2 min and 33 sec to read, 637 words

In this recent essay, Philip Ball makes a series of important observations in the service of an argument for ditching mechanical or machine metaphors when describing biology. We misunderstand life if we seek analogies outside of life. One example he cites is our understanding of the genome, and here I really found myself guilty of what he describes: thinking about the genome as a database that is read and then copied and…we have all used that language when we describe genetics, but Ball cites Barbara McClintock¹ Her Nobel speech is worth reading in full, here: https://www.nobelprize.org/uploads/2018/06/mcclintock-lecture.pdf , and makes the point crisp and clear:

So how now should we be speaking about biology? Keller herself tentatively suggested that we might adopt the prescient suggestion of the Nobel laureate biologist Barbara McClintock in recognising that the genome is a responsive, reactive system, not some passive data bank: as McClintock called it, a ‘highly sensitive organ of the cell’.

There’s virtue in that picture, but I think it points to a wider consideration: that the best narratives and metaphors for thinking about how life works come not from our technologies (machines, computers) but from life itself. Some biologists now argue that we should think of all living systems, from single cells upwards, not as mechanical contraptions but as cognitive agents, capable of sifting and integrating information against the backdrop of their own internal states in order to achieve some self-determined goal. Our biomolecules appear to make decisions not in the manner of on/off switches but in loosely defined committees that obey a combinatorial logic, comparable to the way different combinations of just a few light-sensitive cells or olfactory receptor molecules can generate countless sensations of colour or smell. The ‘organic technology’ of language, where meaning arises through context and cannot be atomised into component parts, is a constantly useful analogy. Life must be its own metaphor.

This puts agency at the heart of the discussion about not just life, but also intelligence – and so asks some profound questions about the metaphors that govern our research into artificial intelligence and machine learning.

But do metaphors really matter? Is this not just philosophical woowoo that is spouted by those who cannot build and code? It is easy to dismiss philosophical analysis of technology as an armchair hobby, but I do think that such a dismissal would be a bad mistake. Our choice of metaphor really determines the possible design space for what we do to a much higher degree than we usually recognize, and this is true for the mind as well as for any other phenomenon we want to understand better.

It is enough to imagine that we were forced to explore the mind in any of the earlier metaphors we used for it – like windmills or electrical circuits or telephone switchboard – to realize that the boundaries of our design space are the boundaries of our metaphors.² Today’s different metaphors include mind as brain, mind as computer and mind as rhizome – see Schuh, K.L. and Cunningham, D.J., 2004. “Rhizome and the mind: Describing the metaphor.” The idea that we should describe life as agency, and then intelligence as a feature of life – and so hence dependent on agency – is one that is floating around in many different formats right now, and I do think that there is a lot to be said for exploring this perspective more deeply in order to understand how agency fits into the larger understanding of what we call intelligence.

Ball concludes:

And shouldn’t we have seen that all along? For what, after all, is extraordinary – and challenging to scientific description – about living matter is not its molecules but its aliveness, its agency. It seems odd to have to say this, but it’s time for a biology that is life-centric.

Footnotes and references

• 1
  Her Nobel speech is worth reading in full, here: https://www.nobelprize.org/uploads/2018/06/mcclintock-lecture.pdf
• 2
  Today’s different metaphors include mind as brain, mind as computer and mind as rhizome – see Schuh, K.L. and Cunningham, D.J., 2004. “Rhizome and the mind: Describing the metaphor.”