213–232). London: University College London Press.
Edvardsson Björnberg, K. (2016). Setting and revising goals. In S. O. Hansson & G. Hirsch Hadorn (Eds.), The argumentative turn in policy analysis. Reasoning about uncertainty (pp. 171–188). Cham: Springer. doi:10.1007/978-3-319-30549-3_7.
Eisenführ, F., Weber, M., & Langer, T. (2010). Rational decision making. Berlin: Springer.
Elliott, K. C. (2016). Climate geoengineering. In S. O. Hansson & G. Hirsch Hadorn (Eds.), The argumentative turn in policy analysis. Reasoning about uncertainty (pp. 305–324). Cham: Springer. doi:10.1007/978-3-319-30549-3_13.
Gee, J. P., & Handford, M. (2012). Introduction. In J. P. Gee & M. Handford (Eds.), The Routledge handbook of discourse analysis (pp. 1–6). London: Routledge.
Goldberg, J. (2003). The unknown. The C.I.A. and the Pentagon take another look at Al Qaeda and Iraq. The New Yorker. http://www.newyorker.com/magazine/2003/02/10/the-unknown-2. Accessed 21 May 2015.
Grüne-Yanoff, T. (2016). Framing. In S. O. Hansson & G. Hirsch Hadorn (Eds.), The argumentative turn in policy analysis. Reasoning about uncertainty (pp. 189–215). Cham: Springer. doi:10.1007/978-3-319-30549-3_8.
Grunwald, A. (2016). Synthetic biology: Seeking for orientation in the absence of valid prospective knowledge and of common values. In S. O. Hansson & G. Hirsch Hadorn (Eds.), The argumentative turn in policy analysis. Reasoning about uncertainty (pp. 325–344). Cham: Springer. doi:10.1007/978-3-319-30549-3_14.
Hajer, M., & Versteeg, W. (2005). A decade of discourse analysis of environmental politics: Achievements, challenges, perspectives. Journal of Environmental Policy & Planning, 7, 175–184. doi:10.1080=15239080500339646.
Hammond, J. S., Keeney, R. L., & Raiffa, H. (1999). Smart choices. A practical guide to making better decisions. Boston: Harvard Business School Press.
Hampshire, S. (1972). Morality and pessimism. Cambridge: Cambridge University Press.
Hansson, S. O. (1993). The false promises of risk analysis. Ratio, 6, 16–26. doi:10.1111/j.1467-9329.1993.tb00049.x.
Hansson, S. O. (1996). Decision-making under great uncertainty. Philosophy of the Social Sciences, 26, 369–386.
Hansson, S. O. (2003). Ethical criteria of risk acceptance. Erkenntnis, 59, 291–309.
Hansson, S. O. (2004a). Great uncertainty about small things. Techne, 8, 26–35.
Hansson, S. O. (2004b). Fallacies of risk. Journal of Risk Research, 7, 353–360. doi:10.1080/1366987042000176262.
Hansson, S. O. (2004c). Weighing risks and benefits. Topoi, 23, 145–152.
Hansson, S. O. (2007). Philosophical problems in cost-benefit analysis. Economics and Philosophy, 23, 163–183. doi:http://dx.doi.org/10.1017/S0266267107001356.
Hansson, S. O. (2008). Do we need second-order probabilities? Dialectica, 62, 525–533. doi:10.1111/j.1746-8361.2008.01163.x.
Hansson, S. O. (2009a). From the casino to the jungle. Dealing with uncertainty in technological risk management. Synthese, 168, 423–432. doi:10.1007/s11229-008-9444-1.
Hansson, S. O. (2009b). Measuring uncertainty. Studia Logica, 93, 21–40. doi:10.1007/s11225-009-9207-0.
Hansson, S. O. (2012). The trilemma of moral preparedness. Review Journal of Political Philosophy, 9, 1–5.
Hansson, S. O. (2013). The ethics of risk. Ethical analysis in an uncertain world. Basingstoke: Palgrave Macmillan.
Hansson, S. O. (2016). Evaluating the uncertainties. In S. O. Hansson & G. Hirsch Hadorn (Eds.), The argumentative turn in policy analysis. Reasoning about uncertainty (pp. 79–104). Cham: Springer. doi:10.1007/978-3-319-30549-3_4.
Hansson, S. O., & Oughton, D. (2013). Public participation – potential and pitfalls. In D. Oughton & S. O. Hansson (Eds.), Social and ethical aspects of radiation risk management (pp. 333–346). Amsterdam: Elsevier Science.
Hansson, S, O. (2011). Risk. Stanford Encyclopedia of Philosophy. http://plato.stanford.edu/entries/risk/. Accessed 21 May 2015.
Heinzerling, L. (2000). The rights of statistical people. Harvard Environmental Law Review, 24, 189–207.
Heinzerling, L. (2002). Markets for arsenic. Georgetown Law Journal, 90, 2311–2339.
Hirsch Hadorn, G. (2016). Temporal strategies for decision making. In S. O. Hansson & G. Hirsch Hadorn (Eds.), The argumentative turn in policy analysis. Reasoning about uncertainty (pp. 217–242). Cham: Springer. doi:10.1007/978-3-319-30549-3_9.
Kandlikar, M., Risbey, J., & Dessai, S. (2005). Representing and communicating deep uncertainty in climate-change assessments. Comptes Rendus Geoscience, 337, 443–455. doi:10.1016/j.crte.2004.10.010.
Keynes, J. M. (1921). A treatise on probability. London: Macmillan.
Knight, F. H. ([1921] 1935). Risk, uncertainty and profit. Boston: Houghton Mifflin.
Lempert, R. J. (2002). A new decision sciences for complex systems. PNAS, 99, 7309–7313.
Lempert, R. J., Popper, S. W., & Bankes, S. C. (2003). Shaping the next one hundred years. New methods for quantitative, long-term policy analysis. Santa Monica: Rand.
Lempert, R. J., Nakicenovic, N., Sarewitz, D., & Schlesinger, M. (2004). Characterizing climate-change uncertainties for decision-makers. An editorial essay. Climatic Change, 65, 1–9.
Levi, I. (1986). Hard choices. Decision making under unresolved conflicts. Cambridge: Cambridge University Press.
Locke, J. (1824). The works of John Locke in nine volumes (12th ed., Vol. 7). London: Rivington.
Mastrandrea, M. D., Field, C. B., Stocker, T. F., Edenhofer, O. Ebi, K. L., Frame, D. J., et al. (2010). Guidance Note for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties. Intergovernmental Panel on Climate Change (IPCC). http://www.ipcc.ch. Accessed 20 Aug 2014.
Möller, N. (2016). Value uncertainty. In S. O. Hansson & G. Hirsch Hadorn (Eds.), The argumentative turn in policy analysis. Reasoning about uncertainty (pp. 105–133). Cham: Springer. doi:10.1007/978-3-319-30549-3_5.
Morgan, M. G. (2011). Certainty, uncertainty, and climate change. Climatic Change, 108, 707–721. doi:10.1007/s10584-011-0184-8.
Okasha, S. (2007). Rational choice, risk aversion, and evolution. The Journal of Philosophy, 104, 217–235.
Okasha, S. (2011). Optimal choice in the face of risk: Decision theory meets evolution. Philosophy of Science, 78, 83–104. doi:10.1086/658115
O’Riordan, T., & Cameron, J. (Eds.). (1994). Interpreting the precautionary principle. London: Earthscan.
O’Riordan, T., Cameron, J., & Jordan, A. (Eds.). (2001). Reinterpreting the precautionary principle. London: Cameron May.
Peter, F. (2009). Democratic legitimacy. New York: Routledge.
Rabinowicz, W. (2002). Does practical deliberation crowd out self-prediction? Erkenntnis, 57, 91–122.
Raley, R. K., & Bumpass, L. L. (2003). The topography of the divorce plateau: Levels and trends in union stability in the United States after 1980. Demographic Research, 8, 245–260.
Rittel, H., & Webber, M. (1973). Dilemmas in a general theory of planning. Political Science, 4, 155–169.
Romeijn, J.-W., & Roy, O. (2014). Radical uncertainty: Beyond probabilistic models of belief. Erkenntnis, 79, 1221–1223. doi:10.1007/s10670-014-9687-9.
Ross, A., & Matthews, H. D. (2009). Climate engineering and the risk of rapid climate change. Environmental Research Letters, 4, 045103. doi:10.1088/1748-9326/4/4/045103.
Salmela-Aro, K., Aunola, K., Saisto, T., Halmesmäki, E., & Nurmi, J.-E. (2006). Couples share similar changes in depressive symptoms and marital satisfaction anticipating the birth of a child. Journal of Social and Personal Relationships, 23, 781–803. doi:10.1177/0265407506068263.
Schefczyk, M. (2016). Financial markets: The stabilisation task. In S. O. Hansson & G. Hirsch Hadorn (Eds.), The argumentative turn in policy analysis. Reasoning about uncertainty (pp. 265–290). Cham: Springer. doi:10.1007/978-3-319-30549-3_11.
Sen, A. (1992). Inequality reexamined. Harvard: Harvard University Press.
Shrader-Frechette, K. (2016). Uncertainty analysis, nuclear waste, and million-year predictions. In S. O. Hansson & G. Hirsch Hadorn (Eds.), The argumentative turn in policy analysis. Reasoning about uncertainty (pp. 291–303). Cham: Springer. doi:10.1007/978-3-319-30549-3_12.
Spohn, W. (1977). Where Luce and Krantz do really generalize Savage’s decision model. Erkenntnis, 11, 113–134.
Styron, W. (1979). Sophie’s choice. New York: Random House.
Swart, R., Bernstein, L., Ha-Duong, M., & Petersen, A. (2009). Agreeing to disagree: Uncertainty management in assessing climate change, impacts and responses by the IPCC. Climatic Change, 92, 1–29. doi:10.1007/s10584-008-9444-7.
Taleb, N. N. (2001). Fooled by randomness: The hidden role of chance in life and in the markets. London: Texere.
Taleb, N. N. (2007). The black swan: The impact of the highly improbable. New York: Random House.
Tversky, A., & Kahneman, D. (1986). Rational choice and the framing of decisions. The Journal of Business, 59, S251–S278.
Walker, W. E., Harremoës, P., Rotmans, J., van der Sluijs, J. P., van Asselt, M. B. A., Janssen, P., & Krayer von Krauss, M. P. (2003). Defining uncertainty. A conceptual basis for uncertainty management in model-based decision support. Integrated Assessment, 4, 5–17. doi:10.1076/iaij.4.1.5.16466.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
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
Download citation
DOI: https://doi.org/10.1007/978-3-319-30549-3_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-30547-9
Online ISBN: 978-3-319-30549-3
eBook Packages: Religion and PhilosophyPhilosophy and Religion (R0)