Abstract
A goal of this volume is to build on the pathbreaking work by experts such as Bill Wimsatt and Andy Pickering in order to develop a more robust account of robustness. However, the idea may be so multifaceted that no single account will do. I shall canvass a few basic ideas of robustness, popular and technical, and then address such questions as: What is the relation of robustness to fragility or brittleness? Can a system be completely robust? Are decentralized, distributed systems potentially more robust than centralized ones? Which network topologies are more robust than others? What, if anything, do power laws have to do with robustness and with Wimsatt’s “generative entrenchment”? Is there an interesting connection between robustness and design? Robustness and innovation? Robustness and scientific revolutions? Robustness, heuristics, experimental design, and novel prediction? Robustness and realism? My central claim, supported by a diverse body of literature, is that robustness is deeply related to fragility. Rather than vanquishing fragility, complex robustness shifts its location. More than that, complex robustness can actually generate fragility where none existed before.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
See also Perrow (1972, 2011). It is also relevant to mention here Herbert Simon’s seminal work on bounded rationality and the behavior of complex organizations (Simon 1947). Bill Wimsatt and I share an admiration for Simon’s work. As I once told Bill, I regard Simon as one of the great American pragmatists.
- 2.
Although I do not have space to defend this claim, most of the people represented in this volume surely accept some version of it. Incidentally, while large portions of the design are deliberately engineered in response to inputs from “nature,” as is usual in cases of large human constructions, we should expect that modern sciences and their research programs contain important elements that were not explicitly designed, some of which we are surely unaware.
- 3.
Wagner and co-researchers are engaged in an extensive research program to explore these questions involving robustness, embryological development, evolution, specialization, modularity, and the like. For example, Martin and Wagner (2008) discuss the tradeoffs in genetic networks that serve more than one function. They ask to what extent the need to serve several functions constrains the network architecture—and what effect such compromises may have on robustness.
- 4.
Actually, this failure rate calculates to 4.5 “sigmas” or standard deviations from the mean value, assuming a normal distribution. The extra 1.5 sigmas are imposed to allow for long-term variation, given that the approach is evidence-based and that most evidence is short-term.
- 5.
Descartes admitted algebraic derivations as well as geometrical ones, and his use of ‘derive’ was more liberal than that allowed by the later, formal concept of deduction.
- 6.
I refer to Duhem (1954) on the need for auxiliary assumptions in any predictive inference and the resulting difficulty of pinning the blame for failure on any one premise.
- 7.
Here we can include not only philosophical and scientific systems based on reason and evidence but also ethical and religious systems based on revelation, mind-control, and various other self-protecting contagions and social viruses discussed by meme theorists. The most secure, deeply entrenched of these is, according to the line being developed here, vulnerable to catastrophic collapse. Gaye McCollum-Nickles reminds me here of Oliver Wendell Holmes, Jr.’s poem, “The Deacon’s Masterpiece or, the Wonderful ‘One-hoss Shay’: A Logical Story,” about the sudden collapse of Calvinism in late 19th-century America.
Pickering (Chapter 13) regards standalone, material machines as the hallmark of modernity. Also falling within modernity is the extension of this idea to Bacon’s and Descartes’ (unsuccessful) attempts to mechanize scientific procedures (the alleged discovery of “the scientific method”). As a response to an unpredictable world, the idea of “standalone” ethical systems invulnerable to the arrows of fortune is very old. Such were the systems of the ancient Stoics and Epicureans.
- 8.
Bridgman (1927), one of the founders of operationism, blamed the need for the relativity revolution on physicists’ failure to operationally define their concepts (especially simultaneity) prior to theorizing—as if we could work out a robust system of concepts prior to theory in work at the frontier of research!
- 9.
Since robustness includes resilience to environmental shocks in addition to predator-prey issues, even in biology, the phenomenon is more general than the usual sort of arms race in which, e.g., long legs for greater speed increase the fragility of the legs. Our primary concern here is with human technological systems, including epistemic systems. We can construe the race as an attempt to identify and avoid possible new sorts of accidents before they happen, or before they happen again.
- 10.
See Geoffrey West’s lecture, with slides, available at http://online.itp.ucsb.edu/online/pattern_i03/west/. Power laws apparently characterize the metabolism rate, energy use, extinction rates, and many other aspects of the animal and plant worlds. For criticism, see Downs et al. (2008). For a survey of leading models of species extinction, see Newman and Palmer (2003).
- 11.
In my opinion the distinction between novel “design” by natural selection and intelligent design by human engineering is usually exaggerated. While there are important differences, at bottom both are selectionist processes, that is, variation-plus-selection processes. See Nickles (2003 and forthcoming).
- 12.
A generic form of common power laws is \(f{\left(x\right)} = cx^\delta + o{\left(x^\delta \right)}\), where c is the constant, δ is the scaling factor, as before, and o is an asymptotically small function that captures small deviations or uncertainties.
- 13.
See Kauffman (1993), Chapter 2 et passim. The NK model is Kauffman’s start toward “a statistical mechanics of fitness landscapes” (1993, p. 40). “N refers to the number of parts of a system—genes in a genotype, amino acids in a protein, or otherwise. Each part makes a fitness contribution which depends upon that part and upon K other parts among the N.”
- 14.
There is already a large literature, both technical and popular, on these developments. Newman et al. (2006) is a collection of many of the most influential papers to that date. See also the Carlson and Doyle articles, Watts (1999), and Jen (2005). Among the popular or semi-popular works, see Buchanan (2002, 2007), Miller and Page (2007), and Barabási (2002). The websites of many of these people often contain additional resources.
- 15.
The graph can be found at http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=4206%26objectType=file.
- 16.
For the color version, the reader may consult Albert et al. (2000) or http://www.computerworld.com/s/article/75539/Scale_Free_Networks.
- 17.
Both principles would seem to play a role in Wimsatt’s conception of generative entrenchment as applied to developing systems, either biological or humanly devised.
- 18.
Among other attempts to explain some power laws, see Fabrikant et al. (2002). The study of phase transitions at critical points is another locus of such efforts.
- 19.
Popper attempted to remove the fear of making mistakes. His motto was “We learn from our mistakes.” In his methodology of scientific research programs, Lakatos (1970) followed Kuhn in the respect mentioned in the main text while retaining some Popperian elements. Kuhn (1970) objected to Popper’s talk of falsifications as mistakes.
- 20.
In the chapters on normal science, Kuhn invites us to look at scientific work from the point of view of the normal-scientific practitioner, who, according to Kuhn, is convinced that s/he is uncovering the truth about the world. In the chapters on scientific revolutions, Kuhn invites us instead to look at the history of science from above and to note the contingency involved in the revolutionary passage to a new paradigm. As a rough generalization, philosophers have tended to take a normal scientific, realist view whereas sociologists have distanced themselves from the normal science perspective. In my opinion, contrary to Kuhn, taking the normal scientists’ viewpoint does not require conviction that the paradigm is on the track to a final truth about the world.
- 21.
Bak does not mention Kuhnian revolutions, though he does relate his work to other models of transformative change such as Gould-Eldredge punctuated equilibrium and mass extinction (Bak, Chapter 1). Sornette (2003, Chapter 3) contends that the causes of stock market crashes are not ordinary events, that crashes are outliers with a special statistics of their own that call for special explanations. However, his model is not totally different from those under discussion. The underlying processes involve increasingly correlated phenomena of complex systems, driven by positive feedback, that send the system to a critical point, where it becomes unstable. At this point a normal change can tip the system one way or the other. As an emergent phenomenon of a complex system, such a disruption, like a Kuhnian revolution, is holistic. It cannot be analyzed into component parts.
- 22.
- 23.
It is then open to a Kuhnian to reply that genuine revolutions are precisely those disturbances that could not be contained within the bounds of normal science and that resulted in overturning the old approach, that making the distinction a matter of degree violates the hierarchical nature of his model. One response would be that even Kuhn, qua historian, agrees that classical mechanics went through several phase changes between Newton and Einstein, changes that transformed it almost beyond recognition as it incorporated the so-called Baconian sciences; later adopted the latest Lagrangian, Hamiltonian, and other mathematical techniques; rejected the ideas of action-at-a-distance and that all forces are central forces; became statistical-probabilistic, etc. The very concept of mechanics was transformed in the process. So why count all of this as normal science?
- 24.
See Soler (Chapter 10, Section 10.16) as well as Soler (2000, 2004). Kuhn (1962) stated that paradigm change is almost inevitable given the unavoidable contingency of its formation. After all, at the frontiers of a new domain of research it is most obvious that scientists cannot yet know much about the structure of that domain. It is thus exceedingly improbable that a given paradigm will be able to anticipate future results so as to get everything right. Thus Soler’s treatment of contingency nicely complements my own about maturation as increasing vulnerability to transformative change in the system. Sociologists of science from Latour and Woolgar (1979), Knorr-Cetina (1981), and Pickering (1984) to the present have given far more attention to the contingency of scientific decisions than have philosophers of science.
- 25.
This last is a familiar point often made about Kuhn and Feyerabend. Papineau (1979) provides an excellent discussion. Kuhn retained a more limited sort of meaning holism later in his career (Kuhn 2000). Soler (2000, 2004) interprets Kuhn’s account of meaning and meaning change in terms of the structuralism inspired by Ferdinand de Saussure’s work.
- 26.
Hume’s problem of induction implies that we should be fallibilists about the future, but the problem is so general that it undercuts all enterprises more or less equally. More specific considerations involved in what I call heuristic appraisal provide differential appraisals of future prospects and thereby make a difference (Nickles 2006).
- 27.
Lakatos (1970) and his students made heuristics an important part of search programs.
- 28.
Although the two are intricately linked (Rescher 1977), we need to distinguish between the retrospective and the prospective (or heuristic) robustness of a product and the robustness of the process that produced it. A product can be robust even though the process that produced it is now regarded as “played out,” sterile, unlikely to produce fruitful new results, thus not robust in the heuristic sense. And a process may be evaluated as robust in the heuristic sense even if has not yet produced much in the way of warranted products. Thus we need to interpret my basic expression R(s,p,d,c) generously to allow that robustness of system s in the dimension(s) of future promise might be of degree d great enough to withstand both endogenous perturbations p (anomalies, adjustments to the research system) and less endogenous ones such as the complaint of underdevelopment, compared to the competition.
- 29.
References
Albert, Réka, Hawoong Jeong, and Albert-László Barabási. 2000. “Error and Attack Tolerance of Complex Networks.” Nature 406(27 July):378–81. Reprinted in Newman et al. (2006), 503–6.
Bak, Per. 1996. How Nature Works: The Science of Self-Organized Criticality. New York: Copernicus, Springer.
Barabási, Albert-László. 2002. Linked: The New Science of Networks. Cambridge, MA: Perseus.
Bridgman, P.W. 1927. The Logic of Modern Physics. New York: Macmillan.
Buchanan, Mark. 2002. Nexus: Small Worlds and the Groundbreaking Theory of Networks. New York: Norton.
Buchanan, Mark. 2007. The Social Atom: Why the Rich Get Richer, Cheaters Get Caught, and Your Neighbor Usually Looks Like You. New York: Bloomsbury.
Calvin, William. 2002. A Brain for All Seasons: Human Evolution and Abrupt Climate Change. Chicago: University of Chicago Press.
Carlson, Jean, and John Doyle. 1999. “Highly Optimized Tolerance: A Mechanism for Power Laws in Designed Systems.” Physical Review E60:1412–27.
Carlson, Jean M., and John Doyle. 2002. “Complexity and Robustness.” Proceedings of the National Academy of Science 99:2538–45.
Downs, Cynthia, J.P. Hayes, and C.R. Tracy. 2008. “Scaling Metabolic Rate with Body Mass and Inverse Body Temperature: A Test of the Arrhenius Fractal Supply Model.” Functional Ecology 22:239–44.
Doyle, John, et al. 2005. “Robustness and the Internet: Theoretical Foundations.” In Jen (2005), 273–85.
D’Souza, Raissa, C. Borgs, J.T. Chayes, N. Berger, and R. Kleinberg. 2007. “Emergence of Tempered Preferential Attachment From Optimization.” Proceedings of the National Academy of Sciences 104:6112–7.
Duhem, Pierre. 1954. The Aim and Structure of Physical Theory. Princeton, NJ: Princeton University Press. Translated from the French edition of 1914.
Fabrikant, Alex, Elias Koutsoupias, and Christos Papadimitriou. 2002. “Heuristically Optimized Trade-offs: A New Paradigm for Power Laws in the Internet.” In Proceedings of the 29th International Colloquium on Automata, Languages, and Programming (ICALP), edited by P. Widmayer, et al., 110–22. Berlin: Springer.
Feynman, Richard. 1965. The Character of Physical Law. Cambridge, MA: MIT Press.
Gershenson, Carlos, ed. 2008. Complexity: 5 Questions: Automatic Press/VIP/Vince.
Gertstein, Marc. 2008. Flirting with Disaster: Why Accidents Are Rarely Accidental. New York: Union Square Press.
Giere, Ronald. 1988. Explaining Science: A Cognitive Approach. Chicago: University of Chicago Press.
Giere, Ronald. 2008. “Comment on Teller: Incommensurability from a Modeling Perspective.” In Soler et al. (2008), 265–9.
Gladwell, Malcolm. 2000. The Tipping Point: How Little Things Can Make a Big Difference. Boston: Little Brown.
Hindo, Brian. 2007. “At 3 M, a Struggle Between Creativity and Efficiency.” Business Week, June 11.
Horgan, John. 1995. “From Complexity to Perplexity.” Scientific American 272(June):74–9.
Jen, Erica, ed. 2005. Robust Design: A Repertoire of Biological, Ecological, and Engineering Case Studies (Santa Fe Institute Studies in the Sciences of Complexity). Oxford: Oxford University Press.
Kauffman, Stuart. 1993. The Origins of Order: Self-Organization and Selection in Evolution. Oxford: Oxford University Press.
Keller, Evelyn Fox. 2005. “Revisiting ‘Scale-Free’ Networks.” BioEssays 27:1060–8.
Klein, Martin, Abner Shimony, and Trevor Pinch. 1979. “Paradigm Lost?” Isis 70:429–40.
Knorr-Cetina, Karin. 1981. The Manufacture of Knowledge. Oxford: Pergamon Press.
Kuhn, Thomas. 1962. The Structure of Scientific Revolutions. 2nd ed. with “Postscript—1969”, 1970. Chicago: University of Chicago Press.
Kuhn, Thomas. 1970. “Logic of Discovery or Psychology of Research?” In Lakatos and Musgrave (1970), 1–20.
Kuhn, Thomas. 2000. The Road Since Structure, edited by James Conant and John Haugeland. Chicago: University of Chicago Press.
Lakatos, Imre. 1970. “Falsification and the Methodology of Scientific Research Programmes.” In I. Lakatos and A. Musgrave, 91–195.
Lakatos, Imre, and Alan Musgrave, eds. 1970. Criticism and the Growth of Knowledge. Cambridge: Cambridge University Press.
Latour, Bruno. 1987. Science in Action: How to Follow Scientists and Engineers Through Society. Cambridge, MA: Harvard University Press.
Latour, Bruno, and Steve Woolgar. 1979. Laboratory Life: The Social Construction of Scientific Facts. Beverly Hills, CA: Sage.
Laudan, Larry. 1981. “A Confutation of Convergent Realism.” Philosophy of Science 48:19–49.
Leplin, Jarrett, ed. 1984. Scientific Realism. Berkeley, CA: University of California Press.
Levin, Simon, et al. 1998. “Resilience in Natural and Socioeconomic Systems.” Environment and Development Economics 3:225–36.
Martin, O.C., and Andreas Wagner. 2008. “Multifunctionality and Robustness Tradeoffs in Model Genetic Circuits.” Biophysical Journal 94:2927–2937.
McMullin, Ernan. 1993. “Rationality and Paradigm Change in Science.” In World Changes: Thomas Kuhn and the Nature of Science, edited by Paul Horwich, 55–78. Cambridge, MA: MIT Press.
Miller, John, and Scott Page. 2007. Complex Adaptive Systems: An Introduction to Computational Models of Social Life. Princeton, NJ: Princeton University Press.
Mitchell, Melanie. 2009. Complexity: A Guided Tour. New York: Oxford University Press.
Newman, Mark. 2001. “Scientific Collaboration Networks.” Physical Review E 64, paper 016131.
Newman, Mark, and Richard Palmer. 2003. Modeling Extinction. Oxford: Oxford University Press.
Newman, Mark, Albert-László Barabási, and Duncan Watts, eds. 2006. The Structure and Dynamics of Networks. Princeton, NJ: Princeton University Press.
Nickles, Thomas. 1997. “A Multi-Pass Conception of Scientific Inquiry.” In Danish Yearbook of Philosophy 1997, vol. 32, edited by Stig Andur Pedersen, 11–43. Copenhagen: Museum Tusculanem Press.
Nickles, Thomas. 2003. “Evolutionary Models of Innovation and the Meno Problem.” In International Handbook on Innovation, edited by Larisa Shavinina, 54–78. Amsterdam: Elsevier.
Nickles, Thomas. 2006. “Heuristic Appraisal: Context of Discovery or Justification?” In Revisiting Discovery and Justification: Historical and Philosophical Perspectives on the Context Distinction, edited by Jutta Schickore and Friedrich Steinle, 159–82. Dordrecht: Springer (Archimedes Series).
Nickles, Thomas. 2009. “Scientific Revolutions.” Stanford Encyclopedia of Philosophy. http://plato.stanford.edu/entries/scientific-revolutions/.
Nickles, Thomas. Forthcoming. “Some Normal Scientific Puzzles.” In Kuhn’s “The Structure of Scientific Revolutions” Revisited, edited by Theodre Arabatzis, and Vasso Kindi. London: Routledge.
Papineau, David. 1979. Theory and Meaning. Oxford: Oxford University Press.
Perrow, Charles. 1972. Complex Organizations: A Critical Essay. 3rd ed. New York: McGraw-Hill.
Perrow, Charles. 1984. Normal Accidents: Living with High-Risk Technologies. New York: Basic Books.
Perrow, Charles. 2011. The Next Catastrophe. Princeton, NJ: Princeton University Press.
Pickering, Andrew. 1980. “Exemplars and Analogies: A Comment on Crane’s Study of Kuhnian Paradigms in High Energy Physics” and “Reply to Crane.” Social Studies of Science 10:497–502 and 507–8.
Pickering, Andrew. 1984. Constructing Quarks. Chicago: University of Chicago Press.
Pickering, Andrew. 1995. The Mangle of Practice: Time, Agency, and Science. Chicago: University of Chicago Press.
Popper, Karl. 1963. Conjectures and Refutations. London: Routledge.
Psillos, Stathis. 1999. Scientific Realism: How Science Tracks Truth. London: Routledge.
Putnam, Hilary. 1962. “What Theories Are Not.” In Logic, Methodology and Philosophy of Science, edited by Ernest Nagel, Patrick Suppes, and Alfred Tarski, 215–27. Palo Alto, CA: Stanford University Press. Reprinted in Putnam’s Mathematics Matter and Method: Philosophical Papers, vol. 1, 2nd ed., Cambridge: Cambridge University Press, 1979.
Quine, W.V. 1951. “Two Dogmas of Empiricism.” Philosophical Review 60:20–43. Reprinted with changes in Quine’s From a Logical Point of View. Cambridge, MA: Harvard University Press, 1953, 20–46.
Rescher, Nicholas. 1977. Methodological Pragmatism. Oxford: Blackwell.
Rheinberger, Hans-Jörg. 1999. Toward a History of Epistemic Things: Synthesizing Proteins in the Test Tube. Stanford, CA: Stanford University Press.
Rouse, Joseph. 2003. “Kuhn’s Philosophy of Scientific Practice.” In Thomas Kuhn, edited by Thomas Nickles, 101–21. Cambridge: Cambridge University Press.
Schumpeter, Joseph. 1942. Capitalism, Socialism and Democracy. New York: Harper & Brothers.
Simon, Herbert. 1947 (later editions). Administrative Behavior: A Study of Decision-Making Processes in Administrative Organization. New York: Macmillan.
Simon, Herbert. 1981. The Sciences of the Artificial. 2nd ed. Cambridge: MIT.
Soler, Léna. 2000. “Le concept kuhnien d’incommensurabilité, reconsidéré a la lumière d’une théorie structurale de la signification.” Philosophia Scientae 4:2(October):189–217.
Soler, Léna. 2004. “The Kuhnian Concept of Incommensurability Reconsidered in the Light of a Saussurian Framework.” Malaysian Journal of Science and Technology Studies May:51–75.
Soler, Léna, Howard Sankey, and Paul Hoyningen-Huene, eds. 2008. Rethinking Scientific Change and Theory Comparison: Stabilities, Ruptures, Incommensurabilities? Dordrecht: Springer.
Sornette, Didier. 2003. Why Stock Markets Crash: Critical Events in Complex Financial Systems. Princeton, NJ: Princeton University Press.
Strogatz, Steven. 2003. Sync: The Emerging Science of Spontaneous Order. New York: Hyperion.
Teller, Paul. 2001. “Twilight of the Perfect Model Model.” Erkenntnis 55:393–415.
Teller, Paul. 2008. “Of Course Idealizations Are Incommensurable.” In Rethinking Scientific Change and Theory Comparison: Stabilities, Ruptures, Incommensurabilities? edited by L. Soler et al., 247–64. Netherlands: Springer.
Wagner, Andreas. 2005. Robustness and Evolvability in Living Systems. Princeton, NJ: Princeton University Press.
Watts, Duncan. 1999. Small Worlds: The Dynamics of Networks Between Order and Randomness. Princeton, NJ: Princeton University Press.
Willinger, Walter, and John Doyle. 2005. “Robustness and the Internet: Design and Evolution.” In Robust Design: A Repertoire of Biological, Ecological, and Engineering Case Studies, edited by E. Jen, 231–71. Oxford: Oxford University Press.
Wimsatt, William C. 1981. “Robustness, Reliability, and Overdetermination.” In Scientific Inquiry and the Social Sciences, edited by M. Brewer and B. Collins, 124–63. San Francisco, CA: Jossey-Bass. Reprinted in Wimsatt (2007), 43–74.
Wimsatt, William C. 2006. “Aggregate, Composed, and Evolved Systems: Reductionistic Heuristics as Means to more Holistic Theories.” Biology and Philosophy 21:667–702.
Wimsatt, William C. 2007. Re-Engineering Philosophy for Limited Beings: Piecewise Approximations to Reality. Cambridge, MA: Harvard University Press.
Wray, K. Brad. 2007. “Kuhnian Revolutions Revisited.” Synthese 158:61–73.
Zhou, Tong, Jean M. Carlson, and John Doyle. 2002. “Mutation, Specialization, and Hypersensitivity in Highly Optimized Tolerance.” Proceedings of the National Academy of Science 99:2049–2054.
Acknowledgements
Thanks to Léna Soler for organizing the conference on robustness at Nancy 2, to the members of the Poincaré Archives for their hospitality, to the participants, especially Léna, Bill Wimsatt, an anonymous referee, and Gaye McCollum-Nickles, for helpful comments on either my presentation or a previous draft. I am also generally indebted to Andy Pickering for his attention in his publications to what I call heuristic appraisal and to his pragmatic outlook on the sciences generally. For discussion of Kuhn I am indebted to my students, Jared Ress and Jonathan Kanzelmeyer.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer Science+Business Media B.V.
About this chapter
Cite this chapter
Nickles, T. (2012). Dynamic Robustness and Design in Nature and Artifact. In: Soler, L., Trizio, E., Nickles, T., Wimsatt, W. (eds) Characterizing the Robustness of Science. Boston Studies in the Philosophy of Science, vol 292. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-2759-5_14
Download citation
DOI: https://doi.org/10.1007/978-94-007-2759-5_14
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-2758-8
Online ISBN: 978-94-007-2759-5
eBook Packages: Humanities, Social Sciences and LawPhilosophy and Religion (R0)