While discussing some sections of a paper I wrote with Maarten Boudry, we have seen a number of reasons why using machine-information metaphors is bad for science education. As I pointed out before, the full paper also devotes quite a bit of space to arguing that those metaphors haven’t been particularly good in actual scientific research. One of the fascinating things to watch after I posted the first part of this commentary was the number of people who vehemently defended the “biological organisms are machines” take, both here on the blog and on my Twitter feed. It’s like here we are, in the second decade of the 21st century, and there are still a lot of Cartesians around, who have apparently never heard of David Hume. Oh well.
In the conclusion of this two-part series I am going to focus on the last section of my paper with Maarten, where we discuss the search for alternative metaphors, and in the end (spoiler alert!) suggest that the best thing to do at this point is just to describe things as they are, staying as clear as possible of metaphorical language. And when one really cannot avoid it, then use multiple metaphors and be very clear on the limits of their use. Let’s take a look.
In their classic work on metaphors, Lakoff and Johnson argue that the basic function of metaphorical concepts is to structure a new kind of experience in terms of a more familiar and delineated experience. In science as well as in everyday language, metaphors highlight particular aspects of whatever it is we are trying to grasp, but they will inevitably distort others. For example, the image of the “tree of life,” with new species branching off as budding twigs and extinct species as dead branches, is an instructive approximation of the relations of evolutionary descent. However, it can also foster misconceptions about “progress” in evolution, or lead to a simplistic conception of speciation events, or to a downplay of horizontal gene transfer and reticulate (i.e., by interspecies hybridization) speciation events. To give one more example, in physical chemistry the model of the atom as a miniature solar system, with electrons orbiting the nucleus as planets, though still having wide public appeal, is fundamentally inaccurate.
Of course, no metaphor will do its job perfectly, but it is crucial to realize, as Lakoff and Johnson have shown, that the widespread deployment of a particular metaphor can have a feedback effect on the way we perceive things, not just how we present them to others. In the examples discussed in my paper with Maarten, the lure of machine-information metaphors in the history of biology has invited scientists to think of genomes as “blueprints” for organisms, written in the four-letter alphabet of DNA and readable in a manner analogous to a computer code. But as we argue, the machine-information conception of living systems has led both the public and the scientific community astray.
In response to this problem, some scientists and science educators have proposed several alternative and improved metaphors to characterize the relationship between genotype and phenotype. Biologist Patrick Bateson, for instance, was probably the first to compare the DNA sequence of living organisms with a recipe for a cake. The idea of a genetic recipe has several advantages over the blueprint metaphor, the most important being that it takes into account pleiotropy (one gene affecting more than one trait) and epistasis (gene–gene interactions). As a consequence, the simple picture of a one-to-one (or close to) correspondence between particular genes and phenotypic traits is abandoned, which becomes clear when one considers that there is no way to locate particular ingredients in individual crumbs of a cake. Accordingly, there is no possibility of reverse-engineering the end product to the set of procedures (the “recipe”) that made the final product possible. This has important consequences not just for science education, but for research agendas, as the idea of ‘‘reverse engineering’’ is commonly invoked everywhere from genomic studies to the understanding of the brain.
Of course, if carried too far, the recipe metaphor can in turn be quite misleading. To get the desired result, a cook has to lump together different ingredients in the correct proportions and follow a set of instructions for handling the dough and preparing the oven. But actual developmental encoding in living organisms is an enormously more complex and very different sort of procedure, which is also highly dependent on epigenetic factors and unpredictable vagaries of the external environment. The expression of specific genes in the course of development resembles nothing like the way a cook handles the ingredients of a recipe. Living organisms are also highly differentiated in a number of functional parts or components (cell types, tissues, etc.), in contrast with the homogenous cake that comes out of the oven. Moreover, the genome is not written in anything like a ‘‘language,’’ as in the case of a recipe, and it certainly does not contain a description of the desired end product in any meaningful sense of the word ‘‘description.’’
Condit and colleagues have discussed the recipe metaphor as an alternative to talk of blueprints, pointing out that it was adopted ‘‘with surprising swiftness’’ by science popularizers and the media in the 1990s. However, they also remark that, as a new ‘‘master metaphor’’ to capture the relationship between genotype and phenotype, the image of a recipe for a cake has little to recommend either. For example, evoking recipes can invite people to think of the genome as a step-by-step manual that describes ‘‘how to make a human,’’ in that sense falling into the same trap as the idea of a blueprint.
That being said, if contrasted with the blueprint metaphor, the recipe metaphor conveys the point about lack of one-to-one correspondence between genes and phenotypes very well, and hence it highlights an important fact about development and what biologists call the Genotype => Phenotype map. If the recipe metaphor is used within this restricted context, for example in explicit contrast with the characteristics of a blueprint, it is immediately clear what are the salient points of connection with living systems, and people are less likely to be misled by stretching the metaphor beyond usefulness. If the recipe metaphor is presented as an alternative to the blueprint, however, it is bound to mislead people no less than its rival.
The same point applies to other interesting metaphors that have been proposed in this context, for example Lewis Wolpert’s comparison of early embryonic development with the Japanese art of origami. The analogy highlights the circuitous step-by-step development of the early embryo, but of course in a piece of origami art the structure is imposed top-down from an intelligent agent, whereas the functional differentiation in the embryo is regulated bottom-up by a complex interaction between genes and environment. Moreover, origami simply fold to yield the final product, which in a very real sense is already there from the beginning. This is definitely not the way embryos develop, with their ability to respond to local and external environmental fluctuations.
The general problem that we have been discussing seems to us to be not just that one kind of metaphor or another is woefully inadequate to conceptualize biological organisms and their evolution. It is that it simply does not seem to be possible to come up with a metaphor that is cogent and appropriate beyond a very limited conceptual space. Although some of the alternatives are more accurate than the blueprint metaphor (in some respects), Maarten and I certainly have not found one that we would recommend as a replacement. Should we therefore try to avoid the use of metaphors in biological teaching and research altogether? Or do we simply expect too much from metaphors in science and education?
Analogical and metaphorical thinking is widespread among human beings, although of course different cultures and historical moments inspire people to use different metaphors. After all, a metaphor is an attempt to make sense of novel concepts by pairing them with known ideas to increase our overall understanding. Metaphorical thinking is therefore part of our language, and language is inextricably connected to our thinking, but to put it as Wittgenstein did: ‘‘It is, in most cases, impossible to show an exact point where an analogy starts to mislead us.’’ Yet a great part of doing philosophy consists precisely in clarifying our language in an attempt to advance our thinking. To quote Wittgenstein again: ‘‘Philosophy is a battle against the bewitchment of our intelligence by means of our language.’’ To complicate matters further, there is emerging empirical evidence that the human brain processes metaphors in a specific fashion: research on Alzheimer’s patients, for instance (see ref. in the paper), found that impairment of the brain’s ‘‘executive’’ function, associated with the prefrontal cortex, leads to poor understanding of novel metaphors (while, interestingly, comprehension of familiar metaphors is unaffected). Metaphorical thinking seems to be a biologically entrenched functional mode of our brains, and may therefore be hard to avoid altogether.
Both science and philosophy have made ample use of metaphorical and analogical thinking, sometimes with spectacularly positive results, at other times more questionably so. Nonetheless, it seems that nowhere is metaphorical thinking so entrenched — and so potentially misleading — as in biology. Given the maturity of biology as a science, and considering that it deals with objects whose nature is not as alien to our daily experience as, say, those of quantum physics, Maarten and I do not actually see any good reason for clinging onto outdated metaphors in biological education and research for characterizing living organisms, their genomes and their means of development. Taking into account the fact that the machine information metaphors have been grist to the mill of ID creationism, fostering design intuitions and other misconceptions about living systems, we think it is time to dispense with them altogether. Still, we are also not as naive as to expect that this advice will be followed by scientists and science educators any time soon, precisely because the machine/information metaphor is so entrenched in biology education. What to do then? We propose two approaches, one for science educators, the other for practicing scientists.
In science education, talk of metaphorical thinking can be turned into a teaching moment. Students (and the public at large) would actually greatly benefit from explanations that contrast different metaphors with the express goal of highlighting the limitations intrinsic in metaphors and analogies. So, for instance, science educators and writers could talk about the human genome by introducing the blueprint metaphor, only to immediately point out why it does not capture much of what genomes and organisms are about; they could then proceed to familiarize their students and readers with alternative metaphors, say the recipe one, focusing on differences with the original metaphor while of course not neglecting to point out the (different) deficiencies of the new approach as well. The goal of this process would be to foster a cautious attitude about metaphorical thinking, as well as to develop a broader understanding of how unlike commonsense modern science really is. On the latter point, it is interesting to note, for instance, that a popular refrain among evolution or global warming deniers is that ‘‘simple commonsense’’ shows that the scientists are wrong, a position that ignores the proper weight of technical expertise in favor of a folk understanding of nature. It is therefore crucial that the public appreciates the limitations of common sense thinking about science.
There is an analogous teaching moment that can be brought to bear when research scientists engage in unbridled metaphorical thinking: we could refer to this as a philosophy appreciation moment. Scientists are notoriously insensitive to, or even downright dismissive of, considerations arising from the history and philosophy of their discipline, and often for good practical reasons: modern science is a highly specialized activity, where there is barely enough time to keep up with the overwhelming literature in one’s own narrow field of research, and certainly not enough incentive to indulge in historical readings or philosophical speculation. Nonetheless, historians and philosophers of science can easily show the pitfalls of metaphorical thinking (by using well-documented historical examples) and even get across to their colleagues some basic notions of philosophy (by analyzing the effects of particular metaphors on the development of specific lines of scientific inquiry). None of this will quickly amount to overcoming C.P. Snow’s infamous divide between ‘‘the two cultures,’’ but it may bring about better understanding and appreciation of philosophy by scientists, and perhaps even help science see new horizons that have been hitherto obscured by a superficially illuminating metaphor.
Massimo, I have that reference you asked Coel about. Actually, I found three:
Journal of Machine-Learning Biology Volume 1440, issue 42 (see how old and respectable it is!).
“How Blueprints for Machine-Learning Biological Design Do Not Imply an Intelligent Blueprinter”
Journal of Machine-Learning Biology Volume 1452, issue 33
“Mechanism in Biology: Scientism’s Clear and Literal Refudiation of Intelligent Design”
Journal of Machine-Learning Scientistic Philosophy of Biology Volume 2478, issue 24
“When a Metaphor is Not a Metaphor: The Philosophy of Literalistic Statements about Mechanism from Hero of Alexandria.”
Brodix: “Look at how the world is being run. Does ego or wisdom seem to be the primary motivation? Wouldn’t a philosophy taking the obvious into account seem reasonable?”
Leaving aside the definitions of “world” and “run”, some kind of dichotomy (or schism) seems to be involved.
The situation might be understood through an analogy, if not pursued too far:
About 25 years ago, my wife (aged 43 at the time) was diagnosed with Type 1 diabetes, subtype brittle (in which the response to insulin is partly unpredictable, causing frequent fluctuations of blood sugar). The result, in effect, is as though the destruction of the capacity to produce insulin is not complete, so that the medical control program of insulin injection is in conflict with the native insulin produced by the pancreas.
The analogy here is to the gradual replacement, in homo sapiens, of the instinctive system of regulating behavior (possessed by all other animals) by a highly complex and diverse culture-based system, occurring over the past couple of million years and probably far from complete at this point. The resulting conflict has been variously represented as a Fall of Man, or a war between Good and Evil, Ego and Id, etc., overlooking the fact that both sides of the conflict originated (and continue) in the evolutionary process. Although violent behavior certainly exists in nature, the aspects of the natural world commonly described as bestial and “inhumane” are far more characteristic of the civilized world: murder, rape, torture, slavery, war, etc., to say nothing of injustice, oppression of the weak, and discrimination of all kinds.
To paraphrase an old joke: “The missing link between the lower animals and civilized man has been discovered: it’s us!”
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My point is that consciousness is not an illusion, nor it is granted by an all-knowing deity. It seems to be nascent to biology. So since biology evolves upward, through increasing levels of complexity, then accepting this sense of being aware and the resulting perceptions and projections as being from an elemental basis would be a useful key in the lock of explaining how and why organisms, including humans, act the ways they do, rather than assuming much of life are automatons.
It would also remove the authority of the father figure deity, which seems to be a significant ideological issue.
ah, you are right, you said that Siri and thermostats understand. Which, of course, still means you are wrong. But in a slightly different way.
“My point is that consciousness is not an illusion, nor it is granted by an all-knowing deity”
That was your point? I would have never guess. You should have said so to begin with. Of course you are still wrong about feelings and bacteria.
That’s not my understanding of understanding. No wonder we were confused.
If this is what ‘understanding’ means a key word look up table (which is what much that passes for AI is) has understanding.
“But it doesn’t “feel” nothing in plants or bacteria (no nervous system), and yet they do it, by other means.”
What other means? This is my question. What drives their actions? I’m not saying it is desire. I agree with you that makes no sense. I am noting that desire seems to be what drives our actions. So what does the same in plants and bacteria?
I do not know the answer to this question. But you are answering it as though you know the answer. Your first answer was “natural selection.” Then Brodix pointed out to you that natural selection is a process by which phenotypes are selected, not something that causes the actions of organisms. So you then answered “survive and procreate” which is an end result not a drive governing the actions of organisms. So what drives their actions?
Now your answer is “by other means” meaning actions in plants are not driven by desires but by “other means.” What other means? Again I am not implying that it is desire. I’m saying what is it then? What are these “other means” you speak of?
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“That was your point? I would have never guess.”
I presume i’ve made my argument then. My problem is that I don’t see any counter argument. You don’t like machine metaphors, nor a designer. What then? Consciousness arose with the bicameral mind?
“What other means? This is my question. What drives their actions?”
There are very good descriptions of these means in books and papers about plant and bacterial physiology and cell genetics. It’s all automatic, made possible by specific interactions of molecules, favored by natural selection. Look for instance at how plants have sex. We have exellent understanding of it, and none of it invokes desires. Desires, incidentally, are part of the means by which animals achieve the same results as plants and bacteria: survival and reproduction.
“My problem is that I don’t see any counter argument. You don’t like machine metaphors, nor a designer. What then? Consciousness arose with the bicameral mind?”
Mutation and atural selection. The standard mechanisms of evolution.
I’ve made my argument and you have made yours. I agree consciousness manifests as a process of exploration/mutation and decision/selection. It’s just not clear to me this process is the motivation as well.
Joel David Hamkins posted this of someone putting three agents (Siri, Alexa and Google Home) together, resulting in “ouroboros”-like self-referencing loops.
You know, machines act autonomically. That part of the metaphor actually partially works for plants, and for animals below a certain threshold of consciousness.
I am not sure I understand the question. Natural selection selects for certain behaviours and processes that achieve certain goals, ie surviving until reproduction or abetting similar organisms to do so. So what drives the organism is the behaviour or process that was selected for. What more explanation is required? That seems to cover it.
We are just the same, except that in our case reasoning, self reflection and creative co operation within a culture were among the behaviours that were selected for.
Neither plants nor bacteria act. People act and do so for various reasons.
Certainly animals and even micro-organisms engage in various movements, and presumably, these are going to be explained, most immediately, by appeal to whatever physical events caused them. But the realm of actions and reasons — as well as all the variety of normative predicates one satisfies by virtue of being the sort of thing that acts for reasons — is one that is occupied exclusively by persons.
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As I understand it evolution does not select for goals like survival, rather gene’s that enhance survival survive. It’s not quite a tautology.
Keep in mind life permeates every possible crevice and niche possible. What drives it to do so?
You observe that you live in a fairly cooperative context, as it suits your survival, but competition and cooperation function as two sides of a larger process. When it is more effective for survival to compete, life competes and when cooperation is more effective, it cooperates. Why does life have this tendency to push every aspect of its environment? Is it because nature abhors a vacuum and life functions like a gas?
Yet gas doesn’t particularly care that when it expands, it becomes more diffuse. When life expands, it will increase its mass to maintain similar density.
There are other aspects as well. To use the steering versus motor analogy, if you decide/select for taking a particular route, your view is the reason you are moving down that road is because you turned onto it. Yet that overlooks the dynamic propelling you, the motor.
Which gets into medium versus message issues.
As in being conscious, versus what we are conscious of. The premise of artificial intelligence is that if a computer can process information as effectively as a person, it qualifies as being as conscious as a person, rather than understanding that processing information is the talent our consciousness does to survive, while assuming other organisms, such as fish, are not conscious, because they only evolved to swim to survive.
By this logic, if fish scientists could program a robot to swim as effectively as a fish, it would logically be as conscious as a fish is.
So your position would be that it is what you are conscious of, that motivates you, rather than then the fact you are conscious and selected what worked best for you.
Which gets to my observation that we are ultimately driven by desire, than the apparent objects of our desire.
One way to consider this might is if you have to deal with problematic obsessive or habitual issues and learned to deal with them by refocusing your tendency to obsess on other things. Necessarily one is driven by the tendency to obsess, rather than what one is obsessed about.
That’s what natural selection means: whatever survives to reproduction, by whatever means, passes its genes on
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“scientists discovered that octopuses, along with some squid and cuttlefish species, routinely edit their RNA (ribonucleic acid) sequences to adapt to their environment.”
Massimo: ” Look for instance at how plants have sex. We have exellent understanding of it, and none of it invokes desires.”
Having been an active participant in plant sex (via field hybridization of lima beans) I can testify that the desire (and the attendant discomfort from squatting in the hot sun) was all mine.
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Daniel: “Neither plants nor bacteria act. People act and do so for various reasons.
Certainly animals and even micro-organisms engage in various movements, and presumably, these are going to be explained, most immediately, by appeal to whatever physical events caused them. But the realm of actions and reasons — as well as all the variety of normative predicates one satisfies by virtue of being the sort of thing that acts for reasons — is one that is occupied exclusively by persons.”
So much of the discussion has focused on motivation; e.g. that animals of all sorts move, with apparent purpose, despite their inability to provide what any child could do, i.e. an explanation of their reasons for moving. It seems that some kind of middle ground is needed, that allows us to refer credibly to a state between agency and passivity, in recognition of the fact that before we came along, creatures of all kinds were living on earth and going about their ways in some sort of coherent fashion for millions of years.
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Machines also don’t emote, and per Dan on substrates and Massimo on embodied cognitiion, we’re learning ever more about embodied emotion. https://news.nationalgeographic.com/2018/03/why-the-brain-body-connection-is-more-important-than-we-think/
A Grand ambition:
“When Science shall have subjected all natural phenomena to the laws of Theoretical Mechanics, when she shall be able to predict the result of every combination as unerringly as Hamilton predicted conical refraction, or Adams revealed to us the existence of Neptune,— that we cannot say. That day may never come, and it is certainly far in the dim future. We may not anticipate it, we may not even call it possible. But none the less are we bound to look to that day, and to “bound to look to that day, and to many things move me to suspect that everything depends upon certain forces, in virtue of which the particles of bodies, through forces not yet understood, are either impelled together so as to cohere in regular figures, or are repelled and recede from one another.” Newton, in Preface to the Principia. (Quoted by Mr W. Spottiswoode, Brit. Assoc. Presidential Address, 1878.)
D’Arcy Wentworth Thompson. On Growth and Form (Kindle Locations 713-716). Kindle Edition.
It’s marvelous what you can find on Kindle! Only 99 cents.
Sir D’Arcy Wentworth Thompson in his classic book On Growth and Form, published in 1917.4
Found in book I’m currently reading:
West, Geoffrey. Scale: The Universal Laws of Growth, Innovation, Sustainability, and the Pace of Life in Organisms, Cities, Economies, and Companies (p. 86). Penguin Publishing Group. Kindle Edition.
Which I think may be relevant to Laland’s work.
“that animals of all sorts move, with apparent purpose, despite their inability to provide what any child could do, i.e. an explanation of their reasons for moving. It seems that some kind of middle ground is needed, that allows us to refer credibly to a state between agency and passivity, in recognition of the fact that before we came along, creatures of all kinds were living on earth and going about their ways in some sort of coherent fashion for millions of years.”
That ability is also referred to as rationalization, where the reasons tend to be a mashup of conflicting impulses and assumptions. This habit tends even to the most august bodies in society.
We like clear definitions, between concepts, levels of value, groups, etc, but the lines just get fuzzy when we look closely.
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In computer science, the code of agents with Emotions-Beliefs-Desires-Intentions (EBDI) is considered to be imitational, and arguable that consciousness (C) is needed for real EBDI.
 EBDI: An Architecture for Emotional Agents