The world is complex, but acknowledging its complexity requires an appreciation for the many roles context plays in shaping natural phenomena. In _Unsimple Truths, _Sandra Mitchell argues that the long-standing scientific and philosophical deference to reductive explanations founded on simple universal laws, linear causal models, and predict-and-act strategies fails to accommodate the kinds of knowledge that many contemporary sciences are providing about the world. She advocates, instead, for a new understanding that represents the rich, variegated, interdependent fabric of many levels (...) and kinds of explanation that are integrated with one another to ground effective prediction and action. Mitchell draws from diverse fields including psychiatry, social insect biology, and studies of climate change to defend “integrative pluralism”—a theory of scientific practices that makes sense of how many natural and social sciences represent the multi-level, multi-component, dynamic structures they study. She explains how we must, in light of the now-acknowledged complexity and contingency of biological and social systems, revise how we conceptualize the world, how we investigate the world, and how we act in the world. Ultimately _Unsimple Truths _argues that the very idea of what should count as legitimate science itself should change. (shrink)
This fine collection of essays by a leading philosopher of science presents a defence of integrative pluralism as the best description for the complexity of scientific inquiry today. The tendency of some scientists to unify science by reducing all theories to a few fundamental laws of the most basic particles that populate our universe is ill-suited to the biological sciences, which study multi-component, multi-level, evolved complex systems. This integrative pluralism is the most efficient way to understand the different and complex (...) processes - historical and interactive - that generate biological phenomena. This book will be of interest to students and professionals in the philosophy of science. (shrink)
Biological knowledge does not fit the image of science that philosophers have developed. Many argue that biology has no laws. Here I criticize standard normative accounts of law and defend an alternative, pragmatic approach. I argue that a multidimensional conceptual framework should replace the standard dichotomous law/ accident distinction in order to display important differences in the kinds of causal structure found in nature and the corresponding scientific representations of those structures. To this end I explore the dimensions of stability, (...) strength, and degree of abstraction that characterize the variety of scientific knowledge claims found in biology and other sciences. (shrink)
Beatty, Brandon, and Sober agree that biological generalizations, when contingent, do not qualify as laws. Their conclusion follows from a normative definition of law inherited from the Logical Empiricists. I suggest two additional approaches: paradigmatic and pragmatic. Only the pragmatic represents varying kinds and degrees of contingency and exposes the multiple relationships found among scientific generalizations. It emphasizes the function of laws in grounding expectation and promotes the evaluation of generalizations along continua of ontological and representational parameters. Stability of conditions (...) and strength of determination in nature govern projectibility. Accuracy, ontological level, simplicity, and manageability provide additional measures of usefulness. (shrink)
Philosophical accounts of emergence have been explicated in terms of logical relationships between statements (derivation) or static properties (function and realization). Jaegwon Kim is a modern proponent. A property is emergent if it is not explainable by (or reducible to) the properties of lower level components. This approach, I will argue, is unable to make sense of the kinds of emergence that are widespread in scientific explanations of complex systems. The standard philosophical notion of emergence posits the wrong dichotomies, confuses (...) compositional physicalism with explanatory physicalism, and is unable to represent the type of dynamic processes (self-organizing feedback) that both generate emergent properties and express downward causation. (shrink)
The `fact' of pluralism in science is nosurprise. Yet, if science is representing andexplaining the structure of the oneworld, why is there such a diversity ofrepresentations and explanations in somedomains? In this paper I consider severalphilosophical accounts of scientific pluralismthat explain the persistence of bothcompetitive and compatible alternatives. PaulSherman's `Levels of Analysis' account suggeststhat in biology competition betweenexplanations can be partitioned by the type ofquestion being investigated. I argue that thisaccount does not locate competition andcompatibility correctly. I then defend anintegrative (...) model for understanding pluralism. This view is based on taking seriously both thecomplexity and contingency of biologicalorganization and the idealized character ofbiological models. On this view, explanationbecomes, among other things, the location forthe integration of diverse models. I explicatemy argument by an analysis of explanations ofdivision of labor in social insects. (shrink)
The controversy regarding the unit of selection is fundamentally a dispute about what is the correct causal structure of the process of evolution by natural selection and its ontological commitments. By characterizing the process as consisting of two essential steps--interaction and transmission--a singular answer to the unit question becomes ambiguous. With such an account on hand, two recent defenses of competing units of selection are considered. Richard Dawkins maintains that the gene is the appropriate unit of selection and Robert Brandon, (...) in response, argues that the individual organism is better suited to the role. This paper argues that by making explicit the underlying questions that each of these views addresses, the apparent conflict can be resolved. Furthermore, such a resolution allows for a more complete and realistic understanding of the process of evolution by natural selection. (shrink)
Multilevel research strategies characterize contemporary molecular inquiry into biological systems. We outline conceptual, methodological, and explanatory dimensions of these multilevel strategies in microbial ecology, systems biology, protein research, and developmental biology. This review of emerging lines of inquiry in these fields suggests that multilevel research in molecular life sciences has significant implications for philosophical understandings of explanation, modeling, and representation.
ABSTRACT It has long been held that the structure of a protein is determined solely by the interactions of the atoms in the sequence of amino acids of which it is composed, and thus the stable, biologically functional conformation should be predictable by ab initio or de novo methods. However, except for small proteins, ab initio predictions have not been successful. We explain why this is the case and argue that the relationship among the different methods, models, and representations of (...) protein structure is one of integrative pluralism. Our defence appeals to specific features of the complexity of the functional protein structure and to the partial character of representation in general. We present examples of integrative strategies in protein science. _1._ Introduction _2._ Partiality of Representation _3._ Protein Functional Complexity _4._ Modelling Protein Structure _4.1_ Integrating ab initio and experimental models _4.2_ Integrating multiple experimental models _5._ Conclusion. (shrink)
It has been claimed that ceteris paribus laws, rather than strict laws are the proper aim of the special sciences. This is so because the causal regularities found in these domains are exception-ridden, being contingent on the presence of the appropriate conditions and the absence of interfering factors. I argue that the ceteris paribus strategy obscures rather than illuminates the important similarities and differences between representations of causal regularities in the exact and inexact sciences. In particular, a detailed account of (...) the types and degrees of contingency found in the domain of biology permits a more adequate understanding of the relations among the sciences. (shrink)
In this article I consider the challenges for exporting causal knowledge raised by complex biological systems. In particular, James Woodward’s interventionist approach to causality identified three types of stability in causal explanation: invariance, modularity, and insensitivity. I consider an example of robust degeneracy in genetic regulatory networks and knockout experimental practice to pose methodological and conceptual questions for our understanding of causal explanation in biology. †To contact the author, please write to: Department of History and Philosophy of Science, University of (...) Pittsburgh, 1017 Cathedral of Learning, Pittsburgh, PA 15260; e‐mail: [email protected] (shrink)
It has long been held that the structure of a protein is determined solely by the interactions of the atoms in the sequence of amino acids of which it is composed, and thus the stable, biologically functional conformation should be predictable by ab initio or de novo methods. However, except for small proteins, ab initio predictions have not been successful. We explain why this is the case and argue that the relationship among the different methods, models, and representations of protein (...) structure is one of integrative pluralism. Our defence appeals to specific features of the complexity of the functional protein structure and to the partial character of representation in general. We present examples of integrative strategies in protein science. 1. Introduction2. Partiality of Representation3. Protein Functional Complexity4. Modelling Protein Structure4.1 Integrating ab initio and experimental models4.2 Integrating multiple experimental models5. Conclusion. (shrink)
In this paper I discuss recent debates concerning etiological theories of functions. I defend an etiological theory against two criticisms, namely the ability to account for malfunction, and the problem of structural doubles. I then consider the arguments provided by Bigelow and Pargetter (1987) for a more forward looking account of functions as propensities or dispositions. I argue that their approach fails to address the explanatory problematic for which etiological theories were developed.
Division of labor and its associated phenomena have been viewed as prime examples of group-level adaptations. However, the adaptations are the result of the process of evolution by natural selection and thus require that groups of insects once existed and competed for reproduction, some of which had a heritable division of labor while others did not. We present models, based on those of Kauffman (1984) that demonstrate how division of labor may occur spontaneously among groups of mutually tolerant individuals. We (...) propose that division of labor itself is not a product of natural selection but instead is a "typical" outcome of self organization. (shrink)
This is a collection of papers presented at the Symposium "Are There are Laws of Biology?", in the 1996 Biennial Meetings of the Philosophy of Science Association. It includes four separate papers: "Why Do Biologists Argue Like They Do?" by John Beatty, "Does Biology Have Laws? The Experimental Evidence" by Robert Brandon, "Two Outbreaks of Lawlessness in Recent Philosophy of Biology" by Elliott Sober, and "Pragmatic Laws" by Sandra D. Mitchell.
The question, “Will science remain human?” expresses a worry that deep learning algorithms will replace scientists in making crucial judgments of classification and inference and that something crucial will be lost if that happens. Ever since the introduction of telescopes and microscopes humans have relied on technologies to “extend” beyond human sensory perception in acquiring scientific knowledge. In this paper I explore whether the ways in which new learning technologies “extend” beyond human cognitive aspects of science can be treated instrumentally. (...) I will consider the norms for determining the reliability of a detection instrument, nuclear magnetic resonance spectroscopy, in predicting models of protein atomic structure. Do the same norms that apply in that case be used to judge the reliability of Artificial Intelligence deep learning algorithms? (shrink)
Proceedings of the Pittsburgh Workshop in History and Philosophy of Biology, Center for Philosophy of Science, University of Pittsburgh, March 23-24 2001 Session 2: Female Orgasms and Evolutionary Theory.
There has been a recent resurgence of interest in anthropomorphism, attributable to both the rise of cognitive ethology and the requirements of various forms of expanded, environmental ethics. The manner and degree to which non-human animals are similar to human beings has thus become a focus of scientific research and a necessary component to our decisions to act morally. At its basis, anthropomorphism involves claims about the similarity of non-human objects or beings to humans. Critics of anthropomorphism often attack the (...) presumptive character of such claims. In this paper I consider a range of stances toward anthropomorphism from global rejections to specific models. The bumper sticker version of this talk could be: science made too easy is bound to be wrong. In the end I will argue that specific anthropomorphic theses are supported or not supported by the same rigorous experimental and logical reasoning as any other scientific model. (shrink)
In this paper I argue that two domains of uncertainty should inform our strategies for making social policy on new genetic technologies. The first is biological complexity, which includes both unknown consequences on known variables and unknown unknowns. The second is value pluralism, which includes both moral conflict and moral pluralism. This framework is used to investigate policy on genetically modified food and suggests that adaptive management is required to track changes in biological knowledge of these interventions and that less (...) simplistic, polemic representations of scientific knowledge are required to permit democratic decision making. (shrink)
Sociobiologists explain human social behavior as genetically adapative. The intervention of cultural learning into the processes of the acquisition and transmission of human behavior makes such explanation prima facie unjustified. William Durham has developed a theory of coevolution which claims that although the processes of genetic evolution and cultural evolution are independent, the results of the two processes are "functionally complementary." In this paper I characterize the conditions necessary for giving an explanation by adaptation of human behavior and argue that (...) Durham's defense of functional complementarity cannot be justified until further evidence of the causal background conditions of cultural transmission and selection are presented. (shrink)