Among many properties distinguishing emergence, such as novelty, irreducibility and unpredictability, computational accounts of emergence in terms of computational incompressibility aim first at making sense of such unpredictability. Those accounts prove to be more objective than usual accounts in terms of levels of mereology, which often face objections of being too epistemic. The present paper defends computational accounts against some objections, and develops what such notions bring to the usual idea of unpredictability. I distinguish the objective unpredictability, compatible with determinism (...) and entailed by emergence, and various possibilities of predictability at emergent levels. This makes sense of practices common in complex systems studies that forge qualitative predictions on the basis of comparisons of simulations with multiple values of parameters. I consider robustness analysis as a way to ensure the ontological character of computational emergence. Finally, I focus on the property of novelty, as it is displayed by biological evolution, and ask whether computer simulations of evolution can produce the same kind of emergence as the open-ended evolution attested in Phanerozoic records. (shrink)

In this article, I consider the term “environment” in various claims and models by evolutionists and ecologists. I ask whether “environment” is amenable to a philosophical explication, in the same way some key terms of evolutionary theorizing such as “fitness,” “species,” or more recently “population” have been. I will claim that it cannot. In the first section, I propose a typology of theoretical terms, according to whether they are univocal or equivocal, and whether they have been the object of formal (...) or conceptual attempts of clarification. “Environment” will appear to be in a position similar to “population,” yet almost no extant attempt has been made to make sense of its meaning and reference. In the second section, I will present several theoretical claims or issues that refer to “environment” in apparently very diverse ways, but always supposing a contrastive term, which is not always the same. The third section directly considers models in evolution and in ecology, and asks “where” in them is the environment term. The fourth section proposes that “environment” refers to a distinction between a varying and an invariant term, but shows that this does not exhaust its meaning, which requires making more conceptual differences. Then, I take on the suggestion that there might be two “environment” terms, one in ecology and one in evolution, but show that is not the case. Finally I center on the specific notion of “complex environment,” which is the object of several research programs, and propose a typology of “complex environments” across theories. (shrink)

A popular goal in psychological science is to understand human cognition and behavior in the ‘real-world.’ In contrast, researchers have typically conducted their research in experimental research settings, a.k.a. the ‘psychologist’s laboratory.’ Critics have often questioned whether psychology’s laboratory experiments permit generalizable results. This is known as the ‘real-world or the lab’-dilemma. To bridge the gap between lab and life, many researchers have called for experiments with more ‘ecological validity’ to ensure that experiments more closely resemble and generalize to the (...) ‘real-world.’ However, researchers seldom explain what they mean with this term, nor how more ecological validity should be achieved. In our opinion, the popular concept of ecological validity is ill-formed, lacks specificity, and falls short of addressing the problem of generalizability. To move beyond the ‘real-world or the lab’-dilemma, we believe that researchers in psychological science should always specify the particular context of cognitive and behavioral functioning in which they are interested, instead of advocating that experiments should be more ‘ecologically valid’ in order to generalize to the ‘real-world.’ We believe this will be a more constructive way to uncover the context-specific and context-generic principles of cognition and behavior. (shrink)

This dissertation focuses on teleology and functions in biology. More precisely, it focuses on the scientific legitimacy of teleofunctional attributions and explanations in biology. It belongs to a multi-faceted debate that can be traced back to at least the 1970s. One aspect of the debate concerns the naturalization of functions. Most authors try to reduce, translate or explain functions and teleology in terms of efficient causes so that they find their place in the framework of the natural sciences. Our approach (...) here is radically different, as we question the premise that teleological explanations are disguised causal explanations. On the contrary, we defend that they are acceptable in natural sciences and in biology in particular. We challenge the idea that teleological explanations are immature causal explanations, as well as the idea that teleology and functions are some sort of intentional explanations. We therefore reject the accusations of anthropomorphism, vitalism and finalism. On the contrary, we defend that teleology, causality and intentionality correspond to different, autonomous and complementary modes of representation of the outside world. -/- ———[FRANÇAIS]——— -/- Ce travail de thèse porte sur la téléologie et les fonctions en biologie. Plus précisément, il porte sur la légitimité scientifique des attributions et des explications téléofonctionnelles en biologie. Il s’inscrit dans le cadre d’un débat à plusieurs facettes que l’on peut faire remonter au moins jusqu’aux années 1970 et qui est encore très actif aujourd’hui. L’un des aspects du débat porte sur la naturalisation des fonctions, c’est-à-dire sur la manière de les réduire, de les traduire ou de les expliciter en termes de causes efficientes de sorte qu’elles trouvent leur place dans le cadre des sciences de la nature. Notre approche ici est radicalement différente, car nous remettons en question la prémisse selon laquelle les explications téléologiques seraient des explications causales déguisées. Nous défendons au contraire qu’elles sont acceptables en tant que telles aussi bien de façon générale que dans le domaine scientifique et en particulier en biologie. De façon générale, nous remettons en question l’idée selon laquelle la pensée téléologique serait une pensée causale immature, ainsi que sa dépendance présumée vis-à-vis de la psychologie, c’est-à-dire de l’intentionnalité. Nous rejetons donc les accusations d’anthropomorphisme, de vitalisme et de finalisme formulées contre elle. Nous défendons au contraire que la téléologie, la causalité et l’intentionnalité correspondent à des modes différents, autonomes et complémentaires de représentation du monde extérieur. (shrink)

Early 20th century philosopher Henri Bergson posited an initial push that propelled the diversity of life forward into a varied, novel future: The élan vital, a necessary force or impulse that animated life’s progress and development. His idea had largely been abandoned by mid-century. Even so, much of the conceptual and explanatory work this impulse targeted is yet in want of an explanation. In particular, Bergson’s derelict ideas on evolution addressed three areas that have once again become relevant in the (...) effort to unite evolutionary genetics, biological development, and ecological context : the purposeful nature of individual organisms and their parts; the integrative, holistic, non-linear emergent dynamics seen in evolutionary processes; and how genuine novelty emerges into the universe :422, 2016; Simondon et al. in On the mode of existence of technical objects. Univocal series, Univocal Publishing LLC, Minneapolis, 2017; Bang, in: Winther-Lindqvist, Bang, Valsiner Nothingness: philosophical insights into psychology, Transaction Publishers, Somerset, 2016; Moreno and Mossio in Biological autonomy: a philosophical and theoretical enquiry. History, philosophy and theory of the life sciences, Springer, Dordrecht, 2015). In this paper I argue that Bergson’s ideas may yet be relevant to these questions, and his work warrants a reexamination in light of current problems in evolutionary biology. This is not a call to ‘return’ to Bergson, nevertheless his notions about complexity suggest ways of looking at current biological problems in ways that offer a heuristic insight worth entertaining. Bergson’s Nobel Prize-winning book, Creative Evolution, provided a strikingly prescient early 20th century framework for understanding how Darwinian evolution acts as an engine for generating new forms, University Press of America, Lanham, Bergson 1911). (shrink)

We present two case studies from contemporary biology in which we observe conflicts between established and emerging approaches. The first case study discusses the relation between molecular biology and systems biology regarding the explanation of cellular processes, while the second deals with phylogenetic systematics and the challenge posed by recent network approaches to established ideas of evolutionary processes. We show that the emergence of new fields is in both cases driven by the development of high-throughput data generation technologies and the (...) transfer of modeling techniques from other fields. New and emerging views are characterized by different philosophies of nature, i.e. by different ontological and methodological assumptions and epistemic values and virtues. This results in a kind of conflict we call “epistemic competition” that manifests in two ways: On the one hand, opponents engage in mutual critique and defense of their fundamental assumptions. On the other hand, they compete for the acceptance and integration of the knowledge they provide by a broader scientific community. Despite an initial rhetoric of replacement, the views as well as the respective audiences come to be seen as more clearly distinct during the course of the debate. Hence, we observe—contrary to many other accounts of scientific change—that conflict results in the formation of new niches of research, leading to co-existence and perceived complementarity of approaches. Our model thus contributes to the understanding of the pluralization of the scientific landscape. (shrink)

We propose a theoretical framework that highlights the most important consequences of complexity for the form and evolution of projects and use it to develop a typology of project complexity. This framework also enables us to deepen the understanding of how knowledge production and flexibility strategies enable project participants to address complexity. Based on this understanding, we advance a number of propositions regarding the strategies that can be most effective for different categories of complexity. These results contribute to the integration (...) of various strands in the research on project complexity and provide a roadmap for further research on the strategies for addressing it. (shrink)

The cybernetic definition of a living individual proposed previously (Korzeniewski, 2001) is very abstract and therefore describes the essence of life in a very formal and general way. In the present article this definition is reformulated in order to determine clearly the relation between life in general and a living individual in particular, and it is further explained and defended. Next, the cybernetic definition of a living individual is confronted with the real world. It is demonstrated that numerous restrictions imposed (...) on the cybernetic definition of life by physical reality imply a number of particular properties of life that characterize present life on Earth, namely: (1) a living individual must be a dissipative structure (and therefore a low-entropy thermodynamic system out of the state of equilibrium); (2) spontaneously-originated life must be based on organic compounds; (3) evolutionarily stable self-dependent, free-living individuals must have some minimal level of complexity of structure and function; (4) a living individual must have a record of identity separated from an executive machinery; (5) the identity of living individuals must mutate and may evolve; (6) living individuals may collect and accumulate information in subsequent generations over very long periods of time; (7) the degree of complexity of a living individual reflects the degree of complexity of its environment (ecological niche) and (8) living individuals are capable of supple adaptation to varying environmental conditions. Thus, the cybernetic definition of a living individual, when confronted with the real physical world, generates most of the general properties of the present life on Earth. (shrink)

Whatever we take “life” to mean, it must involve an attempt to describe the objective reality beyond scientists’ biases. Traditionally, this is thought to involve comparing our scientific categories to “natural kinds.” But this approach has been tainted with an implicit metaphysics, inherited from Aristotle, that does not fit biological reality. In particular, we must accept that biological categories will never be specifiable in terms of necessary and sufficient conditions or shared underlying physical structures that produce clean boundaries. Biology blurs (...) all lines and failure to embrace this unique feature has blocked attempts to reach consensus on the meaning of “life.” Thus, while the three classical accounts all fall short of offering a complete definition, their advocates fail to realize that they share the same view of life’s ultimate, functional hallmark: its uniquely rich adaptive capacity. I develop an account of life as adaptive capacity that sidesteps debates about the relative importance of specific mechanisms and the precise location of boundaries to bring the three classical accounts together under a shared conceptual framework. (shrink)

A common belief is that evolution generally proceeds towards greater complexity at both the organismal and the genomic level, numerous examples of reductive evolution of parasites and symbionts notwithstanding. However, recent evolutionary reconstructions challenge this notion. Two notable examples are the reconstruction of the complex archaeal ancestor and the intron‐rich ancestor of eukaryotes. In both cases, evolution in most of the lineages was apparently dominated by extensive loss of genes and introns, respectively. These and many other cases of reductive evolution (...) are consistent with a general model composed of two distinct evolutionary phases: the short, explosive, innovation phase that leads to an abrupt increase in genome complexity, followed by a much longer reductive phase, which encompasses either a neutral ratchet of genetic material loss or adaptive genome streamlining. Quantitatively, the evolution of genomes appears to be dominated by reduction and simplification, punctuated by episodes of complexification. (shrink)

Abstract Since modernity, the concept of subject supposes both an anthropocentric and a dualistic view of life and reality. In this study, we carry out an analytic interpretation of the Descartes’ notion of subject, in order to build a different dimension of the concept of subject. We discuss the activity of computing, as the manner by which the living subject relates with and in-forms the world. We further examine computing in the aging yeast as an example of living subject and (...) we try to comprehend the maturity of the subjectivity in Descartes’ res cogitans and in our proposed res computans . Content Type Journal Article Category Original Paper Pages 1-12 DOI 10.1007/s10516-011-9177-5 Authors María Belén Campero, Center of Philosophical Investigations, CONICET, Buenos Aires, Argentina Cristián Favre, Institute of Experimental Physiology, CONICET, School of Biochemical Sciences, University of Rosario, Suipacha 570, S2002LRL Rosario, Argentina Journal Axiomathes Online ISSN 1572-8390 Print ISSN 1122-1151. (shrink)

This paper discusses the benefits of describing the world as information, especially in the study of the evolution of life and cognition. Traditional studies encounter problems because it is difficult to describe life and cognition in terms of matter and energy, since their laws are valid only at the physical scale. However, if matter and energy, as well as life and cognition, are described in terms of information, evolution can be described consistently as information becoming more complex. The paper presents (...) five tentative laws of information, valid at multiple scales, which are generalizations of Darwinian, cybernetic, thermodynamic, and complexity principles. These are further used to discuss the notions of life and cognition and their evolution. (shrink)

Even though complexity is a concept that is ubiquitously used by biologists and philosophers of biology, it is rarely made precise. I argue that a clarification of the concept is neither trivial nor unachievable, and I propose a unifying framework based on the technical notion of “effective complexity” that allows me to do justice to conflicting intuitions about biological complexity, while taking into account several distinctions in the usage of the concept that are often overlooked. In particular, I propose a (...) distinction between two kinds of complexity, “mechanical” and “emergent”, which can be understood as different ways of relating the effective complexity of mechanisms and of behaviors in biological explanations. I illustrate the adequacy of this framework by discussing different attempts to understand intracellular organization in terms of pathways and networks. My framework provides a different way of thinking about recent philosophical debates, for example, on the difference between mechanistic and topological explanations and about the concept of emergence. Moreover, it can contribute to a proper assessment of metascientific arguments that invoke biological complexity. (shrink)

The pervasive use of computer simulations in the sciences brings novel epistemological issues discussed in the philosophy of science literature since about a decade. Evolutionary biology strongly relies on such simulations, and in relation to it there exists a research program (Artificial Life) that mainly studies simulations themselves. This paper addresses the specificity of computer simulations in evolutionary biology, in the context (described in Sect. 1) of a set of questions about their scope as explanations, the nature of validation processes (...) and the relation between simulations and true experiments or mathematical models. After making distinctions, especially between a weak use where simulations test hypotheses about the world, and a strong use where they allow one to explore sets of evolutionary dynamics not necessarily extant in our world, I argue in Sect. 2 that (weak) simulations are likely to represent in virtue of the fact that they instantiate specific features of causal processes that may be isomorphic to features of some causal processes in the world, though the latter are always intertwined with a myriad of different processes and hence unlikely to be directly manipulated and studied. I therefore argue that these simulations are merely able to provide candidate explanations for real patterns. Section 3 ends up by placing strong and weak simulations in Levins’ triangle, that conceives of simulations as devices trying to fulfil one or two among three incompatible epistemic values (precision, realism, genericity). (shrink)

In this article, I will discuss possible differences between ecosystems and organisms on the basis of their intrinsic complexity. As the concept of complexity still remains highly debated, I propose here a practical and original way to measure the complexity of an ecosystem or an organism. For this purpose, I suggest using the concept of logical depth (LD) in a specific manner, in order to take into account the difficulty as well as the time needed to generate the studied object. (...) I illustrate this method with fully controlled Daisyworld simulations (i.e., simulations based on the Gaia hypothesis) that have often been proposed to mimic living systems. The method consists of the following sequential stages: (1) identification of the shortest program able to numerically model the studied system (also called the Kolmogorov–Solomonoff complexity); (2) running the program, once if there are no stochastic components in the system, several times if stochastic components are there; and (3) computing the time needed to generate the system with LD complexity. This measure is supposed to estimate the system complexity. It appears in this study that LD estimations fit well with the intuition we have of complex systems, with higher complexities being found for more realistic Daisyworlds. With such a method of capturing the time needed to build a system, we expect to detect in future studies any quantified differences between complex ecosystems and organisms. (shrink)

Concepts of cause, choice, and information are closely related. A cause is a choice that can be held responsible. It is a difference that makes a difference. Information about past causes and their effects is a valuable commodity because it can be used to guide future choices. Information about criteria of choice is generated by choosing a subset from an ensemble for ‘reasons’ and has meaning for an interpreter when it is used to achieve an end. Natural selection evolves interpreters (...) with ends. Surviving genes embody a textual record of past choices that had favorable outcomes. Consultation of these archives guides current choices. Purposive choice is well-informed difference making. (shrink)

The common opinion has been that evolution results in the continuing development of more complex forms of life, generally understood as more complex organisms. The arguments supporting that opinion have recently come under scrutiny and been found wanting. Nevertheless, the appearance of increasing complexity remains. So, is there some sense in which evolution does grow complexity? Artificial life simulations have consistently failed to reproduce even the appearance of increasing complexity, which poses a challenge. Simulations, as much as scientific theories, are (...) obligated at least to save the appearances! We suggest a relation between these two problems, understanding biological complexity growth and the failure to model even its appearances. We present a different understanding of that complexity which evolution grows, one that genuinely runs counter to entropy and has thus far eluded proper analysis in information-theoretic terms. This complexity is reflected best in the increase in niches within the biosystem as a whole. Past and current artificial life simulations lack the resources with which to grow niches and so to reproduce evolution’s complexity. We propose a more suitable simulation design integrating environments and organisms, allowing old niches to change and new ones to emerge. (shrink)

Biologists rely heavily on the language of information, coding, and transmission that is commonplace in the field of information theory developed by Claude Shannon, but there is open debate about whether such language is anything more than facile metaphor. Philosophers of biology have argued that when biologists talk about information in genes and in evolution, they are not talking about the sort of information that Shannon’s theory addresses. First, philosophers have suggested that Shannon’s theory is only useful for developing a (...) shallow notion of correlation, the so-called causal sense of information. Second, they typically argue that in genetics and evolutionary biology, information language is used in a semantic sense, whereas semantics are deliberately omitted from Shannon’s theory. Neither critique is well-founded. Here we propose an alternative to the causal and semantic senses of information: a transmission sense of information, in which an object X conveys information if the function of X is to reduce, by virtue of its sequence properties, uncertainty on the part of an agent who observes X. The transmission sense not only captures much of what biologists intend when they talk about information in genes, but also brings Shannon’s theory back to the fore. By taking the viewpoint of a communications engineer and focusing on the decision problem of how information is to be packaged for transport, this approach resolves several problems that have plagued the information concept in biology, and highlights a number of important features of the way that information is encoded, stored, and transmitted as genetic sequence. (shrink)

Metaphysics in ecology? Ecosystem as a Complex Adaptive System: The metaphysical exploration regarding the origin and evolution of life is also present in ecology, however, does not refer to individual organisms, but entire ecological systems, such as ecosystems and the biosphere. Ecosystem can be considered as a Complex Adaptive System, consisted of numerous, diverse, and autonomous entities, connected by a dense network of interactions. The essential feature of complex systems is the ability to learn and to self-organization, which is a (...) result of adaptation to changes in the environment. Understanding the ecosystem structure and functioning as well as pathways of its evolution is one of the greatest challenges of modern ecology. Ecological studies are often dominated by the reductionist approach, whereby all aspects of life can be explained by physical, chemical, or molecular processes. However, studies on complex systems has shown that the rules describing these systems can not be derived from the basic principles; their behavior defies the basic laws of physics, and in fact is very difficult to predict. Moreover, some aspects of ecology related to the dynamics of living systems violate all the postulates of Newton. Interactions between particular components of a complex ecological systems are asymmetrical, casual, indeterminate, and non-linear. The evolution of the ecosystem can be explained by process ecology that reflects the natural tendency to self-organization of the complex system. The unpredictability of the behavior of complex systems and the inability to provide all the complex ecological processes within the framework of Newtonian dynamics has created a new space in the world that has so far appeared as closed, atomistic and determined. The space in which the reunion between science and faith is becoming increasingly possible. (shrink)

I investigate the relationship between adaptation, as defined in evolutionary theory through natural selection, and the concept of emergence. I argue that there is an essential correlation between the former, and “emergence” defined in the field of algorithmic simulations. I first show that the computational concept of emergence (in terms of incompressible simulation) can be correlated with a causal criterion of emergence (in terms of the specificity of the explanation of global patterns). On this ground, I argue that emergence in (...) general involves some sort of selective processes. Finally, I show that a second criterion, concerning novel explanatory regularities following the emergence of a pattern, captures the robustness of emergence displayed by some cases of emergence (according to the first criterion). Emergent processes fulfilling both criteria are therefore exemplified in evolutionary biology by some so-called “innovations”, and mostly by the new units of fitness or new kinds of adaptations (like sexual reproduction, multicellular organisms, cells, societies) sometimes called “major transitions in evolution”, that recent research programs (Maynard-Smith and Szathmary 1995 ; Michod 1999 ) aims at explaining. (shrink)

Any description of the emergence and evolution of different types of meaning processes (semiosis, sensu C.S.Peirce) in living systems must be supported by a theoretical framework which makes it possible to understand the nature and dynamics of such processes. Here we propose that the emergence of semiosis of different kinds can be understood as resulting from fundamental interactions in a triadically-organized hierarchical process. To grasp these interactions, we develop a model grounded on Stanley Salthe's hierarchical structuralism. This model can be (...) applied to establish, in a general sense, a set of theoretical constraints for explaining the instantiation of different kinds of meaning processes (iconic, indexical, symbolic) in semiotic systems. We use it to model a semiotic process in the immune system, namely, B-cell activation, in order to offer insights into the heuristic role it can play in the development of explanations for specific semiotic processes. (shrink)

Explaining the emergence of life is perhaps central and the most challenging question in modern science. Within this area of research, the emergence and evolution of the genetic code is supposed to be a critical transition in the evolution of modern organisms. The canonical genetic code is one of the most dominant aspects of life on this planet, and thus studying its origin is critical to understanding the evolution of life, including life’s emergence. In this sense it is possible to (...) view the ribosome as a digital-to-analogue information converter. Why the translation apparatus evolved, is one of the enduring mysteries of molecular biology. Assuming the hypothesis that during the emergence of life evolution had to first involve autocatalytic systems, which only subsequently acquired the capacity of genetic heredity, in the present article we discuss some aspects and causes of the possible emergence of digital, discrete information arising from analogue information realized in the intra- and inter-molecular interactions throughout molecular evolution. How such reverse translation was achieved at a molecular level is still unclear. The results of such debates and investigations might shift current biological paradigms and might also have a momentous significance for modern philosophy in understanding our place in the universe. (shrink)

The established definition of replication in terms of the conditions of causality, similarity and information transfer is very broad. We draw inspiration from the literature on self-reproducing automata to strengthen the notion of information transfer in replication processes. To the triple conditions of causality, similarity and information transfer, we add a fourth condition that defines a “generative replicator” as a conditional generative mechanism, which can turn input signals from an environment into developmental instructions. Generative replication must have the potential to (...) enhance complexity, which in turn requires that developmental instructions are part of the information that is transmitted in replication. Demonstrating the usefulness of the generative replicator concept in the social domain, we identify social generative replicators that satisfy all of the four proposed conditions. (shrink)

Germ cells are cross-roads of development and evolution. They define the origin of every new generation and, at the same time, represent the biological end-product of any mature organism. Germ cells are endowed with the following capacities: to store a self-descriptive program, to accumulate a protein-synthesizing machinery, and to incorporate enough nourishment to sustain embryonic development. To accomplish this goal, germ cells do not simply unfold a pre-determined program or realize a sole instructive role. On the contrary, due to the (...) complexity of their cytoarchitecture and the nature of the soma-to-germ interactions, they are heavily involved in processes of sign recognition and meaningful tissue exploration. At each stage of their inward migration, germ plasma membranes act as semiotic interfaces allowing cells to interact with the surrounding extracellular milieu and experience the compatibility of selected developmental sequences. The question of which signaling pathways are activated at each developmental stage does not result from a strictly predetermined program instructing germ cell stemness. Rather, each developmental sequence is an open-ended semiotic relationship explored and gradually defined during evolution by the context-dependency of specific cell-to-cell interactions. In this way, any structural and functional novelty that has emerged in the course of germ cell interactions may be interpreted as an exaptation fixed in the species genome in response to specific environmental constraints. (shrink)

In recent years a new conceptual tool called Complexity Theory has come to the attention of scientists and philosophers. This approach is concerned with the emergent properties of interacting systems. It has found wide applicability from cosmology to Social Structure Analysis. However, practitioners are still struggling to find the best way to define complexity and then to measure it. A new book Complexity and the arrow of time by Lineweaver et al. contains contributions from scholars who provide critical reviews of (...) Complexity Theory and its wider applications. This is a huge task and this essay examines how well the authors have succeeded in satisfying the claim made by the book’s three editors to have clarified the leading questions. I also explore the application of Complexity Theory to Biology as a means to explain the popular view that biological complexity has increased over time. In this regard, I conclude by recommending an Information Theory approach which urges that physical complexity arises from accumulation of genetic coding sequences. (shrink)