Both individuals and governments around the world have willingly sacrificed a great deal to meet the collective action problem posed by Covid-19. This has provided some commentators with newfound hope about the possibility that we will be able to solve what is arguably the greatest collective action problem of all time: global climate change. In this paper we argue that this is overly optimistic. We defend two main claims. First, these two collective action problems are so different that the actions (...) that individuals have taken to try to solve the problem posed by Covid-19 unfortunately provide little indication that we will be able to solve the problem posed by climate change. Second, the actions that states have taken in response to Covid-19 might—if anything—even be evidence that they will continue to fail to cooperate towards a solution to the climate crisis. (shrink)

Integrated assessment models play a major role in the science and policy of climate change. Similarly to other widely used computational tools for addressing socially relevant problems, IAMs need to account for the key uncertainties characterizing processes and socio-economic responses. In the case of climate change, these are particularly complex given the very long-term nature of climate and the deep uncertainty characterizing technological and human systems. Here we draw from philosophical discussion of mathematical modeling of social problems and review the (...) role of uncertainty in climate-economic modeling. In agreement with the literature, we highlight the crucial role of epistemic uncertainty in IAMs. We posit that the normative components of models, more than the physical and socio-techno-economic ones, are the most fraught by uncertainty and yet the least understood. We suggest a research agenda to explore uncertainties of evaluation frameworks, transcending the current implicit normativity of IAMs. (shrink)

Catastrophic risk raises questions that are not only of practical importance, but also of great philosophical interest, such as how to define catastrophe and what distinguishes catastrophic outcomes from non-catastrophic ones. Catastrophic risk also raises questions about how to rationally respond to such risks. How to rationally respond arguably partly depends on the severity of the uncertainty, for instance, whether quantitative probabilistic information is available, or whether only comparative likelihood information is available, or neither type of information. Finally, catastrophic risk (...) raises important ethical questions about what to do when catastrophe avoidance conflicts with equity promotion. (shrink)

This book analyzes major ethical issues surrounding the use of climate engineering, particularly solar radiation management techniques, which have the potential to reduce some risks of anthropogenic climate change but also carry their own risks of harm and injustice. The book argues that we should approach the ethics of climate engineering via "non-ideal theory," which investigates what justice requires given the fact that many parties have failed to comply with their duty to mitigate greenhouse gas emissions. Specifically, it argues that (...) climate justice should be approached comparatively, evaluating the relative justice or injustice of feasible policies under conditions that are likely to hold within relevant timeframes. Likely near-future conditions include "pessimistic scenarios," in which no available option avoids serious ethical problems. The book contends that certain uses of SRM can be ethically defensible in some pessimistic scenarios. This is the first book devoted to the many ethical issues surrounding climate engineering. (shrink)

Abstract:The standard, Bayesian account of rational belief and decision is often argued to be unable to cope properly with severe uncertainty, of the sort ubiquitous in some areas of policy making. This paper tackles the question of what should replace it as a guide for rational decision making. It defends a recent proposal, which reserves a role for the decision maker’s confidence in beliefs. Beyond being able to cope with severe uncertainty, the account has strong normative credentials on the main (...) fronts typically evoked as relevant for rational belief and decision. It fares particularly well, we argue, in comparison to other prominent non-Bayesian models in the literature. (shrink)

Innovative research on decision making under ‘deep uncertainty’ is underway in applied fields such as engineering and operational research, largely outside the view of normative theorists grounded in decision theory. Applied methods and tools for decision support under deep uncertainty go beyond standard decision theory in the attention that they give to the structuring of decisions. Decision structuring is an important part of a broader philosophy of managing uncertainty in decision making, and normative decision theorists can both learn from, and (...) contribute to, the growing deep uncertainty decision support literature. (shrink)

If scientists violate principles and practices of routine science to quickly develop interventions against catastrophic threats, they are engaged in what I call fast science. The magnitude, imminence, and plausibility of a threat justify engaging in and acting on fast science. Yet, that justification is incomplete. I defend two principles to assess fast science, which say: fast science should satisfy as much as possible the reliability-enhancing features of routine science, and the fast science developing an intervention against a threat should (...) not depend on the same problematic assumptions as the fast science which estimates the magnitude, imminence, and plausibility of the threat. (shrink)

A sketch of my ethical views, or secular moral philosophy. Emphasis is on stating how it all hangs together.