Embryos of Thought: The Productive Role of Language in Early Developmental Genetics

Embryo (image taken from www.wellsphere.com)

Life sciences have been categorized in recent history by a tendency towards biological determinism, by which the expression of the particular genes of an organism’s is said to dictate much of its development and existence. If the above claim sounds matter-of-factly accurate – and I think it would to most people – it is probably because statements of this sort have long been “proven” to be “true” by apparently rigorous applications of the scientific method. What is often obscured by this “habit” of presenting results simply as being the automatic products of verification through experimentation is that it maintains illusions of purpose and control in science. Moreover, it also hides many of the behind-the-scenes processes involved in knowledge production, which often includes a considerable amount of guesswork, luck, and all-around messiness.

Evelyn Keller’s book Making Sense of Life: Explaining biological development with Models, metaphors and machines can be seen as an effort to challenge the discourses of determinism and certainty built around these disciplines. In the chapter entitled Genes, Gene Action, and Genetic Programming, Keller sets out to uncover sources of ambiguity in the language used to make sense of early ‘genetics’. She starts it off with a quote from Hungarian chemist and philosopher of science Michael Polanyi as way to introduce one of her central arguments: “Languages are the product of man’s groping for words in the process of making new conceptual decisions, to be conveyed by words” (in Keller, 123).

What is implied here is that there is a need to invent or adapt language to deal with new experiences always comes either before or at the same time as the new experience is encountered. Applied in contrast to a history of developmental biology, this highlights the fact that seemingly objective scientific truths exist as linguistic constructs first, and are often fleshed out and verified in evidence only later. Within this framework, the ambiguity present in the words that are groped for in order to explain science can often lead to incomplete, inaccurate, or (worst?) overly-applicable conceptual models and metaphors.

Keller presents examples of such cases of over-applicability in the following chapter entitled Taming the Cybernetic Metaphor, where she traces the evolution of uses of the cybernetic metaphors of ‘feedback’ and ‘control’ in different models designed to explain embryonic development. Here, Keller frames her discussion in terms of the flexibility of abstract concepts and models, particularly Delbruck’s mathematical model, which was simultaneously applied to support competing sides of the embryonic development debate (159-167). By doing so, she also calls into question the conservative tendency of the scientific world – and perhaps of society at large – to accept new information if it best fits existing one. Later in the article, Keller attributes this tendency to the guiding principle of parsimony in science, which she describes as “a prescription for conserving as much of the pre-existing formulations as new findings [can] permit” (171).

In other words, it was – and still is – considered normal for scientists to rely on accepted models to gain acceptance for their own discoveries, arguments, or models. What this entails however is that acceptance (or legitimacy) may not be solely about the accuracy of new information but also about ‘how it was framed’ or ‘how well it fit’. In the end, what can often get lost in this process are the unresolved ambiguities that Keller demonstrated were present in the earlier models and concepts, or worst, the fact that newfound evidence may have long proven them to be incomplete or inaccurate.

After having concentrated mainly on the science behind the models and on their different applications, Keller ends this second chapter by bringing the focus back on language once again. She writes that “much as with genetic structures, language builds into new formulations a tacit memory of older concepts, shaping the course of research in accordance with its prior history, even while it also, and at the same time, provides the means by which new concepts are formulated and new perceptions achieved” (172).

It is important to mention however, that despite appearances of it – and my own initial interpretations – the two articles were likely not meant as a case for linguistic determinism, by which choices in language (and models and metaphors) would directly dictate other language, research, and results. Surely, Keller’s intentions were not to swing the pendulum from one extreme all the way to the other. In fact, she is careful to counter her strong claims for the determining effects of language with examples of how ambiguity in meaning of concepts and the flexibility in application of models actually proved to be “productive” in many ways. Most notably, they are said to have filled explanatory gaps long enough to allow to shift the focus onto finding solutions to other problems (129) as well as to have infused some force into research (132), leading to important discoveries such as DNA. Keller’s use of the word “force” is an important one here because it positions language as one of the many influencing factors playing a role in the production of meaning.

It seems like what Keller is getting at, without specifically mentioning it or naming it as such in these two chapters is a type of interactionist approach to the production of scientific knowledge. In fact, in a general sense, the chapters (and the book from which they were taken) argue for the importance of recognizing the tight connections between the use of language in the social domain and how it produces biological understandings. Her final line best exemplifies this position: “words – together with the linguistic forms by which they are given meaning – are, in this sense, just like genes and the regulatory networks in which they are employed, the primary vehicle for their own evolution” (172).

Works cited:

Keller, Evelyn Fox. “Genes, Gene action, and genetic programming” and “Taming the cybernetic metaphor”. Making Sense of Life. Explaining Biological Development with models, metaphors and machines. Harvard University Press. 2002, pp123-172.