Expertise Revisited: Reflecting on the Intersection of Science and Democracy in the Case of Fracking

This dissertation aims to explain the conditions under which expertise can undermine democratic decision making. I argue that the root of the conflict between expertise and democracy lies in what I call insufficiently “representative” expertise – that is forms of scientific research that are not relevant to the policy questions at hand and that fail to make visible their hidden values dimensions. I claim that the scholarly literature on the problem of expertise fails to recognize and address the issue correctly, because it does not open the black box of scientific methodologies. I maintain that only by making sense of the methodological choices of experts in the context of policy making can we determine the relevance of research and reveal the hidden socio-political values and consequences. Using the case of natural gas fracking, I demonstrate how expert contributions – even though epistemically sound – can muddle democratic policy processes. I present four case studies from controversies about fracking to show how to contextualize scientific methodologies in the pertinent political process. I argue that the common problem across all case studies is the failure of expertise to sufficiently represent stakeholders’ problems and concerns. In this context, “representation” has three criteria: (1) the operational research questions on which the qualified experts work are relevant to stakeholders’ problems and concerns; (2) the non-epistemic values and consequences of epistemic choices of experts are compatible with social and political values and priorities; and (3) hidden values attached to facts are fully transparent and openly debated. In the conclusion, I propose a normative version of this representation theory that can be used to evaluate the appropriateness of expertise for democratic policy making. Instead of the value-free science ideal, I propose a new ideal to legitimately allow non-epistemic values in scientific reasoning without compromising the soundness of research