Large-scale Integrated Assessment Models (IAMs) combine economics, energy systems analysis, and climate science to explore global options for mitigating climate change. Despite significant criticism, large-scale IAMs play an authoritative role in the reports of the Intergovernmental Panel on Climate Change and have become a central tool for climate change policy and action. Their influence as tools for determining future policy is hard to understate. If you read that Norwegian oil exploration is in line with the Paris agreement, then you are reading a result from large-scale IAMs.
In this talk we will do two things. First, we will outline what large-scale IAMs are and argue that they deserve greater philosophical attention. Despite their influence, large-scale IAMs have been largely ignored by philosophical discussions around climate change. This may in part be due to confusion about their relation to their - no longer so influential in policy - siblings: cost benefit IAMs (of Nordhaus and Stern review fame). This may also be due to their complexity or their quasi-policy, quasi-scientific status. We contend that exactly these features make large-scale IAMs ripe for philosophical analysis. Their complexity makes them an interesting case of integration of uncertain knowledge on a range of factors into a single framework. Their combined policy/scientific status raises a number of interesting SCIDEM relevant questions. Second, we will sketch an account of what is epistemically valuable about large-scale IAMs. We argue that most reasons philosophers have given to value models do not apply. The representative accuracy of large-scale IAMs is questionable, they do not explain, and they do not constrain the influence of biases and value judgements of analysts. We suggest, instead, that large-scale IAMs should be considered a form of structured expert opinion. We elaborate on this concept and suggest some implications for how large-scale IAMs should be used.