Biologists frequently draw on ideas and terminology from engineering. Evolutionary systems biology—with its circuits, switches, and signal processing—is no exception. In parallel with the frequent links drawn between biology and engineering, there is ongoing criticism against this cross-fertilization, using the argument that over-simplistic metaphors from engineering are likely to mislead us as engineering is fundamentally different from biology. In this article, we clarify and reconfigure the link between biology and engineering, presenting it in a more favorable light. We do so by, first, arguing that critics operate with a narrow and incorrect notion of how engineering actually works, and of what the reliance on ideas from engineering entails. Second, we diagnose and diffuse one significant source of concern about appeals to engineering, namely that they are inherently and problematically metaphorical. We suggest that there is plenty of fertile ground left for a continued, healthy relationship between engineering and biology.
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One may distinguish a representation that portrays a biological system as a network from the connections and interactions among the biological entities themselves. It is not obvious that biological systems are networks, or even what that would exactly mean. But we must bracket this interesting issue here.
This does not imply that we advocate a strong dissociation between claims about proximate and ultimate causation. There is a lively debate on that issue (Laland et al. 2013; O’Malley and Soyer 2012; Steinacher and Soyer 2012; Calcott 2013). We are merely making the modest claim that hypotheses about current behavior do not as such presuppose assumptions about evolutionary origins.
See http://en.wikipedia.org/wiki/Release_early,_release_often for a summary of these ideas.
It is worth pointing out that a charge of poor design is only possible if we have some standard of what good design is—so there is an implicit use of engineering in these arguments.
William Wimsatt’s work on generative entrenchment has, for many years, emphasized similarities between evolutionary and technological change (Wimsatt 2007).
“We…suggest that biological research and teaching could and should actually be done without much use of metaphorical thinking…” (Pigliucci and Boudry 2011, p. 455).
There are other forms of surrogative reasoning that share some properties with metaphor and some with models. A significant example is analogy. We leave it to the reader to extrapolate from what we say here to other cases of surrogation, since our aim is not to cover this topic in exhaustive detail.
Note that precise specification makes the content of the model uncontroversial. Whether and how the model matches the biological system may remain controversial.
As one reviewer suggested, a metaphor and a model might differ in other respects too, such as the status of vehicle of representation: a metaphor might be linguistic, while a model is often mathematical. We won’t delve into thorny issues concerning linguistic versus other forms of representation here. It suffices for our purposes that precision is one significant difference between models and metaphors.
As Steven Vogel would have it: “… biomechanics has mainly been the study of how nature does what engineers have shown to be possible. Nature may have gotten there first, but human engineers, not biologists, have provided us with both analytical tools and practical examples” (Vogel 2003, p. 11).
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Calcott, B., Levy, A., Siegal, M.L. et al. Engineering and Biology: Counsel for a Continued Relationship. Biol Theory 10, 50–59 (2015). https://doi.org/10.1007/s13752-014-0198-3
- Gene regulation
- Evolutionary systems biology