Biology & Philosophy

, Volume 29, Issue 3, pp 293–313 | Cite as

Engineering and evolvability

  • Brett CalcottEmail author


Comparing engineering to evolution typically involves adaptationist thinking, where well-designed artifacts are likened to well-adapted organisms, and the process of evolution is likened to the process of design. A quite different comparison is made when biologists focus on evolvability instead of adaptationism. Here, the idea is that complex integrated systems, whether evolved or engineered, share universal principles that affect the way they change over time. This shift from adaptationism to evolvability is a significant move for, as I argue, we can make sense of these universal principles without making any adaptationism claims. Furthermore, evolvability highlights important aspects of engineering that are ignored in the adaptationist debates. I introduce some novel engineering examples that incorporate these key neglected aspects, and use these examples to challenge some commonly cited contrasts between engineering and evolution, and to highlight some novel resemblances that have gone unnoticed.


Evolvability Adaptationism Teleology Engineering Evolutionary systems biology Evo-devo 



This paper has a long history. Early formulations benefited from feedback at the Philosophy of Biology at Dolphin Beach conference, at ISHPSSB, and at the “Progress by Design” conference in Bielefeld. A draft paper by Ian Wills, and a long café discussion with Dan Nicholson prompted me to think more deeply about the connection between engineering and evolved systems. Arnon Levy, Michael Weisberg, Maureen O’Malley, Emily Parke, Kim Sterelny and two anonymous reviewers provided useful comments (and words of encouragement) on later versions. This work was supported by a Australian Research Council Postdoctoral Fellowship and a Visiting Fellowship at the Konrad Lorenz Institute for Evolution and Cognition Research.


  1. Altshuler DL, Dickson WB, Vance JT, Roberts SP, Dickinson MH (2005) Short-amplitude high-frequency wing strokes determine the aerodynamics of honeybee flight. Proc Natl Acad Sci 102:18213–18218CrossRefGoogle Scholar
  2. Autumn K, Gravish N (2008) Gecko adhesion: evolutionary nanotechnology. Philos Trans R Soc A Math Phys Eng Sci 366:1575–1590CrossRefGoogle Scholar
  3. Autumn K, Peattie A (2002) Mechanisms of adhesion in geckos. Integr Comp Biol 42:1081–1090CrossRefGoogle Scholar
  4. Boudry M, Pigliucci M (2013) The mismeasure of machine: Synthetic biology and the trouble with engineering metaphors. Stud Hist Philos Sci Part C Stud Hist Philos Biol Biomed Sci 44:660–668Google Scholar
  5. Breivold HP, Crnkovic I, Eriksson PJ (2008) Analyzing software evolvability. Presented at the computer software and applications, 2008. COMPSAC’08. 32nd Annual IEEE International, pp 327–330Google Scholar
  6. Brown RL (2013) What evolvability really is. Br J Philos Sci doi: 10.1093/bjps/axt014
  7. Calcott B (2009) Lineage explanations: explaining how biological mechanisms change. Br J Philos Sci 60:51–78CrossRefGoogle Scholar
  8. Calcott B (2013a) Why how and why aren’t enough: more problems with Mayr’s proximate-ultimate distinction. Biol Philos 28:767–780Google Scholar
  9. Calcott B (2013b) Engineering: biologists borrow more than words. Nature 502:170CrossRefGoogle Scholar
  10. Ciliberti S, Martin OC, Wagner A (2007) Innovation and robustness in complex regulatory gene networks. Proc Natl Acad Sci 104:13591–13596CrossRefGoogle Scholar
  11. Connell C (2009) Software engineering !=computer science. Dr Dobb’s: the world of software development. Retrieved 4 Mar 2011, from
  12. Cook S, Ji H, Harrison R (2000) Software evolution and software evolvability. University of Reading, UKGoogle Scholar
  13. Csete ME, Doyle JC (2002) Reverse engineering of biological complexity. Science 295:1664–1669CrossRefGoogle Scholar
  14. Dennett DC (1995) Darwin’s dangerous idea. Simon & Schuster, New York CityGoogle Scholar
  15. Dupré J (2013) I-living causes. Aristot Soc Suppl 87:19–37CrossRefGoogle Scholar
  16. Eldar A, Elowitz MB (2010) Functional roles for noise in genetic circuits. Nature 467:167–173CrossRefGoogle Scholar
  17. French MJ (1994) Invention and evolution. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  18. Gamma E, Helm R, Johnson R, Vlissides J (1994) Design patterns. Pearson Education, PearsonGoogle Scholar
  19. Geim AK, Dubonos SV, Grigorieva IV, Novoselov KS, Zhukov AA, Shapoval SY (2003) Microfabricated adhesive mimicking gecko foot-hair. Nat Mater 2:461–463CrossRefGoogle Scholar
  20. Gerhart J, Kirschner M (2007) The theory of facilitated variation. Proc Natl Acad Sci 104(Suppl 1):8582–8589CrossRefGoogle Scholar
  21. Gilbert SF (2000) Developmental biology, 7th edition, 9th edn. Sinauer Associates, SunderlandGoogle Scholar
  22. Greiner C (2010) Gecko-inspired Nanomaterials. In: Kuma CSSR (ed) Biomimetic and bioinspired nanomaterials. Wiley-VCH, New YorkGoogle Scholar
  23. Griffiths PE (1996) The historical turn in the study of adaptation. Br J Philos Sci 47:511–532CrossRefGoogle Scholar
  24. Hendrikse JL, Parsons TE, Hallgrímsson B (2007) Evolvability as the proper focus of evolutionary developmental biology. Evol Dev 9:393–401CrossRefGoogle Scholar
  25. Jacob F (1977) Evolution and tinkering. Science 196:1161–1166CrossRefGoogle Scholar
  26. Kirschner M, Gerhart J (1998) Evolvability. Proc Natl Acad Sci 95:8420–8427CrossRefGoogle Scholar
  27. Kirschner MW, Gerhart JC (2006) The plausibility of life: resolving Darwin’s dilemma. Yale University Press, New HavenGoogle Scholar
  28. Kitano H (2004) Biological robustness. Nat Rev Genet 5:826–837CrossRefGoogle Scholar
  29. Lewens T (2002) Adaptationism and engineering. Biol Philos 17:1–31CrossRefGoogle Scholar
  30. Lewens T (2004) Organisms and artifacts. Bradford BookGoogle Scholar
  31. Lewontin RC (1996) Evolution as engineering. In: Collado-Vides J, Magasanik B, Smith T (eds) Integrative approaches to molecular biology. MIT Press, Cambridge, MAGoogle Scholar
  32. Lüer C, Rosenblum DS, van der Hoek A (2001) The evolution of software evolvability. Presented at the proceedings of the 4th international workshop on principles of software evolution, pp 134–137Google Scholar
  33. Mayr E (1961) Cause and effect in biology. Science 134:1501–1506CrossRefGoogle Scholar
  34. Monteiro A (2012) Gene regulatory networks reused to build novel traits: co-option of an eye-related gene regulatory network in eye-like organs and red wing patches on insect wings is suggested by optix expression. BioEssays 34:181–186CrossRefGoogle Scholar
  35. Munteanu A, Solé RV (2008) Neutrality and robustness in evo-devo: emergence of lateral inhibition. PLoS Comput Biol 4:e1000226CrossRefGoogle Scholar
  36. Newman SA, Bhat R (2009) Dynamical patterning modules: a “pattern language” for development and evolution of multicellular form. Int J Dev Biol 53:693–705CrossRefGoogle Scholar
  37. Parnas DL (1972) On the criteria to be used in decomposing systems into modules. Commun ACM 12:1053–1058Google Scholar
  38. Parter M, Kashtan N, Alon U (2008) Facilitated variation: how evolution learns from past environments to generalize to new environments. PLoS Comput Biol 4:e1000206CrossRefGoogle Scholar
  39. Pauwels E (2013) Communication: mind the metaphor. Nature 500:523–524CrossRefGoogle Scholar
  40. Pigliucci M (2008) Is evolvability evolvable? Nat Rev Genet 9:75–82CrossRefGoogle Scholar
  41. Pigliucci M (2010) Genotype-phenotype mapping and the end of the “genes as blueprint” metaphor. Philos Trans R Soc B Biol Sci 365:557–566CrossRefGoogle Scholar
  42. Pigliucci M, Boudry M (2010) Why machine-information metaphors are bad for science and science education. Sci Educ 20:453–471CrossRefGoogle Scholar
  43. Pugno NM (2007) Towards a spiderman suit: large invisible cables and self-cleaning releasable super adhesive materials. J Phys: Condens Matter 19:395001Google Scholar
  44. Pugno NM (2008) Spiderman gloves. Nano Today 3:35–41CrossRefGoogle Scholar
  45. Raman K, Wagner A (2011) Evolvability and robustness in a complex signalling circuit. Mol BioSyst 7:1081–1092CrossRefGoogle Scholar
  46. Reeves JW (1992) What is software design. C++ J 2. Retrieved from
  47. Shubin N (2008) Your inner fish. Pantheon Books, New YorkGoogle Scholar
  48. Smith P (2011) Software build systems. Addison-Wesley Professional, BostonGoogle Scholar
  49. Sterelny K (2004) Symbiosis, evolvability, and modularity. In: Schlosser G, Wagner GP (eds) Modularity in development and evolution. University of Chicago Press, ChicagoGoogle Scholar
  50. Swiegers GF (2012) Bioinspiration and biomimicry in chemistry. Wiley, New YorkCrossRefGoogle Scholar
  51. Tinbergen N (1963) On aims and methods of ethology. Zeitschrift für Tierpsychologie 20:410–433CrossRefGoogle Scholar
  52. Vogel S (2003) Comparative biomechanics. Princeton University Press, PrincetonGoogle Scholar
  53. Wagner A (2007) Robustness and evolvability in living systems. Princeton University Press, PrincetonGoogle Scholar
  54. Wagner A (2011) The origins of evolutionary innovations: a theory of transformative change in living systems. Oxford University Press, OxfordCrossRefGoogle Scholar
  55. Wagner GP, Altenberg L (1996) Complex adaptations and the evolution of evolvability. Evolution 50:967–976CrossRefGoogle Scholar
  56. Woodward J (2010) Causation in biology: stability, specificity, and the choice of levels of explanation. Biol Philos 25:287–318CrossRefGoogle Scholar
  57. Woodward J (2013) II-Mechanistic explanation: its scope and limits. Aristot Soc Suppl 87:39–65CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Center for Advanced Modeling, Emergency Medicine DepartmentJohns Hopkins UniversityBaltimoreUSA

Personalised recommendations