Abstract

The Intergovernmental Panel on Climate Change is a central node for a diverse group of actors interested in the politics of climate change. At the interface of science and policy, it is founded on three principles: being policy relevant, never policy prescriptive; enlisting geographically diverse participants; and being transparent about its procedures. Nonetheless, humanist critics of technology and technology enthusiasts alike critique the Intergovernmental Panel on Climate Change, noting the political implications of its predictive technology. For some, the Intergovernmental Panel on Climate Change’s use of machine learning algorithms and the outputs they produce rely on an underlying technocratic logic. As such, the Intergovernmental Panel on Climate Change’s supposed neutrality masks a universal framework that is harmful to democratic politics because it flattens regional variation and Indigenous knowledge and forecloses non-quantitative approaches to the world (e.g., poetry and narrative). For others, general circulation models are not technologically advanced enough and are thus blunt instruments in need of replacement by novel AI. On this account, the Intergovernmental Panel on Climate Change is marred by human flaws and does not defer to technology enough. This article draws from political theory and interpretive methods to address underlying tensions in the Intergovernmental Panel on Climate Change concerning technology and politics. Specifically, it analyzes leadership, reports, and original interviews conducted with climate scientists. These sources not only illustrate how predictive algorithms and expert rule are prominent in the Intergovernmental Panel on Climate Change but also highlight meaningful attempts to incorporate regional differences and non-quantitative outputs. The climate scientists interviewed frequently acknowledge the tension between technocratic and humanistic approaches. Indeed, these scientists often think in humanistic or poetic ways, even as they display optimism about novel predictive technology. We should avoid rule-by-algorithm shortcuts in matters of governance while remaining open to creative ways of wielding AI to inform sustainable practices.