Big data biology—bioinformatics, computational biology, systems biology (including ‘omics’), and synthetic biology—raises a number of issues for the philosophy of science. This article deals with several such: Is data-intensive biology a new kind of science, presumably post-reductionistic? To what extent is big data biology data-driven? Can data ‘speak for themselves?’ I discuss these issues by way of a reflection on Carl Woese’s worry that “a society that permits biology to become an engineering discipline, that allows that science to slip into (...) the role of changing the living world without trying to understand it, is a danger to itself.” And I argue that scientific perspectivism, a philosophical stance represented prominently by Giere, Van Fraassen, and Wimsatt, according to which science cannot as a matter of principle transcend our human perspective, provides the best resources currently at our disposal to tackle many of the philosophical issues implied in the modeling of complex, multilevel/multiscale phenomena. (shrink)

This collection broadens the scientific discussion of modularity by bringing together experts from a variety of disciplines, including artificial life, ...

Philosophers of science traditionally have ignored the details of scientific research, and the result has often been theories that lack relevance either to science or to philosophy in general. In this volume, leading philosophers of biology discuss the limitations of this tradition and the advantages of the "naturalistic turn"—the idea that the study of science is itself a scientific enterprise and should be conducted accordingly. This innovative book presents candid, informal debates among scholars who examine the benefits and problems of (...) studying science in the same way that scientists study the natural world. Callebaut achieves the effect of face-to-face engagement through separate interviews with participants. Contributors include William Bechtel, Robert Brandon, Richard M. Burian, Donald T. Campbell, Patricia Churchland, Jon Elster, Ronald N. Giere, David L. Hull, Philip Kitcher, Karin Knorr Cetina, Bruno Latour, Richard Levins, Richard C. Lewontin, Elisabeth Lloyd, Helen Longino, Thomas Nickles, Henry C. Plotkin, Robert J. Richards, Alexander Rosenberg, Michael Ruse, Dudley Shapere, Elliott Sober, Ryan Tweney, and William Wimsatt. "Why can't we have both theoretical ecology and natural histories, lovingly done?"—Philip Kitcher "Don't underestimate the arrogance of philosophers!"—Elisabeth Lloyd. (shrink)

This volume has its already distant or1g1n in an inter national conference on Evolutionary Epistemology the editors organized at the University of Ghent in November 1984. This conference aimed to follow up the endeavor started at the ERISS (Epistemologically Relevant Internalist Sociology of Science) conference organized by Don Campbell and Alex Rosen berg at Cazenovia Lake, New York, in June 1981, whilst in jecting the gist of certain current continental intellectual developments into a debate whose focus, we thought, was in (...) danger of being narrowed too much, considering the still underdeveloped state of affairs in the field. Broadly speaking, evolutionary epistemology today con sists of two interrelated, yet qualitatively distinct inves tigative efforts. Both are drawing on Darwinian concepts, which may explain why many people have failed to discriminate them. One is the study of the evolution of the cognitive apparatus of living organisms, which is first and foremost the province of biologists and psychologists (H. C. Plotkin, Ed. , Learning, Development, and Culture: Essays in Evolu tionary Epistemology, New York, Wiley, 1984), although quite a few philosophers - professional or vocational - have also felt the need to express themselves on this vast subject (F. M. Wuketits, Ed. , Conce ts and Approaches in Evolutionary Epistemology, Dordrecht Boston, Reidel, 1984). The other approach deals with the evolution of science, and has been dominated hitherto by (allegedly) 'naturalized' philosophers; no book-length survey of this literature is available at present. (shrink)

There are many things that philosophy of biology might be. But, given the existence of a professional philosophy of biology that is arguably a progressive research program and, as such, unrivaled, it makes sense to define philosophy of biology more narrowly than the totality of intersecting concerns biologists and philosophers (let alone other scholars) might have. The reasons for the success of the “new” philosophy of biology remain poorly understood. I reflect on what Dutch and Flemish, and, more generally, European (...) philosophers of biology could do to improve the situation of their discipline locally, regionally, and internationally, paying particular attention to the lessons to be learned from the “Science Wars.”. (shrink)

Systems biology is largely tributary to genomics and other “omic” disciplines that generate vast amounts of structural data. “Omics”, however, lack a theoretical framework that would allow using these data sets as such (rather than just tiny bits that are extracted by advanced data-mining techniques) to build explanatory models that help understand physiological processes. Systems biology provides such a framework by adding a dynamic dimension to merely structural “omics”. It makes use of bottom-up and top-down models. The former are based (...) on data about systems components, the latter on systems-level data. We trace back both modeling strategies (which are often used to delineate two branches of the field) to the modeling of metabolic and signaling pathways in the bottom-up case, and to biological cybernetics and systems theory in the top-down case. We then argue that three roots of systems biology must be discerned to account adequately for the structure of the field: pathway modeling, biological cybernetics, and “omics”. We regard systems biology as merging modeling strategies (supplemented by new mathematical procedures) from data-poor fields with data supply from a field that is quite deficient in explanatory modeling. After characterizing the structure of the field, we address some epistemological and ontological issues regarding concepts on which the top-down approach relies and that seem to us to require clarification. This includes the consequences of identifying modules in large networks without relying on functional considerations, the question of the “holism” of systems biology, and the epistemic value of the “systeome” project that aspires to become the cutting edge of the field. (shrink)

Simon’s bounded rationality , the first scientific research program to seriously take the cognitive limitations of decision makers into account, has often been conflated with his more restricted concept of satisficing—choosing an alternative that meets or exceeds specified criteria, but that is not guaranteed to be unique or in any sense “the best.” Proponents of optimization often dismiss bounded rationality out of hand with the following “hallway syllogism” : bounded rationality “boils down to” satisficing; satisficing is “simply” a theory of (...) search for alternatives that takes into account the costs of computation. Hence, bounded rationality is “just a minor tweak” on optimal search theory. (shrink)

Re-Engineering Philosophy for Limited Beings is about new approaches to many of the big topics in philosophy of science today, but with a very different take. To begin with, we are urged to reject the received Cartesian-Laplacean myths: Descartes’ certainty and Laplace’s computational omniscience. Instead, Wimsatt re-engineers a philosophy for human beings with all their cognitive limitations. His approaches find their starting point in the actual practices of scientists themselves, which he strongly identifies with engineering practices as the source of (...) researchers’ solutions for dealing with a complex world. He aims to construct an understanding of scientific methodology around the central role of reduction. But he dismisses eliminative reductionism in favor of a heuristic-based realist view. Wimsatt’s world is a complex one, and this means that science needs to do away with all the absolute and simple answers, because they do not reflect the world we are living in. A complex world requires the mindset and tinkering of an engineer to uncover its reality. The appropriate response must be heuristics all the way down as we constantly seek out reliable inferences on often shifting ground. To this end, we aim for models and theories that are robust, just as engineers aim to build robust machines. And although errors occur and approaches are fallible, they allow us to continually adapt the heuristics applied and sharpen our perceptions so as to develop more refined tools for investigating and understanding the world. (shrink)

This is the second of two articles in which I reflect on “generalized Darwinism” as currently discussed in evolutionary economics. In the companion article (Callebaut, Biol Theory 6. doi: 10.1007/s13752-013-0086-2, 2011, this issue) I approached evolutionary economics from the naturalistic perspectives of evolutionary epistemology and the philosophy of biology, contrasted evolutionary economists’ cautious generalizations of Darwinism with “imperialistic” proposals to unify the behavioral sciences, and discussed the continued resistance to biological ideas in the social sciences. Here I assess Generalized (...) Darwinism as propounded by Geoffrey Hodgson, Thorbjørn Knudsen, and others, concentrating on the roles of theory and model building in science (and the roles of analogy and metaphor therein), generative replication, and the relation between selection and self-organization. I then point to advances in current biology that promise to be more fruitful as sources of inspiration for evolutionary economics than the project to generalize Darwinism in its current, “hardened Modern Synthesis” form; and I draw some conclusions. (shrink)

This is the first of two articles in which I reflect on “generalized Darwinism” as currently discussed in evolutionary economics. I approach evolutionary economics by the roundabouts of evolutionary epistemology and the philosophy of biology, and contrast evolutionary economists’ cautious generalizations of Darwinism with “imperialistic” proposals to unify the behavioral sciences. I then discuss the continued resistance to biological ideas in the social sciences, focusing on the issues of naturalism and teleology. In the companion article (Callebaut, Biol Theory 6. (...) doi: 10.1007/s13752-013-0087-1, 2011, this issue) I assess generalized Darwinism, concentrating on the roles of theory and model building, generative replication, and the relation between selection and self-organization; and I point to advances in biology that promise to be more fruitful as sources of inspiration for evolutionary economics than the project to generalize Darwinism in its current, “hardened Modern Synthesis” form. (shrink)

In a recent opinion piece, Denis Duboule has claimed that the increasing shift towards systems biology is driving evolutionary and developmental biology apart, and that a true reunification of these two disciplines within the framework of evolutionary developmental biology may easily take another 100 years. He identifies methodological, epistemological, and social differences as causes for this supposed separation. Our article provides a contrasting view. We argue that Duboule’s prediction is based on a one-sided understanding of systems biology as a science (...) that is only interested in functional, not evolutionary, aspects of biological processes. Instead, we propose a research program for an evolutionary systems biology, which is based on local exploration of the configuration space in evolving developmental systems. We call this approach—which is based on reverse engineering, simulation, and mathematical analysis—the natural history of configuration space. We discuss a number of illustrative examples that demonstrate the past success of local exploration, as opposed to global mapping, in different biological contexts. We argue that this pragmatic mode of inquiry can be extended and applied to the mathematical analysis of the developmental repertoire and evolutionary potential of evolving developmental mechanisms and that evolutionary systems biology so conceived provides a pragmatic epistemological framework for the EvoDevo synthesis. (shrink)

I discuss various reactions to my article “Again, what the philosophy of science is not” [Callebaut (Acta Biotheor 53:92–122 (2005a))], most of which concern the naturalism issue, the place of the philosophy of biology within philosophy of science and philosophy at large, and the proper tasks of the philosophy of biology.

Ioannidis [Why most published research findings are false. PLoS Med 2: e124 ] identifies six factors that contribute to explaining why most of the current published research findings are more likely to be false than true, and argues that for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this article, we argue that three “hot” areas in current biological research, viz., agent-based modeling, evolutionary developmental biology, and systems biology, are especially (...) prone to the flaws. (shrink)

The articles in this issue reflect the results of the 25th Altenberg Workshop in Theoretical Biology on ‘‘The Meaning of ‘Theory’ in Biology’’ held at the Konrad Lorenz Institute for Evolution and Cognition Research, Altenberg, Austria, 30 June–3 July, 2011.