In this exclusive interview, we delve into the fundamental questions of life and the evolution of biological research while examining the role of scientific revolutions in shaping our understanding of the living world and the challenges posed by modern advancements like artificial intelligence
PART 1: Basic Characteristics of Life and Biological Research
What are the basic characteristics of life and why are they important for biological research?
It is widely accepted that, in contrast to the physical sciences, there are no universal guiding principles, such as energy conservation or laws, that are applicable to all organisms at all times. The physicist and molecular biologist Francis Crick highlighted this, writing that the results of physics can be expressed in powerful, deep, and often counterintuitive general laws, but there was nothing in biology that corresponded to special and general relativity or quantum electrodynamics.
Crick was of the opinion that, though biology had its “laws,” such as those of Mendelian genetics, they were often only rather broad generalisations with significant exceptions. Rather, Crick emphasised, biology was best characterised by the existence of mechanisms that were built with chemical components that were often modified by other mechanisms later on.
Experimental biologist Jacques Loeb, too, pointed to differences between biology and physics or chemistry. But, he related them to the existence of a critical guiding principle in biology that distinguished this science from other sciences, namely specificity. I quote from a publication in 1916: “The mechanisms for the synthesis of proteins must have one other peculiarity: They must be specific in their action…. Each species seems to possess one or more proteins not found in any other but closely related species. Each organism develops from a tiny, microscopic germ and grows by synthesising the non-specific building stones (amino acids) into the specific proteins of the species.”
In Loeb’s opinion, the “formation of the specific constituents of the living cell from non-specific products” was the “essential feature of the [growth] process in the living cell.” He reminded his colleagues that the artificial creation of life had to involve the synthesis of specific molecules, particularly self-replicating DNA (at the time nuclein).
The introduction of the concepts of specificity, genetic or genomic causality, and hierarchical organisation into basic areas of research contributed decisively to biology becoming a modern experimental science. Specificity expresses itself in body structures and proteins that are specific to individual organisms, species, and so on and is now explained by the existence of specific information encoded in the genome.
When I talk about hierarchy, I refer to the systemic organisation into levels that are subordinated by relationships of control or to different nested categories as in the Linnaean taxonomic system. Hierarchies are at the core of many complex systems, as well as biological systems. An example is hierarchical gene regulatory networks that form the basis of development and play a crucially important role in the causal analysis of development.
Neglecting or rejecting one or all of these biological principles has serious consequences for our understanding of life. This is shown, for example, by the fact that purely mathematical-chemical models cannot explain basic features of the generation of form in development and its stability unless they are guided by genomic causation.
PART 2: Alan Turing and Morphogenesis
What were the key tenets of Alan Turing’s model of morphogenesis? How did biologists react to Turing’s model? Was it readily accepted, or did it encounter resistance? What were the long-term impacts of his ideas?
Alan Turing is known for his outstanding work as a mathematician and computer scientist and his pioneering work on artificial intelligence. It is less known that, in 1952, he also proposed a physical- chemical model related to biology. It was called the reaction-diffusion model, which aimed at explaining the generation of shapes and forms in biological development. His model showed mathematically that in a homogeneous system of two or more diffusing reagents with different properties, under certain conditions, shapes and gradients may emerge.
Turing did not base his model on biological data. He created a speculative mathematical-chemical model of the self-organisation of patterns from what he believed to be a homogeneous egg cell. The model could mimic biological patterns and was often mathematically more elegant than nature. However, discrepancies between the model and reality prevailed. Therefore, biologists ignored or criticised Turing’s model and other mathematical- chemical models for decades. For example, they criticised that egg cells were not homogeneous, that the models were not organism-specific, and that genes were excluded from the discussion, even when it became clear that genes played crucial roles in development.
Biologists also doubted whether Turing systems possessed the robustness over long periods of time that is required to explain reproduction and evolution.
More recently, models of pattern formation and morphogenesis were created that tried to deal with the shortcomings of Turing’s model in development and to combine self-organising events with genomic regulatory mechanisms. Many cellular and developmental processes are indeed self-organised in the sense that they are not under the direct control of the genome.
The interaction of macromolecules can determine features of cellular structures. However, it has been shown that in almost all cases, the self-organising processes are guided by genomic controls that select specific outcomes from many different possibilities.
Key features of developmental systems, in particular the constancy and inheritance of developmental outcomes and the stability of species over evolutionary time periods, cannot be convincingly explained without considering the causal role of the genome and its more or less faithful transgenerational transmission.
PART 3: Canguilhem’s Dictum on Biological Thought
Can you elaborate on Georges Canguilhem’s idea that biological thought is “torn between opposing poles”? How have these contrasting forces shaped the progress of biological research?
Various historians and philosophers of science raised the topic of opposing poles of scientific thought. The French philosopher and physician Georges Canguilhem dealt with the relationship of philosophy and biology or medicine, asking, for example, how major transformations in biology and modern medicine impact concepts of life or how philosophical concepts influence ideas and practices in biology and medicine. As Brooke Holmes pointed out, Canguilhem believed that the history of biological theory oscillates, and he perceived here a dialectic that already existed in ancient Greece, where, for example, Aristotle’s vitalism responded to Democritus’s mechanicism. Examples of these oscillations are those between atomicity and totality (on the problem of individuality) and on preformation and epigenesis (on the problem of development).
In his book “Thematic Origins of Scientific Thought,” the physicist and historian Gerald Holton dealt with 20th-century physics. Holton distinguished two different conceptual motives in theoretical physics that he called “themata.” The search for unity, parsimony, causality, and completeness contrasted with concepts such as causality and uncertainty. Jonathan Harwood, a historian of genetics and technology, distinguished different styles in the research of early 20th-century geneticists. Unlike Holton, who analysed different individual styles, Harwood looked at styles of different scientific communities. He applied Karl Mannheim’s concept of intellectual style to scientific thought, characterising style as recurring epistemological assumptions that differ between groups.
The writings of these historians and philosophers stimulated me to examine the different ways of thinking that philosophers and, later, scientists, have adopted to explain the generation of form in biological development. These different ways started with the dichotomy of preformation theory versus epigenesis in Greek antiquity. The term epigenesis was introduced only in the 17th century by William Harvey. I have shown that the ancient basic differences of thought about development between the two groups of philosophers can also be found in later controversies between groups of scientists over explanations of early development.
These differences are related to the acceptance or rejection of the idea of a physical form of what today would be called information for generating the embryo, that is, a material continuity between generations, being a necessary pre-requisite for specific development and heredity. The opposing poles of genomic causality versus self-organisation in 20th and 21st-century theories of the generation of form are sometimes, but not always, due to different disciplinary backgrounds.
For one group, the generation of patterns, form, and constant outcome in development is causally related to something that is “preformed” in the germ cells, the nucleus of germ cells, or the genome. This approach requires experimental methods and a guiding hypothesis or theory. For the other group, development is a process where genuinely new characters emerge from formless matter by physical-chemical processes of self- organisation. There is no pre-existing form or information. This approach is largely based on computerised simulations.
I concluded that these approaches are not equivalent because it is impossible to explain the generation of form and constant outcome of development without the assumption of the transmission of pre-existing information, that is, information in the form of DNA sequences in the genome. Only in this framework of “preformed” information can “epigenesis” in the form of physical and chemical processes of self-organization play important roles.
PART 4: Thomas Kuhn’s Concept of Scientific Revolutions
How can Thomas Kuhn’s concept of “Scientific Revolutions” be applied to understanding historical shifts in biological paradigms?
As is well known, Thomas Kuhn, in his 1962 book “The Structure of Scientific Revolutions”, rejected the idea of science advancing through the accumulation of knowledge. He also challenged the idea that science progresses at all. Instead, he suggested that periods of stable scientific growth – he called them “normal science” – are occasionally interrupted by revolutions that change the basic framework of the science in question.
In “normal science,” scientists follow an accepted “paradigm”, and their work is mainly “puzzle-solving.” A violation of the expectation – an “anomaly” – may lead to paradigm change and scientific revolutions. Kuhn believed that revolutions are sudden, unstructured, not designed by rational debates, and that persuasion plays a decisive role in paradigm changes. He held that the new paradigms are not truer than the old ones and that paradigms are not comparable but “incommensurable.” For all these reasons, revolutions are not objectively progressive. The book impacted particularly the arts and humanities, among them research and teaching of the history of science.
I have shown that major innovations in the history of biology, their causes and trajectories, were different from each other and that they rarely meet Kuhn’s criteria for a scientific revolution. New developments were often driven by technological advances, mostly had a rational basis, and in many cases, revolutionary changes were generated out of “normal science” without being preceded by “anomalies.” Often, the new paradigms did not replace older ones but opened up new fields of research. In some cases, changes deemed revolutionary were reversed after some time, and the old paradigms were re-instated – an example is the idea of biologically relevant macromolecules that had been superseded by that of colloids in the early 20th century before being re-instated as being far superior. I have written about this period elsewhere. The history of biology and science generally shows that paradigms can be compared and that the agreement with reality has remained a decisive measure of good and bad science.
Recently, I participated in a conference about artificial intelligence (AI), where we discussed, among other things, the extent to which AI is shaking the foundations of how we understand knowledge and undermines trust in science. AI has indeed a tremendous impact on science because it enormously accelerates the generation of knowledge through the recognition of patterns in large datasets. If AI is not accompanied by hypothesis generation and experimentation, one of science’s basic goals, which is the search for understanding mechanisms and causes, is abandoned. But in my opinion, the crisis about the foundation of the generation of knowledge has a long history and was not caused by AI, but by postmodernist philosophical-sociological discourses related to the names Michel Foucault, Bruno Latour, David Bloor, Steve Fuller, and also Thomas Kuhn.
Kuhn has helped understand the importance of social and psychological factors in science that had already been highlighted by Michael Polanyi. But Kuhn’s book also strongly contributed to scientific relativism, which is marked by discourses about the denial of the existence of scientific facts and the idea of scientific truth. Truth here does not mean absolute truth as in Medieval times, but reliable, objective knowledge that is the outcome of a complex search, not a simple act driven by personal belief. The post-truth philosophy affects not only public responses to science, such as indicated in the widespread disregard for scientific evidence that excludes vaccinations as the cause of certain diseases but also society as a whole. As the sociologist Colin Wight once said, it is the concept of objective truth that renders demands for social justice possible.
Bibliography:
- Crick, F.H.C. 1988. What Mad Pursuit: A Personal View of Scientific Discovery, New York: Basic Books.
- Deichmann, U. 2007. “Molecular” Versus “Colloidal”: Controversies in Biology and Biochemistry, 1900–1940. Bulletin for the History of Chemistry 32(2): 105-118.
- Holmes, B. 2023. Canguilhem and the Greeks: Vitalism between history and philosophy. In: Donohue, C., Wolfe, C.T. (Eds.), Vitalism and its Legacy in Twentieth Century Life Sciences and Philosophy. Springer, Cham, Switzerland, pp. 107-129.
- Holton, G. 1973. Thematic Origins of Scientific Thought. Kepler to Einstein. Harvard University Press.
- Kuhn, T. [1962] 1970. The Structure of Scientific Revolutions. Chicago: University of Chicago Press.
- Loeb, J. 1916. The Organism as a Whole from a Physicochemical Viewpoint. New York and London: Putnam’s Sons.
- Polanyi, M. [1958] 1962. Personal Knowledge – Towards a Post-Critical Philosophy. Chicago: University of Chicago Press.
- Turing, A.M. 1952. The Chemical Basis of Morphogenesis. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 237(641), 37-72.
