Gregor Betz

Reflective equilibrium (RE) is often regarded as a powerful method in ethics, logic, and even philosophy in general. Despite this popularity, characterizations of the method have been fairly vague and unspecific so far. It thus may be doubted whether RE is more than a jumble of appealing but ultimately sketchy ideas that cannot be spelled out consistently. In this paper, we dispel such doubts by devising a formal model of RE. The model contains as components the agent’s commitments and a theory that tries to systematize the commitments. It yields a precise picture of how the commitments and the theory are adjusted to each other. The model differentiates between equilibrium as a target state and the dynamic equilibration process. First solutions to the model, obtained by computer simulation, show that the method allows for consistent specification and that the model’s implications are plausible in view of expectations on RE. In particular, the mutual adjustment of commitments and theory can improve one’s commitments, as proponents of RE have suggested. We argue that our model is fruitful not only because it points to issues that need to be dealt with for a better understanding of RE, but also because it provides the means to address these issues.

There are different varieties of conservatism concerning belief formation and revision. We assesses the veritistic effects of a particular kind of conservatism commonly attributed to Quine: the so-called maxim of minimum mutiliation, which states that agents should give up as few beliefs as possible when facing recalcitrant evidence. Based on a formal bounded rationality model of belief revision, which parametrizes degree of conservatism, and corresponding multi-agent simulations, we eventually argue against doxastic conservatism from the vantage point of veritistic social epistemology.

If we want to understand how extremist group ideologies are established, we have to comprehend the social processes which form the basis of the emergence and distribution of such beliefs. In our chapter, we present an innovative approach to examining these processes and explaining how they function: with the method of computer-based simulation of opinion formation, we develop heuristic explanatory models which help to generate new and interesting hypotheses. The focus is thereby not on individuals and their idiosyncrasies but on the dynamic mutual adaptation of beliefs in a group. These dynamics can produce an incremental establishment of “charismatic” opinion leaders and an increasing radicalization and alienation. A prototype of such a simulation model has produced promising first results which are presented and discussed.

Philosophy of science attempts to reconstruct science as a rational cognitive enterprise. In doing so, it depicts a normative ideal of knowledge acquisition and does not primarily seek to describe actual scientific practice in an empirically adequate way. A comprehensive picture of what good science consists in may serve as a standard against which we evaluate and criticize actual scientific practices. Such a normative picture may also explain why it is reasonable for us to trust scientists – to the extent that they live up to the ideal – and to rely on their findings in decision making. Likewise, a sound normative understanding of science exposes the limits of scientific understanding and prevents us from placing blind faith in scientists and experts. For these reasons, philosophy of science represents a useful resource and background theory for the practice and study of science communication. In this handbook article, we provide an opinionated introduction to philosophy of science by flashing a light on 22 central issues which (we think) are of special interest to scholars and practitioners of science communication – and, in particular, to scholars and practitioners of external science communication.

This article discusses how inference to the best explanation 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 ; it is based on recently developed theories of complex argumentation.

Descartes' "Meditationen" sind vielleicht 'der' Klassiker der Philosophie. Sie behandeln grundlegende Fragen: Welche Arten von Gegenständen kommen in der Welt vor? Was für eine Art von Ding bin ich? Bin ich frei? Was ist Wahrheit? Welchen Status haben logische Wahrheiten oder mathematische Theoreme? Was kann ich wissen? Gregor Betz' systematischer Kommentar rekonstruiert die entsprechenden Gedankengänge und Begründungen und versucht Antworten auf Descartes' Fragen zu geben. Auch andere Philosophen, insbesondere des 20. Jahrhunderts, werden in einen Dialog mit Descartes gestellt. Denn eine philosophische Position zu verstehen bedeutet letztlich auch zu überblicken, "welche weiteren Thesen sie impliziert und mit welchen anderen Positionen sie in Konflikt gerät", so der Autor des Bandes.

The ideal of value free science states that the justification of scientific findings should not be based on non-epistemic (e.g. moral or political) values. It has been criticized on the grounds that scientists have to employ moral judgements in managing inductive risks. The paper seeks to defuse this methodological critique. Allegedly value-laden decisions can be systematically avoided, it argues, by making uncertainties explicit and articulating findings carefully. Such careful uncertainty articulation, understood as a methodological strategy, is exemplified by the current practice of the Intergovernmental Panel on Climate Change (IPCC)

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 predictionsincluding the identication 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 dierent 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.

This paper gives an explication of our intuitive notion of strength of justification in a controversial debate. It defines a thesis' degree of justification within the bipolar argumentation framework of the theory of dialectical structures as the ratio of coherently adoptable positions according to which that thesis is true over all coherently adoptable positions. Broadening this definition, the notion of conditional degree of justification, i.e.\ degree of partial entailment, is introduced. Thus defined degrees of justification correspond to our pre-theoretic intuitions in the sense that supporting and defending a thesis t increases, whereas attacking it decreases, t's degree of justification. Moreover, it is shown that (conditional) degrees of justification are (conditional) probabilities. Eventually, the paper explains that it is rational to believe theses with a high degree of justification insofar as this strengthens the robustness of one's position.

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.

In diesem Beitrag möchte ich begründen, warum das 2-Grad-Ziel der internatio- nalen Klimapolitik einen vernünftigen Umgang mit unscharfen Grenzen darstellt. Ich werde zunächst skizzieren, aus welchen Überlegungen das 2-Grad-Ziel ent- standen ist und wie es Eingang fand in die internationale Klimapolitik. Daraufhin werde ich darlegen, dass sich traditionelle Entscheidungsanalyseverfahren (Kos- tennutzenanalyse, kurz: KNA) nicht problemlos auf klimapolitische Fragestel- lungen anwenden lassen. Solche Schwierigkeiten umgeht hingegen der Leitplan- kenansatz, der als Alternative zur KNA entwickelt wurde. Im Leitplankenansatz, so werde ich argumentieren, lässt sich das 2-Grad-Ziel als Klimaleitplanke ein- sichtig begründen. Schließlich werde ich auf ungerechtfertigte Kritik am 2-Grad- Ziel aufmerksam machen.

Based on the theory of dialectical structures, I review the concept of degree of justification of a partial position a proponent may hold in a controversial debate. The formal concept of degree of justification dovetails with our pre-theoretic intuitions about a thesis' strength of justification. The central claim I'm going to defend in this paper maintains that degrees of justification, as defined within the theory of dialectical structures, correlate with a proponent position's verisimilitude. I vindicate this thesis with the results of simulations of controversial argumentation.

Science advances by means of argument and debate. Based on a formal model of complex argumentation, this article assesses the interplay between evidential and inferential drivers in scientific controversy, and explains, in particular, why both evidence accumulation and argumentation are veritistically valuable. By improving the conditions for applying veritistic indicators , novel evidence and arguments allow us to distinguish true from false hypotheses more reliably. Because such veritistic indicators also underpin inductive reasoning, evidence accumulation and argumentation enhance the reliability of inductive inference, for example, inference to the best explanation. 1 Introduction2 Theory of Dialectical Structures3 Debate Simulations4 From Evidence and Arguments to Truth: The First Route5 From Evidence to Truth: The Second Route6 Conclusion

Epistemic trust figures prominently in our socio-cognitive practices. By assigning different degrees of competence to agents, we distinguish between experts and novices and determine the trustworthiness of testimony. This paper probes the claim that epistemic trust furthers our epistemic enterprise. More specifically, it assesses the veritistic value of competence attribution in an epistemic community, i.e., in a group of agents that collaboratively seek to track down the truth. The results, obtained by simulating opinion dynamics, tend to subvert the very idea that competence ascription is essential for the functioning of epistemic collaboration and hence veritistically valuable. On the contrary, we find that, in specific circumstances at least, epistemic trust may prevent a community from finding the truth effectively

Climate models don’t give us probabilistic forecasts. To interpret their results, alternatively, as serious possibilities seems problematic inasmuch as climate models rely on contrary-to-fact assumptions: why should we consider their implications as possible if their assumptions are known to be false? The paper explores a way to address this possibilistic challenge. It introduces the concepts of a perfect and of an imperfect credible world, and discusses whether climate models can be interpreted as imperfect credible worlds. That would allow one to use models for possibilistic prediction and salvage widespread scientific practice

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 future-argument — in short: the AF-argument (Gardiner 2010). Such an argumentative analysis makes explicit the normative and descriptive assumptions which underlie the reasoning, without ascertaining or denying them, and thus enables one to assess the overall strength of the argument as well as to determine which objections do, and which don’t undermine it.