Metaphors in Science (Not Just Public Communication)

Metaphors in science are often understood as being most important for communicating to non-specialists. They are unquestionably important for this purpose. However, they’re also powerful tools for communicating within scientific communities, even—maybe especially—when scientists use them without recognizing them. Because language and physical practices influence each other, metaphors are powerful tools for shaping how science happens.

Importantly, metaphors aren’t just about poetic or decorative language, but about how analogical reasoning—understanding one thing through its similarities to another, even while they remain different—is embedded in the fabric of language (see the intro to metaphor theory). These analogies—often made less obvious and eventually even invisible through metaphors that become routine (that become “dead”)—shape how researchers think about and therefore make knowledge about and technologies for those metaphor’s targets: from the questions that seem reasonable to ask to what data is collected, how data are analyzed, and how results are synthesized and expressed.

Rhetoricians, social scientists, and scientists have described many examples of how metaphors shape scientific practice. Here are just a few:

Cells – In Andrew Reynolds’ book on how metaphors shaped the development of cell biology, he traces how thinking about cells as rooms encouraged thinking about them as closed or walled off, how thinking about them as “cell factories” or other machines has encouraged thinking about them as having discrete modular parts, and how thinking about them as “elementary organisms” has encouraged thinking about individual cells even in multicellular organisms as existing in societies and having individual choices or “fates.”

“Invasive” and “foreign” species – Banu Subramanian and others have shown how attitudes to eradicating and keeping out invasive and foreign other-than-human species parallels language about rounding up and keeping out invasive and foreign humans, in ways that emphasize borders and, in Subramanian’s words, “vilify and pathologize the exotic and invasive.”

The genetic code — Perhaps the best-known and most powerful metaphor in biology. By thinking about DNA and RNA as codes (originally human-language texts, and then as computer codes; these two metaphorical source domains now freely mix), an incredible number of tools have been developed to read and write, code and decode, edit and debug genetic texts. DNA and RNA are often manipulated as lines of text using the same kind of software and algorithms employed to manipulate, parse, and search human-language text. These strategies are now becoming limiting for DNA and RNA design problems that relate to how these molecules physically interact in three dimensions, for example, in how long-range interactions matter to the success of DNA design for synthetic biology.

Further reading:

On how working with bacterial and yeast cells as chassis encourages thinking about them as empty operating systems or machines, not as creatures that have their own needs and interests, see Szymanski and Calvert on “Designing with living systems in the synthetic yeast project” and Szymanski on “Who are the users of synthetic DNA? Using metaphors to activate microorganisms at the center of synthetic biology.”
On how scientific technologies (and CRISPR specifically) are described as agents that move of their own accord, so that scientists and science policy are described as having to “keep up” with technologies that they themselves make, see Leah Ceccarelli on “CRISPR as agent: A metaphor that rhetorically inhibits the prospects for responsible research.”
On how scientists and other researchers come to very different conclusions about analogizing the human brain to a computer, see this collection of articles in Frontiers in Ecology and Evolution.
For an extensive discussion of how the genetic code and “book of life” metaphors came to be, see Lily Kay on “Who wrote the book of life?”