Science & Education

, Volume 20, Issue 5–6, pp 453–471 | Cite as

Why Machine-Information Metaphors are Bad for Science and Science Education

  • Massimo PigliucciEmail author
  • Maarten Boudry


Genes are often described by biologists using metaphors derived from computational science: they are thought of as carriers of information, as being the equivalent of “blueprints” for the construction of organisms. Likewise, cells are often characterized as “factories” and organisms themselves become analogous to machines. Accordingly, when the human genome project was initially announced, the promise was that we would soon know how a human being is made, just as we know how to make airplanes and buildings. Importantly, modern proponents of Intelligent Design, the latest version of creationism, have exploited biologists’ use of the language of information and blueprints to make their spurious case, based on pseudoscientific concepts such as “irreducible complexity” and on flawed analogies between living cells and mechanical factories. However, the living organism = machine analogy was criticized already by David Hume in his Dialogues Concerning Natural Religion. In line with Hume’s criticism, over the past several years a more nuanced and accurate understanding of what genes are and how they operate has emerged, ironically in part from the work of computational scientists who take biology, and in particular developmental biology, more seriously than some biologists seem to do. In this article we connect Hume’s original criticism of the living organism = machine analogy with the modern ID movement, and illustrate how the use of misleading and outdated metaphors in science can play into the hands of pseudoscientists. Thus, we argue that dropping the blueprint and similar metaphors will improve both the science of biology and its understanding by the general public.


Machine Analogy Intelligent Design Niche Construction Natural Theology Design Argument 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The research of Maarten Boudry was supported by the Flemish Fund for Scientific Research (FWO).


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Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Department of PhilosophyCUNY-Lehman CollegeBronxUSA
  2. 2.Department of Philosophy & Moral SciencesGhent UniversityGhentBelgium

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