"Les engagements épistémiques des théories de la complexité »
| When |
Mar 25, 2021 04:00
to
Mar 29, 2021 01:00 |
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| Where | ENS de Lyon, Webinar |
| Contact Name | PABLO JENSEN |
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What kind of ontology of the social world is implicit in complexity theories?
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What performative and normative effects do such ontologies have on complexity specialists’ views of politics?
- Jean-Marc Lévy-Leblond (https://fr.wikipedia.org/wiki/Jean-Marc_Lévy-Leblond)
- Marc Barthelemy (http://cams.ehess.fr/marc-barthelemy/)
- Sébastien Dutreuil (https://otmed.academia.edu/SebastienDutreuil)
Videos available on Your tube : Here
THE PROGRAM
- 11 January - from 11 am to 12.30 pm : "Introduction to the webinar", Fabrizio Li Vigni (Article Fabrizio Li Vigni : here) & Pablo Jensen; "Introduction to complexity theories, Fabrizio Li Vigni and "Cybernetics and Wicked Problems", Andy Pickering (Article Andrew PICKERING : here)
------> video available : HERE
- 18 January - from 11 am to 12.30 pm : "Second cybernetics. the science of saving energy", Thomas Turnbull (Article Thomas Turnbull : here) and "From cybernetics to complexity", Jean-Pierre Dupuy (2 Articles Jean-Pierre Dupuy : here and here)
------> video available : HERE
- 25 January - from 11 am to 12.30 pm : "CosmoTech: from complexity research to business", Michel Morvan and "Complex thinking in organization studies: from theory to practice", David Vallat (Article David Vallat : here)
------> video available : HERE
- 1 February - from 11 am to 12.30 pm : "Whose complexity? Modelling or governing the environment?", Catharina Landstrom (Article Catharina Landstrom : here) and "Complexity sciences and Hayek's neoliberalism", Fabrizio Li Vigni (Article Fabrizio Li Vigni : here)
------> video available : HERE
- 8 February - from 11 am to 12.30 pm : "The Earth system: genealogy of the global environment as a complex system", Sébastien Dutreuil (Article Sébastien Dutreuil : here) and "From Cybersyn to social macroscopes: contributions of complex systems research to a social reflexivity", David Chavalarias (Articles David Chavalarias : here and here)
------> video available : HERE
- 15 February - from 11 am to 12.30 pm : 15 February - from 11 to 12.30 pm : "The (non)neutrality of science and algorithms", Aniello Lampo and "Can gender inequality be created without inter-group discrimination?", Floriana Gargiulo (Article Floriana Gargiulo : here)
------> video available : HERE
- 22 February - from 11 am to 12.30 pm : "Les complexités de la physique", JM Lévy-Leblond (Article JM Lévy-Leblond : here) et Marc Barthelemy (Article de Marc Barthelemy : here)
------> video available : HERE
- 1 March - from 11 am to 12.30 pm : "A non-imperialist physics", Quentin Rodriguez (Article Quentin Rodriguez : here) and "Thermodynamics as the science of complexity in Ilya Prigogine and Isabelle Stengers’ Order out of chaos (1979). Is thermodynamics really able to help social sciences?", Emanuel Bertrand (Article Emanuel Bertrand : here)
------> video available : HERE
- 25 March - from 4 pm to 5.30 pm : "The monetization of ecosystemic services", Victor Lefèvre and "Three visions of the futures of forests in a changing climate: the epistemic commitments of forest scientists", Antoine Dolez (Article Antoine Dolez : HERE)
------> video available : HERE
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Introduction to the webinar - PABLO JENSEN, Fabrizio Li Vigni
Introduction to complexity theories - Fabrizio Li Vigni
The historical and sociological literature about the theories of complexity is very thin. Few works propose a taxonomy of some of these theories, but they are carried out by complexity theorists themselves. In general, there are two kinds of positions: either an irenic and simplifying description of the domain, where different groups are recognized but considered as a single family; or a reductionist, if not propagandistic description where a single group or even a single researcher is considered as “the” true representative of complexity theory. In this short and introductory talk I would like to show that the field is very heterogeneous, by presenting seven different groups of complexity theories. A qualitative study based on a series of criteria has been conducted to find and describe such groups. To confirm or correct such a taxonomy, a quantitative study based on the scientometric analysis of such groups is in course thanks to a collaboration with CNRS mathematician Floriana Gargiulo.
Systematising Energy Saving at the RAND Corporation in the 1970s - Thomas Turbnull
In revisiting the history of the now common-sense notion of energy saving, this paper will address the relation between modelling the dynamics of energy demand and the messy complexity of energy systems in practice. To do so, we will turn to the nineteen-seventies, when archetypal Cold War think tank the RAND Corporation turned its expertise toward the problem of energy demand. The organisation’s researchers realised that utility-led forecasting contributed to growth in electricity use. By developing an independent forecasting method, they reconceptualised the various components of society’s fuel consumption in general systemic terms. This approach was heavily informed by cybernetics. It was suggested that demand reducing feedback loops could be introduced into the system of energy use, iteratively reducing demand over time and with minimal impact on welfare and economic growth. This work marked a conceptual extension of previous attempts by electrical engineers to use the power grid as means of resource conservation. Whereas power engineers had restricted their claims to grid mechanics, RAND researchers suggested the entire energy system could be reconfigured as a sociotechnical means of conservation. This idea followed in an intellectual tradition which considered the grid as a networked computational system, while also reflecting a later cybernetic preoccupation with the relation between energy and information. Many aspects of RAND’s approach were operationalised in California, and the distinction between energy saving in theory and in practice will provide a point of conclusion.
Thomas Turnbull : here
Representing or intervening? When less is more in environmental modelling - Catharina Landström
How much ‘real world’ complexity can you ignore? This is a question that all computer simulation modellers have to address. While computer models make it possible to represent complex systems there are limits to the number of parameters it makes sense to include in a model. Different modelling approaches have different affordances in this regard. The purpose of modelling is also important. Scientific modellers often take pride in the number of elements and relationships that the models they create can represent. However, modelling for environmental management requires a different perspective on complexity and model representation. To build models that provide actionable knowledge for environmental decision makers it is necessary to minimise the number of elements and processes included in the model. Decision makers are not interested in knowing as much as possible about the functioning of a system, they need to know what they can do, to which effects. Models for environmental management must be trustworthy and provide actionable knowledge. But, what is a modeller to do when all the decision makers involved do not operate in the same realities? In this presentation I will consider how the tension between representing complex realities and intervening in them is present in environmental modelling for decision making. Drawing on empirical examples from the field of water management in the UK I will discuss how complexity can be addressed in modelling for the management of socio-hydrological systems.
Article Catharina Landstrom : here
Complexity sciences and Hayek's neoliberalism - Fabrizio Li Vigni
Complexity sciences are one of the most mediatized scientific fields of the last forty years. While this domain has attracted the attention of many philosophers of science, its normative and political aspects have, until recently, not made the object of any systematic study. The present text inscribes in the thin social science literature about complexity and proposes a contribution focused on the political – ideological and organizational – issues of the Santa Fe Institute’s, cradle of the domain. In particular, it illustrates the existence of a certain connection it has with neoliberalism. Two entry points have been chosen. The first is theoretical and deals with the institute’s ontological and axiological views of nature and society, as they are based on a certain reading of Hayek and Darwin. The second entry point is institutional and tackles SFI’s philosophy of fund raising and organizational functioning inspired by Schumpeter. The thesis of the article is that the SFI can be seen as a scientific private institution with some of the characteristics of think tanks, which embodies and justifies a neoliberal view of research based on decentralized innovation, creative destruction and competition.
Complex thinking in organization studies: from theory to practice - David VALLAT
The Covid-19 pandemic has placed uncertainty at the heart of how organizations operate: Should we consider the third wave of the epidemic? Will we have to consider downsizing or reorganizing businesses again? When will we all be truly immune? Uncertainty manifests itself in an environment that appears to be out of control, "complex" to use the concept explored by Edgar Morin (2005), that is to say made up of inconspicuous chains of causalities and feedback loops that blur the reading of events. The pandemic is, however, just one uncertainty among many: climate crisis, political instabilities, energy crisis, volatility in the price of raw materials, technological breakthroughs, etc. To better understand these multiple uncertainties, Edgar Morin suggests adopting a complex thinking: "It is the journey in search of a way of thinking which would respect the multidimensionality, the richness, the mystery of reality, and would know that the cerebral, cultural, social, historical determinations which all thought suffers always co-determine the object of knowledge. This is what I call complex thinking" (Morin, 1980, p. 10). In line with the work aimed at operationalizing the complex thinking of Edgar Morin (Martinet, 2006; Morin and Le Moigne, 1999; Le Moigne, 1999; Avenier 1999), the objective of this presentation is to show how an organization can embrace and practice complex thinking.
Article David Vallat : here
gordon pask and the cybernetic method - andrew pickering
In 1955 Stafford Beer defined cybernetics as the science of 'exceedingly complex systems'—wicked systems we cannot understand a priori. Many of the systems we struggle with in the world today fall into this category, so it is interesting and important to think about how to engage with them. In 1958 Gordon Pask contrasted the cybernetic method appropriate to such systems with the scientific method. The cybernetician aims to 'maximise' interaction with an assemblage, while the scientist aims to 'minimise' it (hypothesis-testing). Unfortunately, Pask's discussion relates to his very ambitious (and unsuccessful) attempts to develop a structure of metal threads to replace the human management of a factory, which I find impossible to follow in any detail. This talk therefore focusses on a much simpler real-world example, the adaptive management of the Colorado River, and seeks to clarify, expand and possibly correct Pask's image of cybernetic method. Pask saw this method as a way of developing a 'language' appropriate to managing an exceedingly complex system, and I show that 'language' here has to be understood as a 'vocabulary' of patterned actions—a 'conversation' of actions, not words. Pask claimed that such conversations amount to building up a 'concept,' while I argue that they are not oriented to concept-formation but aim instead at a choreography of agencies (a multiplicity of river flows, sediment deposition, dam operations)—in a process that, following Heidegger, I have previously referred to as poiesis. My principal conclusion is, then, that we need to organise our dealings with complex systems in performative and choreographic (rather than scientific and representational) terms. I make a further post-Paskian distinction between science and cybernetics. If science aims at 'detachable' and dualist mechanisms (machines that dominate nature and function independently of us), the cybernetic method gears continuing human actions into nature (the timing of water flows from dams in relation to river-flooding, say). The cybernetic method thus aims at a different sort of end-state from conventional science. If time permits, I will discuss more examples, including psychiatry (also mentioned by Pask) and anti-psychiatry.
Article Andrew PICKERING : here
"Three visions of the futures of forests in a changing climate: the epistemic commitments of forest scientists." - ANtoine dolez
The Complexities of Physics - Jean-Marc Lévy-Leblond
I will start by proposing a definition of complexity precise enough so that it goes beyond the commonly vague use of the term and general enough to encompass most of the reasonable attempts to put it at work. Concentrating on physical science, it will then be shown by relying on some specific examples that where a description of the physical situation naturally evokes complexity (in the sense defined), its specific analysis in fact avoids it. One could probably go so far as to claim that physical theory is based on the determined effort to eschew dealing with complexity as such. The possibility of such an escape is intimately linked to the constitutive mathematisation of physics. But we will argue that the spectre of complexity, driven out of the objects of physics, comes back to haunt its practice,which consists indeed, of complex modes of operation resulting from processes that are less simple and linear than is often believed.
Article JM Lévy-Leblond : hereFrom Cybernetics to Complexity and Back - Jean-Pierre Dupuy
The (non)neutrality of science and algorithms - ANiello LAMPO
The impact of Machine Learning (ML) algorithms in the age of big data and platform capitalism has not spared scientific research in academia. In this work, we will analyse the use of ML in fundamental physics and its relationship to other cases that directly affect society. We will deal with different aspects of the issue, from a bibliometric analysis of the publications, to a detailed discussion of the literature, to an overview on the productive and working context inside and outside academia. The analysis will be conducted on the basis of three key elements: the non-neutrality of science, understood as its intrinsic relationship with history and society; the non-neutrality of the algorithms, in the sense of the presence of elements that depend on the choices of the programmer, which cannot be eliminated whatever the technological progress is; the problematic nature of a paradigm shift in favour of a data-driven science (and society). The deconstruction of the presumed universality of scientific thought from the inside becomes in this perspective a necessary first step also for any social and political discussion.
The Earth system: genealogy of the global environment as a complex system - Sébastien Dutreuil
In this communication, I will highlight the extent to which the ontological and political discourse of Complex System Sciences has influenced Earth system sciences (and related contemporary scientific and political discourses on the Earth). I will then trace the genealogy of this new object and emphasize the interconnection between the history going from Gaia to the Earth system and that going from cybernetics (first and second) to Santa Fe complexity sciences.Over the past decades, the “Earth system” has been constituted as a new object of knowledge and power. Complementing the idea of the “global environment”, the Earth system has been defined as the ensemble of physical, chemical, biological and human interactions occurring at the Earth’s surface. Concepts, scientific and political discourses, theories and modelling practices have underpinned and resulted from the constitution of this new object. New modelling practices such as the diffusion of Earth system models, and the elaboration of models of intermediate complexity have given shape to the “Earth system”. A series of normative concepts have hinged on the “Earth system”, such as the “Anthropocene”, “planetary boundaries”, or the “2°C target”. In the meantime, the “Earth system” has underpinned new modes of legitimation of technical and political management of the planet, such as geoengineering.
Article Sébastien Dutreuil : here
Can gender inequality be created without inter-group discrimination ? - Floriana Gargiulo
Understanding human societies requires knowing how they develop gender hierarchies, which are ubiquitous. We test whether a simple agent-based dynamic process could create gender inequality. Relying on evidence of gendered status concerns, self-construals, and cognitive habits, our model included a gender difference in how responsive male-like and female-like agents are to others' opinions about the level of esteem for someone. We simulate a population who interact in pairs of randomly selected agents to influence each other about their esteem judgments of self and others. Half the agents are more influenced by their relative status rank during the interaction than the others. Without prejudice, stereotypes, segregation, or categorization, our model produces inter-group inequality of self- esteem and status that is stable, consensual, and exhibits characteristics of glass ceiling effects. Outcomes are not affected by relative group size. We discuss implications for group orientation to dominance and individuals' motivations to exchange.
Article Floriana Gargiulo : here
Les complexités de la physique - Marc Barthelemy
I will try to present the point of view of a "practitioner" of complexity. Being a theoretical physicist interested in cities, I am confronted to the difficulties - not of quantifying the degree of complexity of urban systems - but mainly how to model such a system. In this respect, I advocate for a pragmatic approach, mostly inspired by statistical physics.
The fundamental starting point for such an approach is the availability of data and the existence of a reproducible empirical fact. In order to illustrate this type of approach, we can consider a recent study [1] about Zipf's law. If we rank cities in a given country according to their population, Zipf [2] proposed almost 100 years ago that the population of a city is inversely proportional to its rank. This law has been tested on many periods and for many countries and seems to be (roughly) correct.
The second step - and the most difficult one - is then to find a theoretical explanation for this observation and to write an equation for the temporal evolution of urban populations. The modelling of such a complex system relies on the fundamental idea that there is a hierarchy of mechanisms: some processes are dominant and should be able to explain Zipf's law. Other mechanisms are "details" and merely represent negligible second-order corrections. The important guide is then the comparison of predictions of the model with the observation and which allows for possible corrections to the theory. There are however many traps at this modelling stage. The first one is to propose a mathematical theory with predictions in qualitative agreement only with empirical observations. This problem appears often in economics and is for example the case of Krugman's model [3] for the agglomeration of industrial activity in cities: Krugman proposed a nonlinear equation displaying concentration effects but without any quantitative empirical validation. The second trap is maybe trickier (but also very common): it is in general not (too) difficult to construct a mathematical model whose predictions are in agreement with the observations but that relies on unrealistic assumptions. This is what happened for Zipf's law: the economist Gabaix proposed a stochastic equation that predicts this law [4] (and this approach is considered so far to be the correct explanation) but it relies on the incorrect assumption that cities cannot disappear. In order to avoid such a problem, the model should be based on realistic assumptions and also gives more than one prediction. In general, it is the tension between the smallest number of assumptions (and parameters) and the largest number of predictions empirically verified that leads to a good modelling. This is what we applied in the case of Zipf's law [1]: starting from first principles, we were able to derive an equation for urban population. Interestingly enough this derivation is based on the generalized central limit theorem, a simple mathematical illustration of how details are irrelevant at large scales (we could surmise that the presence of the sum of many terms is an important condition for the possibility of constructing a mathematical description of such complex systems). This equation explains why Zipf's law is in general an approximation and in fact, most of the time not valid. It also explains dynamical effects such as the rise and fall of cities. In addition, this mathematical modelling allows us to identify the main ingredient for understanding the temporal evolution of urban population and which is the existence of very large and rare inter-urban migratory shocks. This shows in particular the importance of political decisions and planning and more generally, how a theoretical approach to complex systems can be helpful for practical considerations.
[1] Zipf, G. K. Human Behavior and the Principle of Least Effort (Addison-Wesley, 1949).
[2] V. Verbavatz & M. Barthelemy, "The growth equation of cities", Nature 587, pages 397–401 (2020).
[3] P. Krugman. The self-organizing economy, Blackwell, 1996.
[4] X. Gabaix. "Zipf's law for cities: an explanation." The Quarterly journal of economics 114.3 (1999): 739-767.
Article de Marc Barthelemy : here
The monetization of ecosystemic services - Victor Lefèvre
"CosmoTech: from complexity research to business", Michel Morvan
In this presentation, we are going to present the way the fruit of our scientific academic work on complex systems modeling and simulation has been transferred into a startup company in order to make it possible for the industrial sector to use it. We will share both how some industrial actors have been receptive to the ideas and concept we proposed and their implementation in software solutions, but also how hard it can be sometimes to go upsrteam to promote very innovative approaches. We will also share our experience of the specific constraints of the business world and how they are compatible with research and innovation.
"A non-imperialist physics", Quentin Rodriguez
Article Quentin Rodriguez : here
"Thermodynamics as the science of complexity in Ilya Prigogine and Isabelle Stengers' Order out of chaos (1979). Is thermodynamics really able to help social sciences? - Emmanuel Bertrand
In 1979, Ilya Prigogine and Isabelle Stengers published a French bestseller, La Nouvelle Alliance. Métamorphose de la science (Gallimard), mainly about philosophy and history of physics. The Belgian theoretical physicist and chemist Prigogine had won the Nobel Prize in chemistry two years earlier, and Stengers was still working on her doctoral thesis in philosophy of science, under his supervision. This book, translated in English in 1984 as Order out of Chaos. Man’s New Dialogue with Nature (Bantam Books), is both dense and complex, and includes rigorous technical developments. Focusing on both dynamics and thermodynamics, the authors propose a grand narrative for the historical evolution of European physics - from the works of Newton to the emergence of relativity and quantum mechanics. They also describe the recent developments in thermodynamics, insisting on the work conducted in Prigogine’s group at Brussels’ University. In particular, the authors attribute to out-of-equilibrium thermodynamics a very extensive interpretative power. For them, thermodynamics can be used outside its physics context of elaboration, and can be very helpful to interpret and model a great range of ecological, economic, social and even psychological phenomena.
Article Emanuel Bertrand : here