Jump to main content

  1. Plaine Commune, contributive learning territory

    Memories for the Future: Thinking with Bernard Stiegler


    The contributive economy is a strategy to disrupt technological disruption by developing knowledge in all its forms. This program has led to several concrete working groups in Plaine Commune.

    Abstract

    The program Plaine Commune, contributive learning territory, started in late 2016. It emerged from the theoretical work of Bernard Stiegler and the Ars Industrialis group. The contributive economy is a strategy to disrupt technological disruption by developing knowledge in all its forms. This program has led to several concrete working groups in Plaine Commune, while others are still developing. Mainly, work is taking place on the economy, digital urbanism, and young children’s development in the context of the overuse of digital media. Here, we focus on the group on digital media and young children’s development and how academics and inhabitant works integrate.

    Citation
    Montévil, Maël. 2023. “Plaine Commune, Contributive Learning Territory.” In Memories for the Future: Thinking with Bernard Stiegler, edited by Bart Buseyne, Georgios Tsagdis, and Paul Willemarck
    Manuscript Citation Full text
  2. Normativité et infidélités du milieu : actualités biologiques de Canguilhem

    Normativité et infidélités du milieu : actualités biologiques de Canguilhem

    La philosophie et ses dehors


    Quelques remarques sur la pertinence de la philosophie de Canguilhem sur les enjeux contemporains, de la medecine par la preuve à la disruption des organisations biologiques.

    Citation
    Montévil, Maël. 2023. “Normativité et Infidélités Du Milieu : Actualités Biologiques de Canguilhem.” In La Philosophie et Ses Dehors. Centre Lauragais d’Études Scientifiques
    Manuscript Citation Full text
  3. Modeling organogenesis from biological first principles

    Modeling organogenesis from biological first principles

    Organization in Biology: Foundational Enquiries into a Scientific Blindspot


    Here we discuss the application and articulation of biological principles for mathematical modeling of morphogenesis in the case of mammary ductal morphogenesis, with an emphasis on the default state.

    Abstract

    Unlike inert objects, organisms and their cells have the ability to initiate activity by themselves, and thus change their properties or states even in the absence of an external cause. This crucial difference led us to search for principles suitable for the study organisms. We propose that cells follow the default state of proliferation with variation and motility, a principle of biological inertia. This means that in the presence of sufficient nutrients, cells will express their default state. We also propose a principle of variation that addresses two central features of organisms, variation and historicity. To address interdependence between parts, we use a third principle, the principle of organization: more specifically, the notion of the closure of constraints. Within this theoretical framework, constraints are specific theoretical entities defined by their relative stability with respect to the processes they constrain. Constraints are mutually dependent in an organized system and act on the default state.
    Here we discuss the application and articulation of these principles for mathematical modeling of morphogenesis in a specific case, that of mammary ductal morphogenesis, with an emphasis on the default state. Our model has both a biological component, the cells, and a physical component, the matrix that contains collagen fibers. Cells are agents that move and proliferate unless constrained; they exert mechanical forces that i) act on collagen fibers and ii) on other cells. As fibers are organized, they constrain the cells’ ability to move and to proliferate. This model exhibits a circularity that can be interpreted in terms of the closure of constraints. Implementing our mathematical model shows that constraints to the default state are sufficient to explain the formation of mammary epithelial structures. Finally, the success of this modeling effort suggests a step-wise approach whereby additional constraints imposed by the tissue and the organism can be examined in silico and rigorously tested by in vitro and in vivo experiments, in accordance with the organicist perspective we embrace.

    Citation
    Montévil, Maël, and Ana Soto. 2023. “Modeling Organogenesis from Biological First Principles.” In Organization in Biology: Foundational Enquiries into a Scientific Blindspot, edited by Matteo Mossio. Springer Nature
    Manuscript Citation Full text
  4. How does randomness shape the living?

    How does randomness shape the living?

    Figures of Chance


    In biology, randomness is a critical notion to understand variations; however this notion is typically not conceptualized precisely. Here we provide some elements in that direction.

    Abstract

    Physics has several concepts of randomness that build on the idea that the possibilities are pre-given. By contrast, an increasing number of theoretical biologists attempt to introduce new possibilities, that is to say, changes of possibility space – an idea already discussed by Bergson and that was not genuinely pursued scientifically until recently (except, in a sense, in systematics, i.e, the method to classify living beings).
    Then, randomness operates at the level of possibilities themselves and is the basis of the historicity of biological objects. We emphasize that this concept of randomness is not only relevant when aiming to predict the future. Instead, it shapes biological organizations and ecosystems. As an illustration, we argue that a critical issue of the Anthropocene is the disruption of the biological organizations that natural history has shaped, leading to a collapse of biological possibilities.

    Citation
    Montévil, Maël. 2023. “How Does Randomness Shape the Living?” In Figures of Chance, edited by Anne Duprat and others
    Manuscript Citation Full text
  5. Conceptual and Theoretical Specifications for Accuracy in Medicine

    Conceptual and Theoretical Specifications for Accuracy in Medicine

    Personalized Medicine in the Making: Philosophical Perspectives from Biology to Healthcare


    We question some aspects of medicine from the perspective of theoretical biology, on the one hand, and the technological and social dimension of health and disease on the other hand.

    Abstract

    Technological developments in genomics and other -omics originated the idea that precise measurements would lead to better therapeutic strategies. However, precision does not entail accuracy. Scientific accuracy requires a theoretical framework to understand the meaning of measurements, the nature of causal relationships, and potential intrinsic limitations of knowledge. For example, a precise measurement of initial positions in classical mechanics is useless without initial velocities; it is not an accurate measurement of the initial condition. Conceptual and theoretical accuracy is required for precision to lead to the progress of knowledge and rationality in action. In the search for accuracy in medicine, we first outline our results on a theory of organisms. Biology is distinct from physics and requires a specific epistemology. In particular, we develop the meaning of biological measurements and emphasize that variability and historicity are fundamental notions. However, medicine is not just biology; we articulate the historicity of biological norms that stems from evolution and the idea that patients and groups of patients generate new norms to overcome pathological situations. Patients then play an active role, in line with the philosophy of Georges Canguilhem. We argue that taking this dimension of medicine into account is critical for theoretical accuracy.

    Keywords: Normativity, Organization, Personalized Medicine, Technology, theoretical biology

    Citation
    Montévil, Maël. 2022. “Conceptual and Theoretical Specifications for Accuracy in Medicine.” In Personalized Medicine in the Making: Philosophical Perspectives from Biology to Healthcare, edited by Chiara Beneduce and Marta Bertolaso, 47–62. Human Perspectives in Health Sciences et Technology. Springer International Publishing. https://doi.org/10.1007/978-3-030-74804-3_3
    Manuscript Citation Publisher Full text
  6. Anthropocene, exosomatization and negentropy

    Anthropocene, exosomatization and negentropy

    On transition : in response to Antonio Guterres


    After precursors such as Georgescu-Roegen, we maintain that political economy in the Anthropocene is a challenge that requires a fundamental reconsideration of epistemology.

    Abstract

    The industrial economy took shape between the late eighteenth century and the nineteenth century, initially in Western Europe and then in North America. Besides technical production, it involves technological production – the integration of sciences in order to produce indus-trial goods –, to the strict extent that, as Marx showed, capitalism makes knowledge and its economic valorization its primary element.
    Newton’s physics and the metaphysics that goes with it originated the epistemic (in Michel Foucault’s sense) and epistemological (in Gaston Bachelard’s sense) framework of this great transformation. In this transformation, otium (productive leisure time) submits to negotium (worldly affairs, business). All along, mathematics has been applied with ever more powerful and performative calculating machines.
    After precursors such as Nicholas Georgescu-Roegen, himself inspired by Alfred Lotka, we maintain that political economy in what is now called the Anthropocene (whose features were delineated by Vladimir Vernadsky in 1926) is a challenge that requires a fundamental reconsideration of these epistemic frameworks and epistemological frameworks. With Dar-win, living beings became part of a historical process of becoming. In humans, knowledge is a performative part of this process that shapes and reshapes lifestyles in order to tame the im-pact of technical novelties.

    Citation
    Montévil, Maël, Bernard Stiegler, Giuseppe Longo, Ana M. Soto, and Carlos Sonnenschein. 2020. “Anthropocene, Exosomatization and Negentropy.” In On Transition : In Response to Antonio Guterres. https://internation.world/
    Manuscript Citation Publisher Full text
  7. A Primer on Mathematical Modeling in the Study of Organisms and Their Parts

    A Primer on Mathematical Modeling in the Study of Organisms and Their Parts

    Systems Biology


    How do mathematical models convey meaning? What is required to build a model? An introduction for biologists and philosophers.

    Abstract

    Mathematical modeling is a very powerful tool for understanding natural phenomena. Such a tool carries its own assumptions and should always be used critically. In this chapter, we highlight the key ingredients and steps of modeling and focus on their biological interpretation. In particular, we discuss the role of theoretical principles in writing models. We also highlight the meaning and interpretation of equations. The main aim of this chapter is to facilitate the interaction between biologists and mathematical modelers. We focus on the case of cell proliferation and motility in the context of multicellular organisms.

    Keywords: Equations, Mathematical modeling, Parameters, Proliferation, Theory

    Citation
    Montévil, Maël. 2018. “A Primer on Mathematical Modeling in the Study of Organisms and Their Parts.” In Systems Biology, edited by Mariano Bizzarri, 41–55. Methods in Molecular Biology. New York, NY: Springer. https://doi.org/10.1007/978-1-4939-7456-6_4
    Manuscript Citation Publisher Full text
  8. From the Century of the Gene to that of the Organism: Introduction to New Theoretical Perspectives

    From the Century of the Gene to that of the Organism: Introduction to New Theoretical Perspectives

    Life Sciences, Information Sciences


    Our group proposes three main principles for a theory of organisms, namely: the default state, the principle of variation and the principle of organization.

    Abstract

    Summary This chapter briefly presents and describes the three main principles that the group proposes for a theory of organisms, namely: the default state, proliferation with variation and motility, the principle of variation and the principle of organization. It is crucial to critique the philosophical and theoretical position on which the biological research feeding into the program is based and which has dominated biomedical research for the last 70 years. Physical theories are founded on stable mathematical structures, based onregularities and especially on theoretical symmetries. At the time of cell theory formulation and still today, cell theory plays a federating role between evolution biology and organism biology. Finally, analysis of the differences between the physics of inanimate and living matter leads to the proposal of three principles that provide aviable perspective for the construction of a necessary theory of organisms.

    Keywords: cell theory, evolution biology, mathematical structures, organism biology, philosophical position, physical theories, theoretical symmetries

    Citation
    Montévil, Maël, Giuseppe Longo, and Ana M. Soto. 2018. “From the Century of the Gene to That of the Organism: Introduction to New Theoretical Perspectives.” In Life Sciences, Information Sciences, edited by T. Gaudin, D. Lacroix, M.‐C. Maurel, and J.‐C. Pomerol, 81–97. John Wiley & Sons, Ltd. https://doi.org/10.1002/9781119452713.ch9
    Manuscript Citation Publisher Full text
  9. Comparing Symmetries in Models and Simulations

    Comparing Symmetries in Models and Simulations

    Springer Handbook of Model-Based Science


    We distinguish mathematical modeling, computer implementations of these models and purely computational approaches by their symmetries and by randomness.

    Abstract

    Computer simulations brought remarkable novelties to knowledge construction. In this chapter, we first distinguish between mathematical modeling, computer implementations of these models and purely computational approaches. In all three cases, different answers are provided to the questions the observer may have concerning the processes under investigation. These differences will be highlighted by looking at the different theoretical symmetries of each frame. In the latter case, the peculiarities of agent-based or object oriented languages allow to discuss the role of phase spaces in mathematical analyses of physical versus biological dynamics. Symmetry breaking and randomness are finally correlated in the various contexts where they may be observed.

    Keywords: Phase Space, Symmetry Breaking, Chaotic Dynamic, Object Oriented Programming, Genetically Modify Organism

    Citation
    Longo, G., and Maël Montévil. 2018. “Comparing Symmetries in Models and Simulations.” In Springer Handbook of Model-Based Science, edited by M. Dorato, L. Magnani, and T. Bertolotti, 843–56. Springer. https://doi.org/10.1007/978-3-319-30526-4
    Manuscript Citation Publisher Full text
  10. Big Data and biological knowledge

    Big Data and biological knowledge

    Predictability and the Unpredictable. Life, Evolution and Behaviour


    Can big data replace theoretical thinking? How should these technics be used? A critical discussion on the use of big data in biology.

    Abstract

    Some authors assert that the analysis of huge databases could replace the scientific method. On the contrary, we argue that the best way to make these new technologies bear fruits is to frame them with theories concerning the phenomena of interest. Such theories hint to the observable that should be taken into account and the mathematical structures that may link them. In biology, we argue that the community urgently needs an overarching theory of organisms that would provide a precise framework to understand lifecycles. Among other benefits, such a theory should make explicit what we can and cannot predict in principle.

    Keywords: Big Data, biological variation, cancer biology, knowledge, theory

    Citation
    Montévil, Maël, and G. Longo. 2018. “Big Data and Biological Knowledge.” In Predictability and the Unpredictable. Life, Evolution and Behaviour, edited by Giulia Frezza and David Ceccarelli, 133–44. Roma: CNR Edizioni
    Manuscript Citation Full text

Filter by year to see more chapters.