Gregor Betz

The case for climate engineering research: an analysis of the “arm the future” argument

With the evidence for anthropogenic climate change piling up, suggesting that climate impacts of GHG emissions might have been underestimated in the past (Allison et al. 2009; WBGU 2009), and mitigation policies apparently lagging behind what many scientists consider as necessary reductions in order to prevent dangerous climate change, the debate about intentional climate change, or “climate engineering”, as we shall say in the following, has gained momentum in the past years. While efforts to technically modify earth’s climate had been the focus of sporadic discussions at least since the White House’s Report “Restoring the Quality of Our Environment” (cf. Keith 2000), Paul Crutzen’s cautious plea for research into the feasibility and side-effects of stratospheric sulphur injections (Crutzen 2006) has incited an inter-disciplinary controversy (with a preliminary culmination in the Royal Society’s assessment (Royal Society 2009)), while increasing public awareness and debate about climate engineering, as well. The controversy, though, does not focus on the question whether climate engineering should be carried out today (which is largely reckoned to be a bad idea, unnecessary, or premature) or at some point in the future (which is considered a decision we don’t have to take now), but on whether to engage in large-scale research into the alternative technological options for carrying out intentional climate change. It is this paper’s purpose to make that controversy more transparent. In order to do so, we analyse what seems to be the major argument in favour of research into climate engineering: the lesser evil-, or, as Stephen Gardiner has called it, the arm the futureargument—in short: the AF-argument (Gardiner 2010). Such an argumentative analysis makes explicit the normative and descriptive assumptions which underlie the reasoning, Climatic Change DOI 10.1007/s10584-011-0207-5

What’s the Worst Case? The Methodology of Possibilistic Prediction

Abstract Frank Knight (1921) famously distinguished the epistemic modes of certainty, risk, and uncertainty in order to characterize situations where deterministic, probabilistic or possibilistic foreknowledge is available. Because our probabilistic knowledge is limited, i.e. because many systems, e.g. the global climate, cannot be described and predicted probabilistically in a reliable way, Knight’s third category, possibilistic foreknowledge, is not simply swept by the probabilistic mode. This raises the question how to justify possibilistic predictions-including the identification of the worst case. The development of such a modal methodology is particularly vital with respect to predictions of climate change. I show that a methodological dilemma emerges when possibilistic predictions are framed in traditional terms and argue that a more nuanced conceptual framework, distinguishing different types of possibility, should be used in order to convey our uncertain knowledge about the future. The new conceptual scheme, however, questions the applicability of standard rules of rational decision-making, thus generating new challenges.

Ethical Aspects of Climate Engineering

This study investigates the ethical aspects of deploying and researching into so-called climate engineering methods, i.e. large-scale technical interventions in the climate system with the objective of offsetting anthropogenic climate change. The moral reasons in favour of and against R&D into and deployment of CE methods are analysed by means of argument maps. These argument maps provide an overview of the CE controversy and help to structure the complex debate.

Debate Dynamics: How Controversy Improves Our Beliefs

Is critical argumentation an effective way to overcome disagreement? And does the exchange of arguments bring opponents in a controversy closer to the truth? This study provides a new perspective on these pivotal questions. By means of multi-agent simulations, it investigates the truth and consensus-conduciveness of controversial debates. The book brings together research in formal epistemology and argumentation theory.Aside fromits consequences for discursive practice, the work may have important implications for philosophy of science and the way we construe scientific rationality as well.

Analysing Practical Argumentation

Argument analysis is a powerful tool for structuring policy deliberation and decision-making, especially when complexity and uncertainty loom large. Argument analysis seeks to determine which claims are justified or criticized by a given argumentation, how strong an argument is, on which implicit assumptions it rests, how it relates to other arguments in a controversy, and which standpoints one can reasonably adopt in view of a given state of debate. This chapter first gives an overview of the activities involved in argument analysis and discusses the various aims that guide argument analysis. It then introduces methods for reconstructing and evaluating individual arguments as well as complex argumentation and debates. In their application to decisions under great uncertainty, these methods help to identify coherent positions, to discern important points of (dis)agreement, as well as to avoid spurious consensus and oversimplification.

Accounting for Possibilities in Decision Making

Intended as a practical guide for decision analysts, this chapter provides an introduction to reasoning under great uncertainty. It seeks to incorporate standard methods of risk analysis in a broader argumentative framework by re-interpreting them as specific (consequentialist) arguments that may inform a policy debate—side by side along further (possibly non-consequentialist) arguments which standard economic analysis does not account for. The first part of the chapter reviews arguments that can be advanced in a policy debate despite deep uncertainty about policy outcomes, i.e. arguments which assume that uncertainties surrounding policy outcomes cannot be (probabilistically) quantified. The second part of the chapter discusses the epistemic challenge of reasoning under great uncertainty, which consists in identifying all possible outcomes of the alternative policy options. It is argued that our possibilistic foreknowledge should be cast in nuanced terms and that future surprises—triggered by major flaws in one’s possibilistic outlook—should be anticipated in policy deliberation.

Justifying inference to the best explanation as a practical meta-syllogism on dialectical structures

This article discusses how inference to the best explanation (IBE) can be justified as a practical meta-argument. It is, firstly, justified as a practical argument insofar as accepting the best explanation as true can be shown to further a specific aim. And because this aim is a discursive one which proponents can rationally pursue in—and relative to—a complex controversy, namely maximising the robustness of one’s position, IBE can be conceived, secondly, as a meta-argument. My analysis thus bears a certain analogy to Sellars’ well-known justification of inductive reasoning (Sellars, In: Essays in honour of Carl G. Hempel, 1969); it is based on recently developed theories of complex argumentation (Betz, In: Theorie dialektischer Strukturen, 2010a).

Petitio principii and circular argumentation as seen from a theory of dialectical structures

This paper investigates in how far a theory of dialectical structures sheds new light on the old problem of giving a satisfying account of the fallacy of petitio principii, or begging the question. It defends that (i) circular argumentation on the one hand and petitio principii on the other hand are two distinct features of complex argumentation, and that (ii) it is impossible to make general statements about the defectiveness of an argumentation that exhibits these features. Such an argumentation, in contrast, has to be evaluated on a case-by-case basis. “Petitio principii”, this paper thence suggests, is one name for, in fact, a multitude of different and quite complex dialectical situations which require specific analysis and evaluation.

Evaluating Dialectical Structures

This paper develops concepts and procedures for the evaluation of complex debates. They provide means for answering such questions as whether a thesis has to be considered as proven or disproven in a debate or who carries a burden of proof. While being based on classical logic, this framework represents an (argument-based) approach to non-monotonic, or defeasible reasoning. Debates are analysed as dialectical structures, i.e. argumentation systems with an attack- as well as a support-relationship. The recursive status assignment over the arguments is conditionalised on proponents in a debate. The problem of multiple status assignments arising on circular structures is solved by showing that uniqueness can be guaranteed qua reconstruction of a debate. The notion of burden of proof as well as other discursive aims rational proponents pursue in a debate is defined within the framework.

Evaluating dialectical structures with Bayesian methods

This paper shows how complex argumentation, analyzed as dialectical structures, can be evaluated within a Bayesian framework by interpreting them as coherence constraints on subjective degrees of belief. A dialectical structure is a set of arguments (premiss-conclusion structure) among which support- and attack-relations hold. This approach addresses the observation that some theses in a debate can be better justified than others and thus fixes a shortcoming of a theory of defeasible reasoning which applies the bivalence principle to argument evaluations by assigning them the status of being either defeated or undefeated. Evaluation procedures which are based on the principle of bivalence can, however, be embedded as a special case within the Bayesian framework. The approach developed in this paper rests on the assumptions that arguments can be reconstructed as deductively valid and that complex argumentation can be reconstructed such that premisses of arguments with equivalent conclusions are pairwise independent.