Scientific epistemology is a serious business in economics—as it is in any science. Not surprisingly, therefore, discussions about value-ladeness tend to focus on theoretical and methodological issues within the discipline, while the question of the social consequences of science is approached with more reservation. And for many good reasons, one may say, because it is not entirely up to scientists how will the scientific product be disseminated and interpreted in society, or how will it be used by policy makers. Or, that’s not the job of the scientist, one could reason, to determine and be ready for all possible applicative scenarios.
Since the last few decades, research practices have undergone a far-reaching transformation at the interface between science, policy and society. It involves an increased engagement of science in problem solving and policy advice, and the enhancing role of participatory research methods in problem-based approaches. The social consequences of science become therefore more readily visible, opening up new perspectives on debates about facts and values dichotomy, or the relationship between knowledge, truth, and values (cf. Kitcher, 2001). One way of looking at the transformation of scientific practices focuses on the criteria of scientific rationality with regard to scientific knowledge and the very process of knowledge production, echoing a Weberian contrast between instrumental and axiological rationality of social action (Weber 1968). Specifically, the scientific rationality criteria have been extended in the process from purely (i) internal rationality, that can be defined as a conventional scientific rationality approach focused on disciplinary epistemology and methodology, to (ii) external rationality that pertains to axiological, ethical, and societal elements of knowledge and its production (Kiepas, 2006).
There are many reasons for including external rationality in scientific practices. For one thing, all applied sciences can be considered as value-laden in virtue of their goal-oriented values (Pullin, 2002). Furthermore, many contemporary problems, as subjects of research, are radically complex. They are laden with systemic uncertainties, meaning that “the problem is concerned not only with the discovery of a particular fact (as in traditional research), but with the comprehension or management of a reality that has irreducible complexities or uncertainties” (see more in Funtowicz & Ravetz, 1994, p. 1882). They also pose future incalculable risks in an unprecedented scope. For example, in the context of complex, adaptive problems such as climate change, uncertainty in science follows (Brown, 2013). Scientific uncertainty regarding the severity and scope of the problem fuels general disagreement about the appropriate actions to undertake. Attempts to accurately assess all the possible climate change impacts and to exhaustingly assign an economic value to alternative courses of action are bound to fail (Jamieson, 2010). That being the case, the policy-relevance of standard economic analysis as the sole knowledge-base for environmental decision making is limited.
In case of economics, the shift in approaches to rationality can be seen in debates about reflexivity in economics, bounded rationality, or performativity of economic models, to name a few topics. But for the most part, ethical- and value-neutrality continue to feature much of economic research, such as in standard normative theories of decision making under uncertainty and risk. The burgeoning of economics as a separate discipline, accompanied by distancing from philosophy, build up strong methodological foundations to prevent any extra-scientific elements to interfere in its analysis (cf. Hausman, 1992).
The classic conceptualisation of uncertainty and risk in economics is very specific and differs from the above-mentioned, sociologically incrusted understanding. Following the paradigmatic distinction formulated by Knight (1921), uncertainty refers to situations of radical uncertainty that cannot be expressed as sets of probabilities, whereas risk is related to situations in which actions do not lead with certitude to specific outcomes, but the alternative outcomes and their probabilities can be discerned.
The categories of uncertainty and risk, as considered here, lend themselves to complexity of many policy issues, and are associated with the transformation of postmodern societies due to technology, consequences of globalisation, and environmental crises that follow (Beck, 1992; Giddens, 1990). These circumstances, “external” to standard methodological practices, motivate the extension of scientific rationality criteria and rethinking the role of science by researchers themselves. An example of this transformative process is the so-called advocacy science for environmental justice. It represents a socially engaged, multidisciplinary research approach that emerged in response to environmental toxicity movements, and developed an alternative epidemiological paradigm based on participatory research methods (see, e.g., Ottinger & Cohen, 2011).
With regard to the interface between science, policy, and society and the extra-scientific aspects of uncertainty and risk, one can note that the assessment and acceptance of risk are not purely a matter of data analysis or applying the “right” indicators. The perception and interpretation of uncertainty and risk are influenced by a mixture of social, political, and scientific processes that interact with each other. Consider the relationship between environmental pollution and risk. While pollution appears to be solely as a matter of scientific measures, the question of what is an acceptable level of pollution and its risk for a given society, and whether there are cases of unacceptable risks, involves our pre-conceptions and assumptions about what constitutes a good quality of life, wellbeing, and sustainable development (cf. Evernden, 1999).
Why would an individual economist care about the science-policy interface, or about considering extra-scientific elements of her research practice? There are several reasons to seriously reflect on this question. For one thing, transparency about the value content of specific research programs may translate into more careful and accountable approach to complex problems of public policy and the remedying capacity of science and technological progress. Furthermore, Söderbaum (2000) argues that economics should be more properly approached as political economics to make clear the fact that each scientist, as the discipline itself, has an ideological orientation (in the sense of means-ends philosophy) that plays out in the problem-framing, and reflects on the performative features of economic expertise. To the latter point, the analyst’s conclusion that reduces the extra-monetary aspects of a given problem to monetary ones is not without policy consequences; it suggests certain framings and solution-imageries to economic agents and decision makers. Besides, academia itself is not free of subjective interests and rent seeking. But—I haste to add—this does not undermine the value of scientific expertise per se. Neither does it suggest that citizens and policy makers are passive or unreflective recipients of scientific knowledge. It rather suggests a double-edge approach to science that recognises the subjective, cultural, and societal components in scientific practices on the one hand, and the aspiration of scientific community to reach objectivity (understood broadly as a normative objective) on the other hand. Although scientific practices are saturated with theoretical pre-conceptions and cultural perspectives, it does not immediately follow that science has nothing to do with truth and objectivity (a subject that deserves a separate discussion).
The double-edge approach to science calls for more explicit discussions about the social consequences of science and scientific literacy in society:
- Concerns about the role of science and scientific expertise in society may facilitate disciplinary reflexivity. It may also feed into methodological approaches. In case of economics, instead of focusing only on expanding the standard framework of economic analysis onto new subjects, concerns about the social consequences of science create a platform for a more direct consideration of methodological alternatives. Especially for contexts in which standard economic tools of analysis display some limits (e.g., cost-benefit analysis in sustainable development planning), alternative approaches that directly accommodate non-monetary impacts and justice concerns are needed (Brown et al., 2017).
- According to a political scientist Frank Fischer, in face of technical and social complexity that characterises most of policy issues, citizens and politicians need to display a good level of competence (2009, 1). In this context, an urgent question arises: how to democratise science on the one hand, and how to prevent populism and the spread of fake facts to take the provenience of science (as a source of information about the world) on the other hand? While the aspiration of science to be the absolute truth holder has been widely challenged, it does not immediately follow that there is nothing to scientific knowledge that would make it somehow different from other forms of knowledge. No differentiation at all can give way to anti-science of dangerous kind, in which “facts” are matters of preferences or interests. A caveat here is in order: such differentiation does not imply that scientific knowledge is inherently better than any other form of knowledge.
Certainly there are many challenges to balancing the double-edge approach to science both within and outside of the scientific community, as there are multiple philosophical framings of the role and status of scientific expertise in society. To be continued!
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