Analytic philosophers once pantomimed physics: they tried to understand the world by breaking it down into the smallest possible bits. Thinkers from the Darwinian sciences now pose alternatives to this simplistic reductionism. In this intellectual tour--essays spanning thirty years--William Wimsatt argues that scientists seek to atomize phenomena only when necessary in the search to understand how entities, events, and processes articulate at different levels. Evolution forms the natural world not as Laplace's all-seeing demon but as a backwoods mechanic fixing and re-fashioning machines out of whatever is at hand. W. V. Quine's lost search for a "desert ontology" leads instead to Wimsatt's walk through a tropical rain forest. This book offers a philosophy for error-prone humans trying to understand messy systems in the real world. Against eliminative reductionism, Wimsatt pits new perspectives to deal with emerging natural and social complexities. He argues that our philosophy should be rooted in heuristics and models that work in practice, not only in principle. He demonstrates how to do this with an analysis of the strengths, the limits, and a recalibration of our reductionistic and analytic methodologies. Our aims are changed and our philosophy is transfigured in the process.
I. INTRODUCTION 1. Myths of LaPlacean Omniscience Realism for Limited Beings in a Rich Messy World Social Natures Heuristics as Adaptations for the Real World Nature as Backwoods Mechanic and Used-Parts Dealer Error and Change Organization and Aims of This Book 2. Normative Idealizations versus the Metabolism of Error Inadequacies of Our Normative Idealizations Satisficing, Heuristics, and Possible Behavior for Real Agents The Productive Use of Error-Prone Procedures 3. Toward a Philosophy for Limited Beings The Stance and Outlook of a Scientifically Informed Philosophy of Science Ceteris Paribus, Complexity, and Philosophical Method Our Present and Future Naturalistic Philosophical Methods II. PROBLEM-SOLVING STRATEGIES FOR COMPLEX SYSTEMS 4. Robustness, Reliability, and Overdetermination Common Features of Concepts of Robustness Robustness and the Structure of Theories Robustness, Testability, and the Nature of Theoretical Terms Robustness, Redundancy, and Discovery Robustness, Objectification, and Realism Robustness and Levels of Organization Heuristics and Robustness Robustness, Independence, and Pseudo-Robustness: A Case Study 5. Heuristics and the Study of Human Behavior Heuristics Reductionist Research Strategies and Their Biases An Example of Reductionist Biases: Models of Group Selection Heuristics Can Hide Their Tracks Two Strategies for Correcting Reductionist Biases The Importance of Heuristics in the Study of Human Behavior 6. False Models as Means to Truer Theories Even the Best Models Have "Biases" The Concept of a "Neutral Model" How Models Can Misrepresent Twelve Things To Do with False Models Background of the Debate over Linkage Mapping in Genetics Castle's Attack on the "Linear Linkage" Model Muller's Data and the Haldane Mapping Function Muller's "Two-Dimensional" Arguments against Castle Multiply-Counterfactual Uses of False Models False Models Can Provide New Predictive Tests Highlighting Features of a Preferred Model False Models and Adaptive Design Arguments Summary and Conclusions 7. Robustness and Entrenchment: How the Contingent Becomes Necessary Generative Entrenchment and the Architecture of Adaptive Design Generative Systems Come To Dominate in Evolutionary Processes Resistance to Foundational Revisions Bootstrapping Feedbacks: Differential Dependencies and Stable Generators Implications of Generative Entrenchment Generative Entrenchment and Robustness Conclusion 8. Lewontin's Evidence (That There Isn't Any) Is Evidence Impotent, or Just Inconstant? False Models as Means to Truer Theories Narrative Accounts and Theory as Montage III. REDUCTIONISM(S) IN PRACTICE 9. Complexity and Organization Reductionism and the Analysis of Complex Systems Complexity Evolution, Complexity, and Organization Complexity and the Localization of Function 10. The Ontology of Complex Systems: Levels of Organization, Perspectives, and Causal Thickets Robustness and Reality Levels of Organization Perspectives: A Preliminary Characterization Causal Thickets 11. Reductive Explanation: A Functional Account Two Kinds of Rational Reconstruction Successional versus Inter-Level Reduction Levels of Organization and the Co-Evolution and Development of Interlevel Theories Two Views of Explanation: Major Factors and Mechanisms versus Laws and Deductive Completeness Levels of Organization and Explanatory Costs and Benefits An Example: The Assumption of "the Purity of the Gametes" in the Heterozygote Identificatory Hypotheses as Tools in the Search for Explanations Appendix: Modifications Appropriate to a Cost-Benefit Version of Salmon's Account of Explanation 12. Emergence as Non-Aggregativity and the Biases of Reductionism(s) Reduction and Emergence Aggregativity Perspectival, Contextual, and Representational Complexities; or, "It Ain't Quite So Simple as That!" Adaptation to Fine- and Coarse-Grained Environments: Derivational Paradoxes for a Formal Account of Aggregativity Aggregativity and Dimensionality Aggregativity as a Heuristic for Evaluating Decompositions, and Our Concepts of Natural Kinds Reductionisms and Biases Revisited IV. ENGINEERING AN EVOLUTIONARY VIEW OF SCIENCE 13. Epilogue: On the Softening of the "Hard" Sciences From Straw-Man Reductionist to Lover of Complexity Messiness in State-of-the-Art Theoretical Physics Hidden Elegance and Revelations in Run-of-the-Mill Applied Science "Pure" versus Applied Science, and What Difference Should It Make? Hortatory Closure Appendix A. Important Properties of Heuristics Appendix B. Common Reductionistic Heuristics Appendix C. Glossary of Key Concepts and Assumptions Appendix D. A Panoply of LaPlacean and Leibnizian Demons Notes Bibliography Credits Index