The Linguistics of the Life Sciences: From Mechanical Analogies to Teleological Analogies—Preface to the Recommended Chinese Translation of The Book of Life
Philip Ball: *The Book of Life*, translated by Wang Qiaoqi, CITIC Publishing Group, 2025
I was honored to write the recommendation preface for this book. I actually did not read the main text very closely; I mainly wrote from the general perspective of philosophy of science. What I’m posting here is my original draft; the published version may have been revised to some extent.
Science and Analogy
The genome is the “blueprint” of life, the “instruction manual” of life, and life science deciphers the “code” of life through genetic technology… These are all familiar formulas to us. But Philip Ball’s *The Book of Life* is precisely a critique of these “analogies.”
Besides big analogies like “blueprint” and “code,” which are often used in public outreach, a variety of analogical expressions are also frequently used in communication among life scientists themselves—for example, “cell factory,” “biological machine,” “neural communication,” and so on. As Ball puts it, reliance on analogy—“this phenomenon exists in all scientific fields (indeed, in all language and even in all thought), but biology perhaps needs metaphor more than other disciplines precisely because biological principles seem hard to grasp and explain.” (p. 009)
Science includes not only the calculation of all kinds of mathematical symbols, but also the question of how to understand those symbols and formulas. At the level of calculation, we can strive for precision, but at the level of understanding, we inevitably use analogies.
Physics is no exception. For example, quantum mechanics began with Planck’s equation, which precisely predicted various phenomena of black-body radiation, but its physical meaning still had to be understood. In the end, Planck interpreted one symbol in the equation by means of “quanta,” that is, the smallest units in which energy exists. Yet once the equation was made sense of, the introduction of quanta created a series of even stranger problems of understanding: for example, an electron is both a particle and a wave (wave-particle duality); a particle is here and there at the same time (the double-slit interference experiment); a cat is both dead and alive (Schrödinger’s cat); and so on.
The Copenhagen school, represented by Bohr, gave the standard interpretation of quantum mechanics, but what exactly is the Copenhagen interpretation saying? In fact, the most crucial point is that it emphasizes the “limitedness of analogy.”
Bohr said: “What do we human beings fundamentally depend on? … We depend on our words. … The idea that the task of physics is to discover what nature is like is wrong. Physics is concerned with what we can say about nature.”[1] Heisenberg likewise said: “Whether people can talk about atoms themselves is at once a physical question and a linguistic question.”[2] The point of the Copenhagen interpretation is precisely to destroy the “illusion” of classical physics, namely, the belief “that we can describe some part of the world without involving ourselves at all.”[3]
In other words, the paradox that an electron is both a particle and a wave is not a problem with the electron or with Heisenberg’s formula, but with our analogy—after all, we simply should not use concepts like “particle” or “wave” to imagine what fundamental particles look like. But the problem is that all our familiar concepts come from the experience of the macroscopic everyday world, so we cannot find the proper concepts to help us understand the microscopic quantum world.
As far as scientific formulas are concerned, changing particles and waves into buns and porridge, or Newtonian mechanics into “riding-a-horse love science,” is actually irrelevant to the main point; they are just labels. But for poor human beings, that is a bit too stimulating. In order to protect our brains from becoming too chaotic, we still use concepts such as particles and waves when discussing physics, even though these concepts are themselves more or less a bit chaotic too.
Physics is like this, and biology of course is no exception: we are forced to use analogy, but at the same time we must be wary of the misunderstandings those analogies may cause; moreover, we can also do a certain kind of “linguistic” work, examining and updating these analogical usages. That is the theme of *The Book of Life*.
Things Are Not That Simple
From the example of quantum mechanics, we can see that even if scientific formulas and measurements are accurate, we still cannot guarantee that our analogical understanding of those formulas is accurate; we still need to carry out reflection at the “linguistic” level. And in the life sciences, the problem is even more acute, because the life sciences are, to a large extent, not “exact sciences”; the explanations and predictions they provide are not always expressed through mathematical formulas, and more often than not their theories and predictions themselves are written in ambiguous, equivocal analogical language. So when we use inappropriate analogies, they not only affect our understanding of the life sciences, but may also directly affect the concrete practice of life science and biotechnology.
The first chapter of this book begins by taking medical practice during the COVID-19 pandemic as an example. Faced with the pandemic, people urgently needed scientific responses and guidance from biology and medicine. But there is a gap between ideal and reality: we found that the judgments offered by the life sciences were not always timely and effective; real situations are always full of uncertainty and uncontrollability.
The mainstream analogical model in the life sciences is reductionist and mechanistic. This analogy gives rise to a habitual mindset, one that always tends to cut things into small components, then determine the “function” of each part one by one, depict a clear “blueprint” of how each part is organized, and thereby control the operation of the whole “machine.”
This simplified and deterministic picture repeatedly runs into obstacles in reality. One reason, of course, is that the life sciences are still waiting to develop further; but on the other hand, perhaps we have simply gotten the direction of development of the life sciences wrong. An unyielding pursuit of a world picture based on reductionism and determinism may well lead the life sciences into a dead end,
Science is always seeking truth, but since Socrates, “to know that one does not know” has always been part of the scientific spirit. We must acknowledge the limits of human beings and revere the complexity of nature. After reflecting on erroneous analogical language, the life sciences may not necessarily be able to give more precise assertions about pandemics and other complex realities, but at least this can prevent people from becoming too arrogant and thus making many bad decisions.
It is not only in the face of emergencies like a pandemic that this matters. The development of the life sciences, especially genetic engineering, has long since affected every aspect of human society: personal birth, aging, illness, and death; how agriculture should develop; how cities should be planned; how laws should be formulated. The life sciences play a crucial role in many social issues. For example, when genetic engineering can modify genes to prevent newborns from inheriting disease, should embryo gene editing be permitted? Or even should gene editing be mandatory, on the grounds that deliberately giving birth to a defective baby is inhumane? What about using it to improve intellectual disabilities or even enhance intelligence? In dealing with these questions, we need to bring in ethics and law, but even more we need to properly understand the connotation and boundaries of biological science: what exactly do genes mean for a person? What exactly can gene editing accomplish? What exactly counts as a “defect” for a living organism?
The author believes that treating genes with a reductionist, mechanistic, and deterministic attitude will have serious consequences: “This idea itself is not as harmful as eugenics, but if one is not careful, it is only one step away from believing in eugenics, and it suffers from the same defects.” (p. 035)
The reductionist view tends to oversimplify many problems, and in the end these debates seem to be reduced to a stark either-or conflict between progressives and conservatives. It seems that either we must embrace new technology at all costs, or we can only become stubborn “metaphysics ghosts” or defenders of religious theology. But both of these attitudes are equally fanatical and irrational.
This book calls for a more “scientific” attitude toward understanding science, and the first step is to be alert to the abuse of reductionism and to acknowledge the complexity of life. “One answer to the question of ‘how life works’ is: it’s complicated!” (p. 295)
By the way, this also makes the book not so easy to read. Usually, the hallmark of a good popular science book is that it simplifies complexity, expressing complex scientific principles in simple, accessible language. But this book goes in the opposite direction, because its very aim is to break the public’s simplified understanding of life science and genetic engineering and to reveal the complexity of life. So readers who want to quickly grasp the essentials will probably end up completely baffled, because after explaining each piece of scientific knowledge, the author does not give you the feeling of “Aha, so that’s how it is!” but keeps telling you: “But things are not that simple…”
Alongside the scientific knowledge he introduces, the author incorporates a great deal of history of science and philosophy of science. The history he traces is not a presentation of a clear line of knowledge construction; rather, it focuses on showing the controversies encountered by various new discoveries. Many times, stubborn prejudice has hindered the updating of knowledge, and many questions remain unresolved to this day.
Fortunately, the author has put considerable effort into the “art of analogy.” While reminding readers not to take any analogy in a rigid way, he uses richer analogical language to make many complex ideas vivid and concrete, thereby rescuing the book’s readability.
Two Kinds of Analogical Language
Yes, the author does not oppose analogical language, and does not even completely oppose mechanistic language; these languages are, to a greater or lesser extent, effective. What he opposes is the unreflective adoption of specific kinds of analogical language.
Many people, deliberately or not, adopt one kind of analogy—namely the analogical language of reductionism, mechanism, and determinism, such as life as machine, “instruction manual,” “code,” and so on—while rejecting another kind of analogy, such as teleological, anthropomorphic, or value-laden analogical language. For example, speaking of the purpose of cells, the meaning of life, or the “cognition” of single-celled organisms. For the same analogical language, the former terms are regarded as scientific and objective, while the latter are regarded as metaphysical and fanciful. The author quotes: “Putting forward views contrary to mechanical metaphors is instead seen as unscientific; others will strongly and hostilely think that you are trying to bring metaphysics back.” (p. 011)
Compared with the analogy of machines and programs, the author prefers the “language of cognition” (p. 327). Since we can speak of biological parts, functions, and programs as we speak of machines, then we can also speak of biological language, purpose, and meaning as we speak of a cognitive subject. “It is time to embrace the concepts of purpose and agency—and, moreover, there is nothing to fear in doing so.” (XVII)
And the tendency brought about by this latter kind of language is anti-reductionist. What function a machine has can indeed be inferred by precise study and by analyzing the structure of each of its parts, but what purpose a person has cannot be reconstructed by breaking that person down into every cell and then putting them back together. Meaning always re-emerges at each higher level—the cell has its meaning, the organ has its meaning, and individual life has still more its meaning—but the meaning at each level is not a simple combination of the meanings at lower levels. “Just as we ‘interpret’ a book or even a sentence, and can never reduce it to, or derive it from, the interpretation of individual words alone, so too it is with explanations of the mechanisms by which life works. Each level of the life process is not fully defined by, or contained within, the previous level.” (p. 033)
With the help of this new language, the author offers his own answer to the ancient question of “what is life?”: “We can think of life as a kind of ‘meaning generator.’ You could say that life is those entities that are capable of assigning value to their environment and thereby finding their meaning for the universe.” (p. 017)
This language depicts a world picture rich in meaning. Some may worry that speaking of life in this way will contaminate science with values, preventing it from remaining objective and neutral, and that this is therefore harmful. But the problem is that the original mechanistic world picture was never absolutely neutral to begin with; it too embodies certain values and moral tendencies. The author says: “It fails on moral grounds as well, because it forces us to see life as a plan with normative characteristics, while reality can always deviate from this plan to a greater or lesser extent. The exact opposite is the case: life is a process, a truly unfolding process. It is time to abandon those old views.” (p. 263)
Against Perfection
The moral tendency involved here turns on how one evaluates “perfection.” The famous philosopher Sandel has a book on life sciences and technology called Against Perfection, which probably touches on similar issues. A machine has its own “perfect” state: when every part follows the blueprint, precise without error and fitting together without the slightest gap, it is flawless. But real machines in operation always run into problems: perhaps the parts are not manufactured to sufficient precision; perhaps some unexpected situation arises during operation; perhaps something is too tight or too loose; perhaps, inexplicably, one part is missing or one part too many…… Of course, none of these states is perfect, so we always have to work hard to adjust and debug, reduce error, and strive to bring the machine closer to perfection.
But under the new linguistic articulation of life sciences, the above “perfection” is no longer regarded as a good or positive direction. Quite the opposite: this machine-like “perfection” precisely means “non-life,” a negative and privative concept; whereas “imperfection” in the traditional sense is precisely the original face of “life,” a positive and affirmative concept. For human society, what more needs to be pursued and developed is not mechanized perfection, but flourishing vitality.
Some people imagine a “perfect” society created by “genetic engineering techniques,” but life sciences reveal to us how dangerous such a society is (page 265). Resisting the abuse of genetic engineering does not mean resisting life sciences; on the contrary, we are precisely following the teachings of life sciences, because this tendency toward precise control is what is “anti-life.”
The imperfection of life begins at the molecular scale. For a machine, we can reduce it to each and every part and thereby obtain precise knowledge, because the parts and the machine as a whole are, broadly speaking, still things at the same scale, and thus do not give rise to emergent phenomena—until the field of artificial intelligence in recent years, which, thanks to a new analogical language (such as “neural networks”), has finally opened up a new situation, so that in the realm of artificial machines we too can, to a greater or lesser extent, create phenomena of “emergence.” But for life, our “reduction” crosses scales; especially at the molecular scale, uncertainty becomes impossible to ignore.
The author says: “The reason why the analogy of life to a machine fails lies in an important point: cells work at the molecular scale, and the situation in the molecular world differs greatly from that of the everyday world. Molecular motion is random, unpredictable, and filled with noise. In the face of these chaotic characteristics, life is less a matter of striving to maintain order than of trying to make full use of these characteristics. The basis for life’s flourishing development is the noise and diversity at the molecular level, as well as accidental incidents and fluctuations that arise by chance. If molecules were to lose this chaotic characteristic, life would be unable to function.” (page VIII)
In short, complexity, chaos, diversity, and accident are not negative factors to be eliminated, but positive features of life as life. Without complexity or negentropy, life does not exist; without accidents and mutations, life cannot evolve; without diversity, life can hardly coexist.
Once a machine breaks down, it is hard for it to keep running; but the processes of growth and reproduction in life are full of uncertainty—“Have we not seen time and again, at every level, that life really does operate in just this way?” (page 260)
When we switch back from the language of “machine analogy” to the language of “life analogy,” we can more deeply understand the various real-world issues mentioned earlier. For example, should we use genetic engineering to eliminate all kinds of congenital defects in human beings? —If there is in fact no definite “blueprint” that determines what counts as a perfect human being, then so-called “defects” are all relative: lacking a tail is a defect for a monkey, but an advantage for a human being. If the reproduction of life were always flawless and there were no “defects,” then the evolution of life would also come to a standstill. If life cannot be broken down into a set of parts with clear functions, each performing its own duties, then no matter how advanced our technological means become, it will always be difficult to precisely modify any one complex trait—especially those abilities that human beings value, such as reason, emotion, social capacity, and so on. Perhaps one round of gene editing could improve a child’s memory, but at the same time make him more inclined to be solitary; an operation that improves appearance might also hide the risk of some disease, and so on.
This is not to say that we should reject any kind of gene therapy. On the contrary, the author of course believes that life sciences and genetic technologies are continually benefiting humanity. The key is that we must not fetishize the power of technology, nor take omniscience and omnipotence as the ideal of science. Science is always flawed, imperfect—so now, and so it will be in the future. But just like life itself, “defects” precisely prove that science is always full of vitality.
[1] Cited via Roger G. Newton, What Is Scientific Truth?, trans. Wu Jike, Shanghai Science and Technology Education Press, 2001, p. 179.
[2] Heisenberg, Physics and Philosophy, trans. Fan Dainian, Commercial Press, 1984, pp. 109–110.
[3] Heisenberg, Physics and Philosophy, trans. Fan Dainian, Commercial Press, 1984, pp. 21–22.
Translated from the Chinese original with AI assistance. The original text is authoritative.
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