Why machine-information metaphors are bad for science education, part I: biological machines and intelligent design

bacterial flagellum

bacterial flagellum, as often represented in biology education

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. Predictably, modern proponents of Intelligent Design so-called theory, the latest incarnation 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.

In reality, 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.

My friend and collaborator Maarten Boudry and I have written an article several years ago in which 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of the living organism = machine analogy with the modern ID movement, and illustrate how the use of misleading and outdated metaphors in science can play into the hands of pseudoscientists. We argued that dropping the blueprint and similar metaphors will improve both the science of biology and its understanding by the general public.

We have discussed this topic twice in the last couple of years, once on the occasion of another paper with Maarten, on why machine metaphors in biology are misleading; more recently because of a paper I wrote about genes as blueprints; the current entry completes the trilogy, so to speak. In part I, here, I will present what Maarten and I had to say about the origin of machine-information metaphors in biology, as well as its questionable use in science education. In part II, next week, I’ll talk about the search for new and better metaphors in science and science education. Interested readers are referred to the original paper for references, as well as for a discussion of the misuse of machine-information metaphors in actual biological research (i.e., not just for educational purposes).

When delving into unknown territory, scientists have often naturally relied on their experiences in more familiar domains to make sense of what they encounter. In the early days of the scientific revolution, mechanical metaphors proved to be a powerful instrument to get a grip on new discoveries about the living world and the universe at large, and we can trace back the emergence of machine metaphors at least to the Middle Ages, when new achievements of technology had a profound cultural influence and captured the collective imagination. Against this background of technological innovation, it is not surprising that the pioneers of anatomy and physiology relied on the metaphor of the animal body as a complicated piece of machinery to make sense of their discoveries. The mechanical language provided a richness of meaning and allowed them to structure the new phenomena in terms of familiar experiences. For example, the image of the human heart as a pump with intricate mechanical components played an important role in William Harvey’s discoveries about blood circulation.

In the course of the 17th century, a new philosophy of nature became prominent that developed a conception of the universe in purely mechanical terms. According to this mechanical philosophy, which was developed by thinkers like Rene` Descartes, Pierre Gassendi and Robert Boyle, the phenomena of nature can be understood purely in terms of mechanical interactions of inert matter. This mechanization of nature proved an important driving force behind the Scientific Revolution, and at the end of the 17th century culminated in Newton’s theory of motion. Newton’s description of planetary orbits following the fixed laws of gravity conveyed an image of a clockwork universe set in motion by an intelligent First Cause. In fact, that was exactly how Newton conceived the universe and its relation to the Creator. For Newton and many of his contemporaries, the importance of the mechanical conception of nature was greater than the mere term ‘metaphor’ would suggest, as the development of mechanistic philosophy was itself largely inspired by religious motivations; indeed, the very employment of machine metaphors invited theological speculation.

In the second part of the 17th century, the mechanical pictures of living organisms and of the cosmos at large converged into an intellectual tradition where theology and science were intimately intertwined: natural theology. The most famous representative of this tradition was William Paley, whose work Natural Theology, of Evidence of Existence and Attributes of the Deity, Collected from the Appearances of Nature (1802) made a deep impression on the young Charles Darwin. As the title of the book makes clear, Paley and the natural theologians conceived of Nature as a complicated machinery of intricate wheels within wheels, in which every organism has its proper place and is adapted to its environment. According to Paley, the contrivance and usefulness of parts exhibited by living organisms attests to the intelligence and providence of a benevolent Creator. This so-called ‘design argument’ already had a long intellectual pedigree, dating back to Plato, Cicero and Thomas Aquinas, but its most famous formulation is found in the first chapter of Natural Theology, in which Paley famously relies on the analogy between living organisms and a pocket watch to support his design inference.

While Darwin was the one who gave the most decisive blow to the design argument by suggesting a natural explanation for adaptive complexity in the living world, many philosophers would agree that David Hume foreshadowed its demise, by exposing several problems with the central analogy. In his Dialogues Concerning Natural Religion (1779), which actually predates Paley’s magnum opus by more than 50 years, we find a discussion of the design argument among Philo, the skeptical character that voices Hume’s ideas, Demea, the orthodox religious believer, and Cleanthes, the advocate of natural theology.

After Cleanthes has set out the design argument in terms foreshadowing Paley’s analogy of the watch, Philo objects that it is dangerous to derive conclusions about the whole of the universe on the basis of a spurious analogy with one of its parts. Given that our experience with design is limited to human artifacts only, we have to proceed with great caution, and it would be presumptuous to take so minute and select a principle as the human mind as the model for the origin of the whole universe. Hume realized that, at least in some cases, appearances of intelligent design can be deceptive.

In contemplating that ‘‘many worlds might have been botched and bungled, throughout an eternity, ere this system was struck out’’, Hume even comes close to Darwin’s crucial insight about the power of natural selection. Although Hume does not deny that we can discern similarities between nature and human artifacts, he warns us that the analogy is also defective in several respects. And if the effects are not sufficiently similar, conclusions about similar causes are premature. To illustrate this, Philo proposes another possible cosmogony on the basis of the analogy between the world and an animal:

“A continual circulation of matter in [the universe] produces no disorder; a continual waste in every part is incessantly repaired: The closest sympathy is perceived throughout the entire system: And each part or member, in performing its proper offices, operates both to its own preservation and to that of the whole. The world, therefore, I infer, is an animal.” (Hume 1779, p. 39)

In The Origin of Species, Charles Darwin (1859) finally proposed a natural explanation for the phenomenon that inspired Paley but failed to convince Hume. Although the design argument is still of interest to philosophers and historians of science, it has been widely discarded in the scientific community. However, the analogy on which Paley based his inference seems to be alive and well, not only in the minds of creationists and ID proponents, but also in the writings of science popularizers and educators. Many scientists have actually argued that Paley at least offered an incisive formulation of the problem as there is indeed a hard-to-shake intuition of contrivance and intelligent design in nature. As one of the most ardent defenders and popularizers of evolutionary theory, Richard Dawkins, put it, ‘‘Biology is the study of complicated things that give the appearance of having been designed for a purpose.” Adaptive complexity, then, is still regarded as something that requires a special explanation.

In textbooks, science educators have presented the comparison of living organisms and man-made machines not just as a superficial analogy, but carrying it out to a considerable level of detail. For example, the cell has been described as a miniature factory, complete with assembly lines, messengers, transport vehicles, etc. Consider the following quote from Bruce Alberts, molecular biologist, and former president of the National Academy of Sciences:

“The entire cell can be viewed as a factory that contains an elaborate network of interlocking assembly lines, each of which is composed of a set of large protein machines. … Why do we call the large protein assemblies that underlie cell function protein machines? Precisely because, like machines invented by humans to deal efficiently with the macroscopic world, these protein assemblies contain highly coordinated moving parts. Given the ubiquity of protein machines in biology, we should be seriously attempting a comparative analysis of all of the known machines, with the aim of classifying them into types and deriving some general principles for future analyses. Some of the methodologies that have been derived by the engineers who analyze the machines of our common experience are likely to be relevant.” (Alberts 1998, p. 291)

Creationists and their modern heirs of the Intelligent Design movement have been eager to exploit mechanical metaphors for their own purposes. For example, Bruce Alberts’ description of the living cell as a factory has been approvingly quoted by both Michael Behe and William Dembski, two leading figures in the ID movement. For ID proponents, of course, these are not metaphors at all, but literal descriptions of the living world, arching back to Newton’s conception of the Universe as a clock-like device made by the Creator. The very fact that scientists rely on mechanical analogies to make sense of living systems, while disclaiming any literal interpretation, strengthens creationists in their misconception that scientists are ”blinded” by a naturalistic prejudice. In the creationist textbook Of Pandas and People, which has been proposed by ID advocates as an alternative to standard biology textbooks in high school, we read that ‘‘Intelligent design […] locates the origin of new organisms in an immaterial cause: in a blueprint, a plan, a pattern, devised by an intelligent agent’’ (Davis et al. 1993, p. 14).

The analogy between living organisms and man-made machines has proven a persuasive rhetorical tool of the ID movement. In fact, for all the technical lingo and mathematical “demonstrations,” in much of their public presentations it is clear that ID theorists actually expect the analogies to do the argumentative work for them. In Darwin’s Black Box, Behe takes Alberts’ machine analogy to its extreme, describing the living cell as a complicated factory containing cargo-delivery systems, scanner machines, transportation systems and a library full of blueprints. Here is a typical instance of Behe’s reasoning:

“In the main area [cytoplasm] are many machines and machine parts; nuts, bolts, and wires float freely about. In this section reside many copies of what are called master machines [ribosomes], whose job it is to make other machines. They do this by reading the punch holes in a blueprint [DNA], grabbing nuts, bolts, and other parts that are floating by, and mechanically assembling the machine piece by piece.” (Behe 2006, pp. 104–5)

Behe’s favorite model of biochemical systems is a mechanical mousetrap, the familiar variant consisting of a wooden platform, a metal hammer, a spring etc. According to Behe, if any one of these components is missing, the mousetrap is no longer able to catch mice. He has termed this interlocking of parts ‘‘irreducible complexity’’ and thinks it characterizes typical biochemical systems. n other words, the mousetrap is to Behe what the well-designed pocket watch was for Paley. But whereas Paley can be excused on the grounds of the state of scientific knowledge in the 18th century, for Behe the situation is a little different. Modern biochemistry, nota bene Behe’s own discipline, has revealed that biochemical systems are not like mechanical artifacts at all. Moreover, even biological systems that are irreducibly complex under Behe’s definition pose no problem for evolution by natural selection, as has been in detail by people like cell biologist Ken Miller.

ID proponents have buttressed their analogies between living systems and mechanical contraptions with a lot of visual rhetoric as well. The flagellum of the bacterium E. coli, the hallmark of the ID movement, has been represented as a full-fledged outboard rotary motor, with a stator, drive shaft, fuel supply, etc.. It features on the cover of Dembski’s book No Free Lunch, and has been used numerous times in presentations and online articles. The idea seems to be that if it looks designed, it has to be designed. But as Mark Perakh has documented in a paper published in 2008, ID supporters invariably use idealized and heavily stylized representations of the flagellum, in order to make it more resemble a man-made contraption. Another striking example of this visual rhetoric is a video by Discovery Institute president Stephen C. Meyer, which presents a computer-simulated — and again heavily stylized — journey inside the cell, and describes the biochemical processes in terms of ‘‘digital characters in a machine code,’’ ‘‘information-recognition devices,’’ and ‘‘mechanical assembly lines.’’ Meyer commented that evolutionists will have a hard time now dissuading the public from the fact that ‘‘the evidence for design literally unfolds before them.’’

Of course, the mere observation that creationists have seized on machine metaphors in biology does not suffice to demonstrate that these metaphors do not make scientific sense. However, the fact that they tend to do so systematically, using full-length quotes from respectable scientists, should make us weary of the possible dangers of misleading metaphors. If the rhetoric of the ID movement is demonstrably based on these mechanical analogies, it can be instructive to reexamine their scientific merits. In the paper, Maarten and I argue that the machine-information analogy has indeed influenced the way scientists themselves think about biological structure, function, and evolution. By analyzing the consequences of and reactions to this analogy in actual biological research, we show that its scientific merits are very weak, and that its place in modern biology has become questionable. What then? Stay tuned for part II, on the search for new and better metaphors…

122 thoughts on “Why machine-information metaphors are bad for science education, part I: biological machines and intelligent design

  1. Coel

    Robin,

    If so then he is plain wrong. If the ‘program’ concept is applicable at all then the DNA is the storage for the program.

    As per DM, I see nothing wrong with the idea that evolution “programs” the genes and then the genes “program” (= provide instructions to) the brain.

    I think you’re taking a too narrow interpretation of quite a few terms (and narrow vs broad usage is not quite the same as literal vs metaphorical).

    Dawkins point in the article is that the similarities between living things and highly engineered complex designed equipment is a killing blow to mystical and obscurantist views.

    No, not really, he’s saying that the fact that we can now explain life (and its machine-like aspects) has dealt the killing blow to mystical and obscurantist views (specifically he says that Crick and Watson’s explanation of how DNA works and how replication works dealt the “final” blow; presumably Darwin landed the first blows).

    Socratic,

    I think Dennett-vs-Gould dialogue of the 1980s also reflects why the “machine” metaphor is wrong. We don’t talk about spandrels, we don’t talk about skyhooks vs cranes, etc. when we talk about actual machines.

    Except that in the “Spandrels” paper Gould was comparing living entities to human-designed entities, and comparing developmental constraints to engineering constraints. Indeed the very term “spandrels” comes from human engineering.

    Massimo,

    the oxford definition makes it clear why organisms are not machines: they are not made of clearly distinct parts working like parts do in a machine.

    I’d have thought one could regard the elbow joint as sufficiently distinct from, say, the kidney or the lung in terms of function.

    Liked by 1 person

  2. brodix

    Robin,

    ” A device running a program can write a program. ”

    They go opposite directions.

    The device processes the program and then is free to do other programs, thus going from prior to succeeding ones. Past to future. Basically it represents the present state.

    Meanwhile the program goes from potential to conclusion, future to past.

    Think of a factory. The product goes start to finish, future to past. While the process consumes material and expels products, past to future.
    A movie projector and film. The projector light goes from prior to succeeding frames, as the frames are projected and recede into the past.

    Our individual lives go from birth to death, being in the future to in the past, while the species is shedding old generations and moving onto new ones.

    Then you have feedback, as new generations adapt, new models of products are adjusted, etc.

    “it is part of a whole system.”

    Liked by 1 person

  3. Philip Thrift

    Robin,

    “But of course programs can’t write programs. They can’t do anything. They just sit there. ”

    Try genetic programming, “whereby [a population of] computer programs are encoded as a set of [chromosomes] that are then modified (evolved) using an evolutionary algorithm [with mutation, crossover, etc.].” [Wikipedia]
    (If you want true randomness, use a hardware QRNG.)

    Liked by 1 person

  4. Massimo Post author

    Coel,

    “I’d have thought one could regard the elbow joint as sufficiently distinct from, say, the kidney or the lung in terms of function.”

    Sure. Except they are both parts of integrated systems whose boundaries are totally fuzzy. And it gets much more fuzzy at the cellular and molecular level, where the machine metaphor is particularly popular.

    Liked by 1 person

  5. Robin Herbert

    Philip

    Try genetic programming, “whereby [a population of] computer programs are encoded as a set of [chromosomes] that are then modified (evolved) using an evolutionary algorithm [with mutation, crossover, etc.].” [Wikipedia]
    (If you want true randomness, use a hardware QRNG.)

    Yes, I have tried it a number of ways. I have described one of these a couple of times here before. I have a programming language that will always interpret a string as a set of instructions, whatever the string is. I generate, say 50,000 random strings and run each of these as a program, taking the output and using a distance function to match it to a target shape, say a rectangle.

    The 100 or so programs which have drawn a shape closest to a rectangle are written over the 100 that drew figures least like a shape, and some of these are mutated (replacement/insertion/deletion), then I start again.

    The point of the exercise is that unlike “methinks it is like a weasel” type algorithms, it is given a target, but not told how to reach the target, there being a number of ways a program can draw a rectangle.

    It does work, after a fashion, and ends up with programs that draw something like a rectangle, so I was quite happy with the exercise. I am not sure how it would handle any more complex shape, but maybe if I added a bigger population and gave it more time.

    I find the resulting programs make good use of loops, even nested loops, but seem to make little functional use of “if..then” logic.

    So I have no problem with the idea that a run of a program can write a program, but in the case of my little program, each little string of binary data was not in itself they key part of the exercise, it is the process as a whole that was getting the result.

    Also, if I were to try to make this system evolve a program that could not only run another program, but also make copies of itself, then forget it. I don’t think even if I were to run this on the most powerful computer in the world with a vast amount of storage for a huge population and ran it for years or even decades that it would do that.

    Which is why I think that calling this process “programming” is barking up the wrong tree. Self organisation perhaps, I don’t know. Smarter people than me will work that out.

    Liked by 1 person

  6. Robin Herbert

    Coel,

    I think you’re taking a too narrow interpretation of quite a few terms (and narrow vs broad usage is not quite the same as literal vs metaphorical).

    I think I am allowing a pretty wide usage. But programming is the process of creating a program.

    I am not taking a too narrow interpretation of the term “programmer” by saying that the .cpp file on a disk is not a programmer. The programmer is whoever or what ever authored that file.

    The .cpp file was DM’s analogy, and calling a gene a programmer is equivalent to calling that .cpp file a programmer.

    And, as I pointed out, if I write a program to create a neural network, then it would be nonsensical to say that my executable file programmed the neural network. It would even be nonsensical to say that the computer, running my executable programmed the neural network. I programmed the neural network, what the computer did with the executable was merely implement my instructions.

    So if anything can be said to have “programmed” the brain then it is whatever “programmed” the genes in the first place.

    But, as I say, it is ever so much clearer and simpler to describe what is actually happening.

    Liked by 1 person

  7. ejwinner

    The problem with metaphors is that we can forget that they are metaphors. They then shape the way we see the world and respond to it. Eventually we build whole metaphysics founded on nothing more than a play of language.

    The metaphysics found dogmatism, and ignorance results.

    Liked by 6 people

  8. Coel

    Hi Robin,

    I think I am allowing a pretty wide usage. But programming is the process of creating a program.

    The OED allows a little more latitude:

    Programme (verb): “Provide (a computer or other machine) with coded instructions for the automatic performance of a task”.

    “Provide” is more general than “create”. And suppose there were three pre-written programs for a device, that did X, Y and Z respectively. I could fairly say that “I programmed it to do Y” even if all I’d done was choose one of the three and stick in a memory stick. (And may a programmer use pre-existing subroutines, libraries and high-level languages, or does he have to do everything from scratch in assembler?)

    But, even supposing you were right, the “program” in the brain is going to be sufficiently different and in a sufficiently different format (and also involving development and environmental inputs) that it could fairly be said to be “created” rather than merely copied from whatever is in the DNA.

    At this point I’d suspect you might be the adopting the usual philosophical stance (that I’ve come to know from the blog) that it doesn’t count as “programming” or whatever unless accompanied by a conscious self-reflection on the process, such that only a sentient being can “programme”. But you’ve already accepted that evolution can “programme” DNA so perhaps not.

    Anyhow, overall I think you’re being over-picky about Dawkins’s language, which is actually quite reasonable, if read with a modicum of sympathy.

    Liked by 1 person

  9. saphsin

    It looks to me that the demands of justifications are backwards, as if we have to justify why not to associate biology with machines rather than it being the other way around.

    Liked by 3 people

  10. Disagreeable Me (@Disagreeable_I)

    Hi Robin,

    No, it is more like saying that a memory chip, the material of a hard disk or SSD is just storage

    I agree with you that saying that “the hard disk programs the computer to beep” would be a weird — albeit perhaps acceptable — usage. But clearly anyone who says “the DNA programs” is talking about the pattern in the DNA. They are not talking about the substance.

    I’d say if you’re insisting that programs can’t do anything, and that only running programs do anything, then you’re again maybe correct but only in a needlessly pedantic sense. Programmers routinely talk about programs doing things. “This program finds the greatest common divisor of two numbers” and so on. So, again, whatever about Massimo’s argument, I don’t find your case that Dawkins is hopelessly muddled about computers to be convincing.

    The genes are not programmers.

    I think we can all agree on that.

    To me at least, the statement “X programs Y to do Z” does not imply that “X is a programmer”, because to me “programmer” means a person who consciously creates programs, and not merely some process that causes a program to arise. This is somewhat the inverse of the case of the modern usage of “computer”, in that a person who computes is usually no longer called a computer — this term now specifically connotes a non-person. So, to me at least, a computer program that (when running!) writes further computer programs is not a programmer (well, maybe it could be if it was intelligent enough for me to deem it a person, but outside of sci-fi scenarios my statement holds).

    Liked by 2 people

  11. saphsin

    “Is associating biology with DSLs (domain-specific languages) the same as associating it with machines?”

    No, because DSLs are not machines. So why would the level of accuracy of their metaphors both be the same towards biology? But if you’re referring to the type of behavior of insisting to make it fit to describe biology, then yes my previous comment would apply.

    Liked by 1 person

  12. Robin Herbert

    Coel

    At this point I’d suspect you might be the adopting the usual philosophical stance (that I’ve come to know from the blog) that it doesn’t count as “programming” or whatever unless accompanied by a conscious self-reflection on the process, such that only a sentient being can “programme”.

    You would suspect this even though it is the opposite of everything I have just been saying?

    I am curious to know why you always reach the conclusion that I mean the opposite of what I say.

    I have said that the landscape and environment of the organism might be said to be programming the organism. No, I don’t think that landscapes are conscious.

    I have said that executed programs can program.

    But in order to be programming, the process has to be choosing the instructions on some basis. A routine that copies an executable is not programming. If I copy out a program from a book then I am not programming.

    But if the executed program generates a program that doesn’t exist yet, to achieve some result then that can be called programming. For example the program I have just described could be said to be programming when it is running. As I said, the total system of an organism undergoing evolution in an environment could be called programming.

    But the cell reading and expressing the instructions in DNA is not programming, any more than a CPU reading and carrying out instructions is programming.

    The patterns in DNA are somewhat analogous to the files containing a program (whether written by a human or by some other process)

    If we have a fear of snakes it is not the patterns in DNA that chose those instructions go to our brains, it was the environment in which we evolved over deep time that determined that the instructions for fearing snakes would continue and the set of instructions which lacked this fear would be deleted. So if there is programming here, that is where the programming is happening. Merely implementing these instructions is not programming.

    What I suspect is that you are too emotionally attached to the “gene as protagonist” view that you are unwilling to address what I am actually saying here

    Liked by 1 person

  13. Robin Herbert

    DM,

    I think we can all agree on that.

    Surely that is just what we are disagreeing about. The question is, “Is DNA doing something which could be described as “programming” allowing any latitude of definition that does not render the word meaningless?”

    As I asked before, do you consider that your .cpp file “programs” the computer? Do you consider that the executable for that file programs the computer? Do you think that the executable loaded and being executed by the CPU could be considered programming the computer.

    If you can answer those then I can get a clearer idea of what you mean by the term “program”, because none of those things are what I call “programming”.

    Liked by 1 person

  14. synred

    I always considered writing code to ‘programming’. Loading it into a computer and executing it is ‘running’ the program. So?

    Data and code are both loaded in the same kind of memory. They are both bits. What you do with them is what determines what’s code and what’s data.

    On PDP -10 we used to patch the code, by putting code into common blocks (meant for data) and jumping to it from the code section to execute the patch. That way you could test your bug fix before recompiling and re-loading which could be quite slow.

    Liked by 1 person

  15. brodix

    Robin,

    Is it an issue of tenses?

    That “programmed” is past tense, programming” is present tense and “programmable” future tense?

    While “program” is a set of instructions?

    So the fact monkeys do have a fear of snakes is programmed, i.e. past tense, the process of them evolving that fear is programming/present tense and the potential for their genes to evolve a fear of snakes is programmable/future tense?

    Liked by 1 person

  16. Disagreeable Me (@Disagreeable_I)

    Hi Robin,

    Surely that is just what we are disagreeing about. The question is, “Is DNA doing something which could be described as “programming” allowing any latitude of definition that does not render the word meaningless?”

    That’s a different question.

    To the question you posed just now, I would say “Yes, DNA (or the pattern in it) is doing something which could be described as programming without demonstrating cluelessness about computer science — albeit whether this is the best way to describe what it is doing is debatable, per Massimo”.

    But that’s not the same as saying that DNA is well described as a programmer. A programmer is a person.

    As I asked before, do you consider that your .cpp file “programs” the computer?

    No, and no to your other questions. But that’s not the analogy. The analogy would be that a meta-programming program held in a .cpp file (analogous to the pattern in the DNA) programs some other abstract entity at runtime.

    Here’s the analogy as I see it

    The genetic material in the nucleus of a cell: .cpp file
    DNA pattern: meta-programming program in a .cpp file
    Brain’s neural network: output program generated (i.e. programmed) by a meta-programming program in a .cpp file

    The computer itself doesn’t really enter into the analogy. The analogy is to programs and what programs do, not to the computer that runs them. Though I guess you could say that the brain is analogous to the computer that runs the output program produced by the meta-programming program.

    Ack, this is too much of a tangent, sorry Massimo. The only point I wanted to make is that there are programmers who would not agree with you that Dawkins is confused about programming. Further discussion is probably not warranted, so I intend not to respond.

    Liked by 1 person

  17. Robin Herbert

    Coel,

    The OED allows a little more latitude:

    Programme (verb): “Provide (a computer or other machine) with coded instructions for the automatic performance of a task”.

    “Provide” is more general than “create”. And suppose there were three pre-written programs for a device, that did X, Y and Z respectively. I could fairly say that “I programmed it to do Y” even if all I’d done was choose one of the three and stick in a memory stick.

    And if a sysadmin working from home was busy at the other end of the room and said to their two year old “could you please press the yellow button on the screen that says “3”?” and the two year old presses that button on the screen and the result of pressing it loads one of X,Y, and Z from a memory stick on the computer, then is the two year old programming the computer in the sense you mean?

    That is quite a good deal of latitude.

    Again, this demonstrates why a straightforward description of what is happening is a lot better than this metaphorical language because it can mean vastly different things to different people.

    Liked by 1 person

  18. brodix

    Also program as noun(set of instructions) and verb, as per Coel’s use of it. Logically present tense, thus conflating program with programming?

    Liked by 1 person

  19. Robin Herbert

    I know how this goes. You say “genes don’t program us, they are more like the program”

    Then someone says that, if you allow a lot of latitude in the definition of “program” then it might be technically true from a certain point of view that genes might be said to “program” us.

    So you say, ‘well, OK, I suppose so, although it is nothing like what we normally mean by program’

    So then we get to saying that genes “created us, body and mind; and their preservation is the ultimate rationale for our existence.”

    Nah, I am not taking the bait. Others can use the terminology they wish, but genes don’t program us in any meaningful way and to say so has no explanatory merit, in fact it is downright misleading to say so and seems to be a way of getting to the “gene-as-actor” view, which makes no sense to me.

    Liked by 2 people

  20. Robin Herbert

    DM

    “Ack, this is too much of a tangent, ”

    On the contrary, I think that all the useless discussion this has generated is a perfect illustration of what is wrong with metaphor and analogy.

    Saying “genes program us” doesn’t provide any shortcut to explanation.

    Someone could have given a reasonable technical recount of the plain facts about the process using a tenth of the words we have just expended.

    Liked by 1 person

  21. Disagreeable Me (@Disagreeable_I)

    Someone could have given a reasonable technical recount of the plain facts about the process using a tenth of the words we have just expended.

    I’m not giving a strong view on whether the analogy is a good idea or not because that is an empirical question dependent on how typical people tend to think. I personally find it useful and intuitive, such that I immediately understand what Dawkins is trying to communicate. Your mileage obviously varies.

    Liked by 2 people

  22. synred

    Yes, DNA (or the pattern in it) is doing something which could be described as programming

    I wouldn’t say that. The DNA is much closer to data specifying order of amino acids in a protein. The Ribsome interprets the DNA ans spits out the protein. The Ripsome is the same each time, but the DNA/RNA input varies (data) which turn varies the output. The analogy with data processing is pretty strong though presumably as usual fuzzy and imperfect.

    Liked by 1 person

  23. synred

    I once had a bug in a program that illustrates the fuzziness that can occur between data and program. In this bug I wrote out side the boundaries of a common block. The location I wrote to happened to be a the return from a subroutine. The data written there happened to correspond to a no-op (do nothing instruction). The net effect was that the subroutine returned to it start and was re-executed resulting in an infinite loop.

    No matter how long I stared at the code I couldn’t find a loop — indeed there was not one there.

    The PDP-10 I was using had very power full debugger called DDT and I could step through the program and watch what was happening. I found where the correct code had been overwritten and traced it back to another subroutine. The overwrite bug was no where near where it manifest itself has an infinite loop.

    It was almost a kind of mutation.

    So it seems to me DNA (in genes) is mostly data, but can have code like aspects too. The separation we usually maintain in computing need not be complete.

    Liked by 1 person

  24. Coel

    Robin,

    Again, this demonstrates why a straightforward description of what is happening is a lot better than this metaphorical language because it can mean vastly different things to different people.

    That doesn’t follow, since there can be just as much disagreement about what the “straightforward” language means. Indeed one of the points of metaphors and analogies is to clarify what the straightforward language means by linking it to other stuff. Afterall, knowledge of “straightforward” language is not innate, we have to come to understandings of what others mean by it.

    And, to illustrate this point, to me talking about “machines” and “programs” is straightforward language! Biological entities are machines that have been programmed by the genes to act in ways that then propagate the genes. That’s not a metaphor, it’s literal. These are the appropriate terms to use when thinking from a functional or information perspective, and such perspectives are useful and valid.

    And so far I’m not convinced that such talk is at all misleading or bad for science education. (Though one particular metaphor, “blueprints”, is indeed bad, but then everyone accepts that.)

    Liked by 1 person

Comments are closed.