Marcel Weber

Biowissenschaftler an diversen Orten dieser Welt spekulieren heute über die zukünftige Möglichkeit, den Menschen langsamer altern zu lassen, und suchen nach praktischen Wegen, die menschliche Lebensspanne erheblich auszudehnen. Aber wäre ein längeres Leben wirklich ein besseres Leben? Welche Auswirkungen hätte dies für die Gesellschaft im ganzen? Und wie ungerecht wäre es, wenn lebensverlängernde Therapien etwa das Privileg Wohlhabender blieben? Der interdisziplinär angelegte Band bietet erstmals für das deutschsprachige Publikum einen Überblick über die zentralen Aspekte der bisher vor allem in der angelsächsischen Welt geführten Debatte zum Thema Lebensverlängerung. Philosophen, u. a. John Harris, Leon Kass und Peter Singer, und renommierte Biowissenschaftler, darunter David Gems und Michael R. Rose, diskutieren darin aus unterschiedlichen Perspektiven das Projekt eines radikalen Anti-Ageing.

I argue that the originally interest-relative dispositional concept of biological functions can be narrowed in a way that makes functions natural but holistic properties of self-reproducing systems. The additional constraint needed is a coherence relation that obtains exactly between those capacities of an organism's parts that, together, best explain how the organism can self-reproduce. The basic relation that gives rise to this kind of coherence is the contribution that a certain capacity makes to another capacity of the containing system. After developing this account, I show that a system of functions so construed shows the characteristics of a holistic system, strongly resembling a system of beliefs as conceived by semantic holists. The implications for a general conception of holism such as Michael Esfeld's are discussed.

The term molecular genetics sometimes refers to (1) a fundamental theory alleging that genes direct all life processes through the production of proteins and RNAs (ribonucleic acids), sometimes to (2) a more modest, basic theory about the replication and expression of DNA (deoxyribonucleic acid), and sometimes to (3) an investigative approach applied throughout biomedical science that is based on investigative strategies grounded in the basic theory about genes. This entry briefly summarizes the basic knowledge of molecular genetics and surveys philosophical research on the subject, considering all three senses of the term. The focus is on the traditional issue of theoretical reduction as an account of the molecularization of genetics as well as on more recent work that attends to investigative rather than theoretical and explanatory reasoning.

This volume sheds light on still unexplored issues and raises new questions in the main areas addressed by the philosophy of science. Bringing together selected papers from three main events, the book presents the most advanced scientific results in the field and suggests innovative lines for further investigation. It explores how discussions on several notions of the philosophy of science can help different scientific disciplines in learning from each other. Finally, it focuses on the relationship between Cambridge and Vienna in twentieth century philosophy of science. The areas examined in the book are: formal methods, the philosophy of the natural and life sciences, the cultural and social sciences, the physical sciences and the history of the philosophy of science.

A growing number of linguistic attempts to explain how languages change use cultural-evolutionary models involving selection or drift. Developmental constraints and biases, which take center stage in evolutionary developmental biology or evo-devo, seem to be absent within this framework, even though linguistics is home to numerous notions of constraint. In this paper, we show how these evo-devo concepts could be applied to linguistic change and why they should. This requires some conceptual groundwork, due to important differences between linguistic and biotic evolution. In biological evolution, development generates the organism's variable traits on which selection and drift act. In linguistic evolution by analogy, we say development generates the linguistic variants on which selection and drift can act. “Linguistic development” then picks out how individual speakers produce and comprehend language. It involves much more than just learning. Using this broad notion of development, we distinguish between different types of bias that could operate in the processes of linguistic innovation and transmission, which correspond to genetic mutation and biological reproduction, respectively. Having thus sharpened our conceptual toolbox, we then reanalyze two well-documented cases of linguistic change and show that, in both these cases, linguists have only considered Neo-Darwinian evolutionary explanations, falsely deploying an exclusive disjunction of selection and drift. We show that there is at least a third relevant alternative in these examples, namely developmental constraint or bias in the sense we explicate here.

Biological modalities, i.e., biologically possible, impossible, or necessary states of affairs have not received much attention from philosophers. Yet, it is widely agreed that there are biological constraints on physically possible states of affairs, such that not everything that is physically possible is also biologically possible, even if everything that is biologically possible is also physically possible. Furthermore, biologists use concepts that appear to be modal in nature, such as the concept of evolvability in evolutionary developmental biology, or “evo-devo.” The present chapter investigates what kind of modality underlies the concept of evolvability. This concept tries to capture the capacity of an organism or a lineage to sustain genetic changes that enable it to evolve or to evolve adaptively. The basic idea of the proposed approach is to construe evolvability as a kind of accessibility in a modal space. The difficult part is to specify this modal space and the relevant accessibility relation. While there may not be a general way of defining such a relation, there exist model systems for which it is possible, e.g., evolving small RNAs. The modal space in such cases turns out to be quite distinct from those constructed by philosophers, e.g., David Lewis’s similarity metric for possible worlds. Even though the biological case examined here is quite special, attending to the way in which biological possibilities are modeled in this case harbors some general lessons about biological modalities, in particular their dependence on the explanatory goals of the models modeling modality.

Causal selection is the task of picking out, from a field of known causally relevant factors, some factors as elements of an explanation. The Causal Parity Thesis in the philosophy of biology challenges the usual ways of making such selections among different causes operating in a developing organism. The main target of this thesis is usually gene centrism, the doctrine that genes play some special role in ontogeny, which is often described in terms of information-bearing or programming. This paper is concerned with the attempt of confronting the challenge coming from the Causal Parity Thesis by offering principles of causal selection that are spelled out in terms of an explicit philosophical account of causation, namely an interventionist account. I show that two such accounts that have been developed, although they contain important insights about causation in biology, nonetheless fail to provide an adequate reply to the Causal Parity challenge: Ken Waters's account of actual-difference making and Jim Woodward's account of causal specificity. A combination of the two also doesn't do the trick, nor does Laura Franklin-Hall's account of explanation (in this volume). We need additional conceptual resources. I argue that the resources we need consist in a special class of counterfactual conditionals, namely counterfactuals the antecedents of which describe biologically normal interventions.

I attempt to characterize the relationship of classical experimental embryology (CEE) and molecular developmental biology and compare it to the much-discussed case of classical genetics. These sciences are treated here as discovery practices rather than as definitive forms of knowledge. I first show that CEE had some causal knowledge and hence was able to answer specific why?-questions. A paradigm was provided by the case of eye induction, perhaps CEE’s greatest success. The case of the famous Spemann-Mangold organizer is more difficult. I argue that before the advent of molecular biology, knowledge of its causal role in development was very limited. As a result, there was no functional definition of the concept of organizer. I argue that, like the classical gene concept, it is best viewed as an operational concept. This means that an account of reduction such as Kim’s functional reduction, which is still a mainstay in scientific metaphysics, cannot work in these cases. Nonetheless, again like in the classical gene case, the operational concepts of CEE played an important heuristic role in the discovery of molecules involved in morphogenesis and cell differentiation. This was made possible by what I call inter-level investigative practices. These are practices that combine experimental manipulations targeting two (or more) different levels. I conclude that the two sciences are more closely related via their experimental practices than by any inter-level explanatory relations.

The recent literature on causality has seen the introduction of several distinctions within causality, which are thought to be important for understanding the widespread scientific practice of focusing causal explanations on a subset of the factors that are causally relevant for a phenomenon. Concepts used to draw such distinctions include, among others, stability, specificity, proportionality, or actual-difference making. In this contribution, I propose a new distinction that picks out an explanatorily salient class of causes in biological systems. Some select causes in complex biological systems, I argue, have the property of enabling coherent causal control of these systems. Examples of such control variables include hormones and other signaling molecules, e.g., TOR (target of rapamycin), morphogens or the products of homeotic selector genes in embryonic pattern formation. I propose an analysis of this notion based on concepts borrowed from causal graph theory.

This volume, the third in this Springer series, contains selected papers from the four workshops organized by the ESF Research Networking Programme "The Philosophy of Science in a European Perspective" in 2010: Pluralism in the Foundations of Statistics Points of Contact between the Philosophy of Physics and the Philosophy of Biology The Debate on Mathematical Modeling in the Social Sciences Historical Debates about Logic, Probability and Statistics The volume is accordingly divided in four sections, each of them containing papers coming from the workshop focussing on one of these themes. While the programme's core topic for the year 2010 was probability and statistics, the organizers of the workshops embraced the opportunity of building bridges to more or less closely connected issues in general philosophy of science, philosophy of physics and philosophy of the special sciences. However, papers that analyze the concept of probability for various philosophical purposes are clearly a major theme in this volume, as it was in the previous volumes of the same series. This reflects the impressive productivity of probabilistic approaches in the philosophy of science, which form an important part of what has become known as formal epistemology - although, of course, there are non-probabilistic approaches in formal epistemology as well. It is probably fair to say that Europe has been particularly strong in this area of philosophy in recent years.​

The history of developmental biology is interwoven with debates as to whether mechanistic explanations of development are possible or whether alternative explanatory principles or even vital forces need to be assumed. In particular, the demonstrated ability of embryonic cells to tune their developmental fate precisely to their relative position and the overall size of the embryo was once thought to be inexplicable in mechanistic terms. Taking a causal perspective, this Element examines to what extent and how developmental biology, having turned molecular about four decades ago, has been able to meet the vitalist challenge. It focuses not only on the nature of explanations but also on the usefulness of causal knowledge – including the knowledge of classical experimental embryology – for further scientific discovery. It also shows how this causal perspective allows us to understand the nature and significance of some key concepts, including organizer, signal and morphogen. This title is also available as Open Access on Cambridge Core.

Darwin famously held that his use of the term "chance" in evolutionary theory merely "serves to acknowledge plainly our ignorance of the causes of each particular variation". Is this a tenable view today? Or should we revise our thinking about chance in evolution in light of the more advanced, quantitative models of Neo-Darwinian theory, which make substantial use of statistical reasoning and the concept of probability? Is determinism still a viable metaphysical doctrine about biological reality after the quantum revolution in physics, or dowe have to abandon it in favor of an objective indeterminism? In light of such reflections, what is the relevant interpretation of probability in evolutionary theory? Do biologists use the concept of probability because they are finite cognitive agents or because the evolutionary process is fundamentally probabilistic? In this paper, I will show that we do not yet fully understand the nature of chance in evolution.

Several authors have used the notion of causal specificity in order to defend non-parity about genetic causes (Waters 2007, Woodward 2010, Weber 2017, forthcoming). Non-parity in this context is the idea that DNA and some other biomolecules that are often described as information-bearers by biologists play a unique role in life processes, an idea that has been challenged by Developmental Systems Theory (e.g., Oyama 2000). Indeed, it has proven to be quite difficult to state clearly what the alleged special role of genetic causes consists in. In this paper, I show that the set of biomolecules that are normally considered to be information-bearers (DNA, mRNA) can be shown to be the most specific causes of protein primary structure, provided that causal specificity is measured over a relevant space of biological possibilities, disregarding physical as well as logically possible states of the causal variables.

I examine to what extent accounts of mechanisms based on formal interventionist theories of causality can adequately represent biological mechanisms with complex dynamics. Using a differential equation model for a circadian clock mechanism as an example, I first show that there exists an iterative solution that can be interpreted as a structural causal model. Thus, in principle, it is possible to integrate causal difference-making information with dynamical information. However, the differential equation model itself lacks the right modularity properties for a full integration. A formal mechanistic model will therefore have to leave out either noncausal or causal explanatory relations.

Going back at least to Duhem, there is a tradition of thinking that crucial experiments are impossible in science. I analyse Duhem's arguments and show that they are based on the excessively strong assumption that only deductive reasoning is permissible in experimental science. This opens the possibility that some principle of inductive inference could provide a sufficient reason for preferring one among a group of hypotheses on the basis of an appropriately controlled experiment. To be sure, there are analogues to Duhem's problems that pertain to inductive inference. Using a famous experiment from the history of molecular biology as an example, I show that an experimentalist version of inference to the best explanation (IBE) does a better job in handling these problems than other accounts of scientific inference. Furthermore, I introduce a concept of experimental mechanism and show that it can guide inferences from data within an IBE-based framework for induction. 1. Introduction2. Duhem on the Logic of Crucial Experiments3. ‘The Most Beautiful Experiment in Biology’4. Why Not Simple Elimination?5. Severe Testing6. An Experimentalist Version of IBE 6.1. Physiological and experimental mechanisms6.2. Explaining the data6.3. IBE and the problem of untested auxiliaries6.4. IBE-turtles all the way down7. Van Fraassen's ‘Bad Lot’ Argument8. IBE and Bayesianism9. Conclusions.

This Ph.D. thesis provides a pilosophical account of the structure of the evolutionary synthesis of the 1930s and 40s. The first, more historical part analyses how classical genetics came to be integrated into evolutionary thinking, highlighting in particular the importance of chromosomal mapping of Drosophila strains collected in the wild by Dobzansky, but also the work of Goldschmidt, Sumners, Timofeeff-Ressovsky and others. The second, more philosophical part attempts to answer the question wherein the unity of the synthesis consisted. I argue that it exemplifies a weak of form of explanatory unification.

Unlike in physics, the category of thought experiment is not very common in biology. At least there are no classic examples that are as important and as well-known as the most famous thought experiments in physics, such as Galileo’s, Maxwell’s or Einstein’s. The reasons for this are far from obvious; maybe it has to do with the fact that modern biology for the most part sees itself as a thoroughly empirical discipline that engages either in real natural history or in experimenting on real organisms rather than fictive ones. While theoretical biology does exist and is recognized as part of biology, its role within biology appears to be more marginal than the role of theoretical physics within physics. It could be that this marginality of theory also affects thought experiments as sources of theoretical knowledge. Of course, none of this provides a sufficient reason for thinking that thought experiments are really unimportant in biology. It is quite possible that the common perception of this matter is wrong and that there are important theoretical considerations in biology, past or present, that deserve the title of thought experiment just as much as the standard examples from physics. Some such considerations may even be widely known and considered to be important, but were not recognized as thought experiments. In fact, as we shall see, there are reasons for thinking that what is arguably the single most important biological work ever, Charles Darwin’s On the Origin of Species, contains a number of thought experiments. There are also more recent examples both in evolutionary and non-evolutionary biology, as we will show. Part of the problem in identifying positive examples in the history of biology is the lack of agreement as to what exactly a thought experiment is. Even worse, there may not be more than a family resemblance that unifies this epistemic category. We take it that classical thought experiments show the following characteristics: They serve directly or indirectly in the non-empirical epistemic evaluation of theoretical propositions, explanations or hypotheses. Thought experiments somehow appeal to the imagination. They involve hypothetical scenarios, which may or may not be fictive. In other words, thought experiments suppose that certain states of affairs hold and then try to intuit what would happen in a world where these suppositions are true. We want to examine in the following sections if there are episodes in the history of biology that satisfy these criteria. As we will show, there are a few episodes that might satisfy all three of these criteria, and many more if the imagination criterion is dropped or understood in a lose sense. In any case, this criterion is somewhat vague in the first place, unless a specific account of the imagination is presupposed. There will also be issues as to what exactly “non-empirical” means. In general, for the sake of discussion we propose to understand the term “thought experiment” here in a broad rather than a narrow sense here. We would rather be guilty of having too wide a conception of thought experiment than of missing a whole range of really interesting examples.

Philosophy of Experimental Biology explores some central philosophical issues concerning scientific research in experimental biology, including genetics, biochemistry, molecular biology, developmental biology, neurobiology, and microbiology. It seeks to make sense of the explanatory strategies, concepts, ways of reasoning, approaches to discovery and problem solving, tools, models and experimental systems deployed by scientific life science researchers and also integrates developments in historical scholarship, in particular the New Experimentalism. It concludes that historical explanations of scientific change that are based on local laboratory practice need to be supplemented with an account of the epistemic norms and standards that are operative in science. This book should be of interest to philosophers and historians of science as well as to scientists.