I think complexity has a lot to offer, and I will try to show that this potential is yet unexplored. I will start by referring to some of the uses complexity has been put to, namely, (i) using complexity to criticize the linear get-the-facts-then-act model of science for policy; (ii) using complexity to explain, name and label the policy process; (iii) using complexity to give advice on how to use evidence and make decisions. These roles can, and have been combined, and as usual, by speaking of three distinct roles, I am simplifying and creating pure categories that do not reflect complex practice. But the point I want to make is that complexity needs to be taken further: complexity can help us re-think the science-policy interface, or as I will put it, the interface between multiple forms of knowledge and policy. Let’s continue the tour.

Blog post III: Complexity as means to invoke humility and reflexivity in science advice to policy

So far, we have seen how complexity theory has been used to criticise the use of reductionist science in policy making and the linear understanding of the policy process. But does complexity also offer a theory? A number of authors have argued that complexity offers a new epistemology of science, that is, a new way of understanding knowledge. Complexity challenges the idea of scientific knowledge as an orchestra, in which each discipline plays a different tune contributing to a harmonic whole (Neurath, 1946). Complexity rather suggests that the different representations produced by different disciplines are non-equivalent to each other, they cannot be combined into a coherent whole, and that knowledge can be fragmented and contradictory.  A central feature of the new epistemology is irreducible pluralism.

I give two examples of how the epistemology of complexity has been interpreted:

Sandra Mitchell (2009) argues that complexity can be used to construct to an epistemology of integrative pluralism. She explains that complexity decouples determinism from predictability. At the level of the parts, interactions may be described in deterministic terms through local rules of interaction (for example, the simple rules used to describe the behaviour of an ant, a starling, a bee). Local rules, however, cannot be used to predict the behaviour of the whole (the ant colony, the flock of starlings, the bee hive). Mitchell warns against descriptive fundamentalism, that is, the belief that a privileged, complete description of the world can be derived by reducing observation to materialism. The existence of observable units across all scales of analysis, e.g. the fact that everything is made of atoms, does not means that atoms is all there is to be known.

Edgar Morin (1992) argues that the reductionist paradigm that seeks explanation at the level of components, must not be replaced by holism, which seeks explanation at the level of “the system”. Instead, he proposes an epistemology of organisation and interaction. Complexity is not the study of parts and wholes, but of the mutually constitutive interactions between parts and wholes. Interactions are constitutive, because as they are reproduced and stabilised, they create self-organisation. Moreover, organisation “produces both entropy (that is, the degradation of the system and of itself) and negentropy (the regeneration of the system and of itself).” Morin thus speaks of an epistemology which contains uncertainties and antagonisms.

One of the main contributions of complexity is its demand for multiple levels of analysis (Ahl & Allen, 1996; Allen & Starr, 1982). Ideas of irreducible pluralism and antagonism imply that there is no privileged level of analysis. Using the example of the starlings, local rules that explain how individual starlings react to each other’s flight trajectory are not “truer” than the unpredictability of the flock’s flight pattern. The different levels of analysis do not map one onto another, and so there is a certain ambiguity and inconsistency.

The corollary of this epistemology for the science-policy interface is that one cannot give authoritative advice on which type of scientific knowledge should be given privilege and should be used in policy advice. Moreover, science may give contradictory advice to policy – even when there is no sloppy science, and even when there are no conflicts of interest, because of irreducible pluralism. Building on the work of Robert Rosen (1985, 1991), I refer to non-equivalent representations to signify that pluralism is not a matter of different opinions. Non-equivalent representations mean that a globe and a Mercator map will yield different measurements of distance between two points. Yet, both maps are useful. A globe-type representation is useful to calculate time zones, and a Mercator map is useful for navigation.  Except that one is inconsistent with the other.

With regard to the science-policy interface, scholars have therefore used complexity theory to argue for modesty, humility and reflexivity (Geyer & Cairney, 2015; Mitchell, 2009; Strand & Cañellas-Boltà, 2006), here I include my own work (Kovacic & Giampietro, 2015). Science advice to policy should be humble, should take into account uncertainties, inconsistencies, controversies, ambiguities. This does not mean that science cannot advice to policy, but that uncertainty and pluralism should be communicated along with so-called facts. Due to uncertainty, facts become soft (Funtowicz & Ravetz, 1993). Reflexivity invites scientists to acknowledge the limits and contradictions of knowledge. Speaking of limits and contradictions does not mean questioning the validity of scientific knowledge. I am not suggesting that policy might as well be based on reading in entrails, or coffee cups. I argue that science only gives partial information, and that when taken out of the laboratory and into policy advice, more types of knowledge are needed. I will elaborate on this point in my next post.

Before we proceed, I would like to spend just a few more words on reflexivity. Drawing from gender studies, there are two different versions of reflexivity. The first, is that associated with the work of Sandra Harding on standpoint epistemology. Harding argues that the sciences have been blind to their own sexist and androcentric research practices and results (1993). An example of such blindness are medical studies that test new drugs on males (assumed to be representative of human beings), and fail to realise that female bodies react differently to drugs. Reflexivity in this context means recognising that one’s view of the world depends on where one stands – therefore, men will have a different worldview than women, and science produced by men will be different from science produced by women. Harding deconstructs the idea of the scientist as a neutral observer. This valuable contribution, however, cannot produce a better use of scientific knowledge for governance. As Jasanoff puts it, “how … can a sceptical and reflexive stance in relation to scientific knowledge be reconciled with making authoritative recommendations for social policy?” (1996: 393). Standpoint epistemology politicises science. I think politicising science is a valuable exercise, but it does not add to the understanding of the science-policy interface.

The second version of reflexivity is that associated with the work of Donna Haraway on posthumanism. Haraway criticises Harding’s conception of women as a unified category, and uses the figure of the cyborg to explore new possibilities of constructing one’s identity. A cyborg is “a hybrid of machine and organism” (Haraway, 2013), and it is used to question not only gender assumptions, but also assumptions about what it means to be human. Reflexivity à la Haraway is a broader exercise, which goes beyond one’s perspective and takes into account how one produces knowledge. I think that complexity invites a similar exercise. The point of complexity-inspired reflexivity is not just to acknowledge the limits of a particular discipline or method, but to be reflexive about which policy processes and institutions are reinforced and which are hidden in the interaction with science advisors, which uses of evidence science participates in, and about what complexity challenges, and fails to challenge, in the interactions between science and policy.

References

Ahl, V., & Allen, T. F. H. (1996). Hierarchy theory: A vision, vocabulary, and epistemology. New York: Columbia University Press.

Allen, T. F. H., & Starr, T. B. (1982). Hierarchy perspectives for ecological complexity. Chicago: University of Chicago Press.

Funtowicz, S. O., & Ravetz, J. R. (1993). Science for the post-normal age. Futures, (September), 739–755. https://doi.org/0016-3287/93/07739-17

Geyer, R., & Cairney, P. (2015). Handbook on complexity and public policy. Cheltenham: Edward Elgar.

Haraway, D. (2013). A cyborg manifesto: Science, technology, and socialist feminism in the late twentieth century. In Simians, cyborgs, and women: The reinvention of nature. London and New York: Routledge.

Harding, S. (1993). Rethinking standpoint epistemology: What is “Strong Objectivity”? In L. Alcoff & E. Potter (Eds.), Feminist epistemologies. London and New York: Routledge.

Jasanoff, S. (1996). Beyond epistemology: Relativism and engagement in the politics of science. Social Studies of Science, 26, 393–418.

Kovacic, Z., & Giampietro, M. (2015). Beyond “beyond GDP indicators”: the need for reflexivity in science for governance. Ecological Complexity, 21, 53–61. https://doi.org/10.1016/j.ecocom.2014.11.007

Mitchell, S. D. (2009). Unsimple truths: Science, complexity and policy. Chicago: University of Chicago Press.

Morin, E. (1992). From the Concept of System to the Paradigm of Complexity Introduction: Mastering the Concept of System. Jownal of Social and Evolutionary Systems, 15(4), 371–385.

Neurath, O. (1946). The Orchestration of the Sciences by the Encyclopedism of Logical Empiricism. Philosophy and Phenomenological Research, 6(4), 496–508.

Rosen, R. (1985). Anticipatory systems. Oxford: Pergamon Press.

Rosen, R. (1991). Life itself: A comprehensive inquiry into the nature, origin, and fabrication of life. New York: Columbia University Press.

Strand, R., & Cañellas-Boltà, S. (2006). Reflexivity and modesty in the application of complexity theory. In A. Guimaraes Pereira, A. Guedez Vaz, & S. Tognetti (Eds.), Interfaces between science and society. Sheffield: Greenleaf Publishing.


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