Ahmad Elabbar

The weaponizing of scientific expertise to oppose regulation has been extensively studied. However, the relevant studies, belonging to the emerging discipline of agnotology, remain focused on the analysis of empirical corruption: of misinformation, doubt mongering, and other practices that cynically deploy expertise to render audiences ignorant of empirical facts. This paper explores the wrongful deployment of expertise beyond empirical corruption. To do so, I develop a broader framework of morally subversive expertise, building on recent work in political philosophy (Howard, 2016). Expertise is subversive if it sets up its audience to fail morally, either intentionally or negligently. I distinguish three modes of subversive expertise: empirical subversion (the focus of agnotology), normative subversion and motivational subversion. Drawing on these distinctions, I offer a revisionary account of the Trump Administration’s regulatory science as a case study. I show that the Trump Administration’s use of expertise to dismantle climate regulation, contra the standard charge, cannot be explained using the resources of agnotology alone: the Administration produced highly reliable climate assessments, detailing the risks of climate change, candidly admitting the harms of its proposed policies, and still successfully deployed these findings to justify massive climate deregulation. The lesson of the analysis is that dismissing the expertise that underpins climate deregulation as empirically corrupt ‘anti-science’ both obscures its actual role in the politics of climate change and understates its wrongfulness: it misses the breadth of the assault on moral agency that sustains climate injustice.

The setting of evidential standards is a core practice of scientific assessment for policy. Persuaded by considerations of inductive risk, philosophers generally agree that the justification of evidential standards must appeal to non-epistemic values but debate whether the balance of non-epistemic reasons favours varying evidential standards versus maintaining fixed high evidential standards in assessment, as both sets of standards promote different and important political virtues of advisory institutions. In this paper, I adjudicate the evidential standards debate by developing a novel argument from justice, drawing on the IPCC’s assessment of climate impacts as a case study. I argue that in assessments marked by background evidential inequality, maintaining fixed high evidential standards results in an unequal distribution of ‘epistemic power’ among stakeholders, producing a ‘powerful assessment’ for the data-rich (a high rate of findings) and a ‘weak assessment’ for the data-poor (a low rate of findings). Where such inequalities of epistemic power disadvantage those in data-poor regions with respect to fundamental interests, such as basic human rights, we have decisive reasons of justice to vary evidential standards.