Contemporary complexity theory has been instrumental in providing novel rigorous definitions for some classic philosophical concepts, including emergence. In an attempt to provide an account of emergence that is consistent with complexity and dynamical systems theory, several authors have turned to the notion of constraints on state transitions. Drawing on complexity theory directly, this paper builds on those accounts, further developing the constraint-based interpretation of emergence and arguing that such accounts recover many of the features of more traditional accounts. We (...) show that the constraint-based account of emergence also leads naturally into a meaningful definition of self-organization, another concept that has received increasing attention recently. Along the way, we distinguish between order and organization, two concepts which are frequently conflated. Finally, we consider possibilities for future research in the philosophy of complex systems, as well as applications of the distinctions made in this paper. (shrink)

Climatology is a paradigmatic complex systems science. Understanding the global climate involves tackling problems in physics, chemistry, economics, and many other disciplines. I argue that complex systems like the global climate are characterized by certain dynamical features that explain how those systems change over time. A complex system's dynamics are shaped by the interaction of many different components operating at many different temporal and spatial scales. Examining the multidisciplinary and holistic methods of climatology can help us better understand the nature (...) of complex systems in general. -/- Questions surrounding climate science can be divided into three rough categories: foundational, methodological, and evaluative questions. "How do we know that we can trust science?" is a paradigmatic foundational question (and a surprisingly difficult one to answer). Because the global climate is so complex, questions like "what makes a system complex?" also fall into this category. There are a number of existing definitions of `complexity,' and while all of them capture some aspects of what makes intuitively complex systems distinctive, none is entirely satisfactory. Most existing accounts of complexity have been developed to work with information-theoretic objects (signals, for instance) rather than the physical and social systems studied by scientists. -/- Dynamical complexity, a concept articulated in detail in the first third of the dissertation, is designed to bridge the gap between the mathematics of contemporary complexity theory (in particular the formalism of "effective complexity" developed by Gell-Mann and Lloyd [2003]) and a more general account of the structure of science generally. Dynamical complexity provides a physical interpretation of the formal tools of mathematical complexity theory, and thus can be used as a framework for thinking about general problems in the philosophy of science, including theories, explanation, and lawhood. -/- Methodological questions include questions about how climate science constructs its models, on what basis we trust those models, and how we might improve those models. In order to answer questions about climate modeling, it's important to understand what climate models look like and how they are constructed. Climate model families are significantly more diverse than are the model families of most other sciences (even sciences that study other complex systems). Existing climate models range from basic models that can be solved on paper to staggeringly complicated models that can only be analyzed using the most advanced supercomputers in the world. I introduce some of the central concepts in climatology by demonstrating how one of the most basic climate models might be constructed. I begin with the assumption that the Earth is a simple featureless blackbody which receives energy from the sun and releases it into space, and show how to model that assumption formally. I then gradually add other factors (e.g. albedo and the greenhouse effect) to the model, and show how each addition brings the model's prediction closer to agreement with observation. After constructing this basic model, I describe the so-called "complexity hierarchy" of the rest of climate models, and argue that the sense of "complexity" used in the climate modeling community is related to dynamical complexity. -/- With a clear understanding of the basics of climate modeling in hand, I then argue that foundational issues discussed early in the dissertation suggest that computation plays an irrevocably central role in climate modeling. "Science by simulation" is essential given the complexity of the global climate, but features of the climate system--the presence of non-linearities, feedback loops, and chaotic dynamics--put principled limits on the effectiveness of computational models. This tension is at the root of the staggering pluralism of the climate model hierarchy, and suggests that such pluralism is here to stay, rather than an artifact of our ignorance. Rather than attempting to converge on a single "best fit" climate model, we ought to embrace the diversity of climate models, and view each as a specialized tool designed to predict and explain a rather narrow range of phenomena. Understanding the climate system as a whole requires examining a number of different models, and correlating their outputs. This is the most significant methodological challenge of climatology. -/- Climatology's role contemporary political discourse raises an unusually high number of evaluative questions for a physical science. The two leading approaches to crafting policy surrounding climate change center on mitigation (i.e. stopping the changes from occurring) and adaptation (making post hoc changes to ameliorate the harm caused by those changes). Crafting an effective socio-political response to the threat of anthropogenic climate change, however, requires us to integrate multiple perspectives and values: the proper response will be just as diverse and pluralistic as the climate models themselves, and will incorporate aspects of both approaches. I conclude by offering some concrete recommendations about how to integrate this value pluralism into our socio-political decision making framework. (shrink)

Complexity theory attempts to explain, at the most general possible level, the interesting behaviors of complex systems. Two such behaviors are the emergence of simple or stable high-level behavior from relatively complex low-level behavior, and the emergence of sophisticated high-level behavior from relatively simple low-level behavior; they are often found nested in the same system. Concerning the emergence of simplicity, this essay examines Herbert Simon's explanation from near-decomposability and a stochastic explanation that generalizes the approach of statistical physics. A more (...) general notion of an abstract difference-making structure is introduced with examples, and a discussion of evolvability follows. Concerning the emergence of sophistication, this essay focuses on, first, the energetics approach associated with dissipative structures and the fourth law of thermodynamics, and second, the notion of a complex adaptive system. (shrink)

In this contribution, I comment on Raffaella Campaner’s defense of explanatory pluralism in psychiatry (in this volume). In her paper, Campaner focuses primarily on explanatory pluralism in contrast to explanatory reductionism. Furthermore, she distinguishes between pluralists who consider pluralism to be a temporary state on the one hand and pluralists who consider it to be a persisting state on the other hand. I suggest that it would be helpful to distinguish more than those two versions of pluralism – different understandings (...) of explanatory pluralism both within philosophy of science and psychiatry – namely moderate/temporary pluralism, anything goes pluralism, isolationist pluralism, integrative pluralism and interactive pluralism. Next, I discuss the pros and cons of these different understandings of explanatory pluralism. Finally, I raise the question of how to implement or operationalize explanatory pluralism in scientific practice; how to structure the “genuine dialogue” or shape “the pluralistic attitude” Campaner is referring to. As tentative answers, I explore a question-based framework for explanatory pluralism as well as social-epistemological procedures for interaction among competing approaches and explanations. (shrink)

In this paper, I discuss the concept of complexity. I show that the principle of natural selection as acting on complexity gives a solution to the problem of reconciling the seemingly contradictory notion of generally increasing complexity and the observation that most species don’t follow such a trend. I suggest the process of evolution to be illustrated by means of a schematic diagram of complexity versus time, interpreted as a form of the Tree of Life. The suggested model implies that (...) complexity is cumulatively increasing, giving evolution a direction, an arrow of time, thus also implying that the latest emerging species will be the one with the highest level of complexity. Since the human species is the last species evolved in the evolutionary process seen at large, this means that we are the species with the highest complexity. The model implies that the human species constitutes an integral part of organic evolution, yet rendering us the exclusive status as the species of the highest complexity. (shrink)

This article contends that the evolution toward interdisciplinary collaboration that we are witnessing in the sciences must also occur in the humanities to ensure their very survival. That is, humanists must be open to working with scientists and social scientists interested in similar research questions and vice versa. Digital humanities is a positive first step. Complexity science should be the next step. Even though much of the ground-breaking work in complexity science has been done in the natural sciences and mathematics, (...) it can, if critically adapted, provide the needed metaphor for a broad integration of disciplines, humanistic and otherwise. Given its almost a-disciplinary nature, a complexity approach to the research problems in the humanities necessarily breaks down silos. Moreover, it can restore and reframe the seamless intellectual fabric sought by researchers before the atomization of the various disciplines in the nineteenthcentury academy. (shrink)

Many of the existing ethical analyses of genetic engineering technologies (GET) focus on how they can be used to enhance individuals—to improve individual well-being, health and cognition. There is a gap in the current literature about the specific ways enhancement technologies could be used to improve our populations and species, viewed as a whole. In this paper, I explore how GET may be used to enhance the species through improvements in the gene pool. I argue one aspect of the species (...) that may be desirable to enhance is ‘persistence’ or long-term viability. I then look at some of the ways in which GET could be used to improve human persistence and argue that the use of GET to secure benefits for individuals may compromise persistence. This suggests conflicts between uses of GET to enhance individuals and uses to promote the persistence of the species may occur. As GET are further developed, the likelihood that these conflicts will actually arise, and how we should resolve them if they do, will need to be considered. (shrink)

(This version was submitted to Behavioral and Brain Science. A revised version was published by Biological Theory) Estimates of autism’s incidence increased 5-10 fold in ten years, an increase which cannot be genetic. Though many mutations are associated with autism, no mutation seems directly to cause autism. We need to find the direct cause. Complexity science provides a new paradigm - confirmed in biology by extensive hard data. Both the body and the personality are complex dynamic systems which spontaneously self-organize (...) from simple dynamic systems. Autism may therefore be caused by the failure of a simple dynamic system. We know that infants who cannot track their mother’s face often become autistic, that eye-contact initiates intersubjectivity which is blocked in autism, and that the infant-mother pair seems designed to promote eye-contact, as does the eye’s appearance. This author earlier proposed that failure of eye-contact might directly cause autism and that early non-maternal childcare, including television/video, would therefore be statistically linked to autism. Waldman et al. (2008; 2006) recently proved that autism is strongly linked to precipitation (indoor activity) and to the introduction of cable. The most plausible explanation? Early exposure to television/video is linked to autism. Furthermore a normal developmental cascade (blocked in autism) has been deciphered: (a) Infant-mother eye-contact triggers increased maternal attention. (b) Early maternal attention permanently increases not only baseline vasopressin but also that oxytocin release which is triggered by subsequent maternal attention. (c) Vasopressin and oxytocin promote face recognition, gazing-at-the-eyes, emotion recognition, and social bonding. The eye-contact hypothesis suggests a clinical study addressing prevention: recruit prospective parents who agree to curtail television/video/computer/wi-fi in their families; measure autism’s incidence in their children. (shrink)

This article provides an analysis of how the philosophy of Aristotle and St. Thomas Aquinas, particularly their treatment of the "Problem of the One and the Many," can help inform Sam Harris's attempt to ground ethics in the empirical sciences in his 2010 book The Moral Landscape: How Science Can Determine Human Values. -/- The paper shows how Aristotle and Aquinas's thought can: • Explaining how the sciences are organized and why they will not produce multiple, competing measures of goodness (...) and well-being; • Resolving the “moral paradoxes” that Harris finds himself unable to find a solution to, by demonstrating how the human good essentially involves a “common good,” and how goodness always relates to the whole; • Providing us with a better explanation for why selfless behavior is good and why it is “good for us” to be virtuous; • Providing Harris with a better definition of freedom as self-determination; and • Showing how neither a recognition that the sciences must play a major role in ethics, nor naturalistic explanations of human behavior, need to preclude our orientation towards a transcendent good. (shrink)

This paper explores the evolution of consciousness and subjectivity through a biological framework for understanding the universe. It posits that functional patterns in biological systems mirror cosmic mathematical principles, defining our objective reality. Similar to wave and Fibonacci patterns in different physical phenomena, biological patterns are intrinsic to all things and can be quantified using Dedre Gentner’s approach to analogy. For example, Earth’s ocean currents and the melting and freezing of Antarctica resemble the circulatory system and heart, while the production (...) of music from instruments is analogous to ribosomal protein synthesis. Shelves, tables, and chairs function like cytosol by holding objects in space, and a coffee cup mirrors red blood cell distribution. These analogies reveal a universal order rooted in biology’s functional patterns, essential for shaping the emergence and evolution of life. The paper traces the development of consciousness from its rudimentary cellular states to complex human cognition, highlighting the role of biologically-patterned environments in driving evolutionary changes. Organisms that recognized and organized according to these patterns evolved as “pattern recognition engines” crucial for survival—thus, Life (survival) being the primary measure of consciousness. Humans advanced this capacity, gaining cognitive freedom by insulating themselves from environmental constraints, but faced increased subjectivity complexity. Consciousness, while inherently subjective and necessary for cognitive development, evolves in humans to understand objective reality and its biological nature, so to understand and navigate complexities of subjectivity. Ultimately, the paper asserts consciousness is the ability to recognize and adhere to life-sustaining patterns and principles. Successful adherence deems them worthy of continued existence, while failure leads to demise. Parallels with historical concepts like Atman and Brahman in Hinduism suggest ancient recognition of the correspondence between human and universal patterns. This ancient understanding, coupled with modern scientific evidence, reveals the interconnectedness and intrinsic biological nature of reality. (shrink)

The mathematical universe hypothesis is a theory that the physical universe is not merely described by mathematics, but is mathematics, specifically a mathematical structure. Our research provides evidence that the mathematical structure of the universe is biological in nature and all systems, processes, and objects within the universe function in harmony with biological patterns. Living organisms are the result of the universe’s biological pattern and are embedded within their physiology the patterns of this biological universe. Therefore physiological patterns in living (...) organisms can be used as models to structurally map analogies from the biological domain to any target domain to reveal and understand the biological nature of the target domain. Our paper explores various analogies, structurally mapping a red blood cell to a cup; proteins produced from ribosomes to music produced from instruments; a beating heart to the melting and freezing of Antartica; cells, tissue, organs and blood, to people, organizations, industries, and money, and; bio-economic concepts in cellular society to socioeconomic concepts in human society. It also discusses how phenomena in cellular mitosis can help explain phenomena in the universe, such as black holes, dark matter, dark energy, and the structure of the universe. Building upon the concept of perennial wisdom, our research has provided evidence that the ideas of a biological universe were expressed across many past cultures and historical periods. The implications of this theory are vast, encompassing fields such as physics, science, philosophy, religion, law, economics, politics, and engineering, thus serving as a unifying theory for all knowledge. Our theory is supported by meta-analysis of scientific, historic, and religious literature, observations and first principles logic. (shrink)

Bhaskar's philosophy supports society via a process of homeostasis to resist socioecological system disintegration by developing its values and ethics in response to endogenous and exogenous change. To the contrary, positivist (first generation) and hermeneuticist (second generation) approaches to systems theory have distorted humanity's mechanism of homeostasis because, amongst other things, they disallow the use of facts to guide values/actions. Since acting on knowledge is, ceteris paribus, a given in Bhaskar's approach, resolving socioecological system problems involves correcting the method of (...) homeostasis (our method of finding knowledge and acting on it) rather than correcting the consequences of the failure of homeostasis (the poorly informed action or inaction). This is reminiscent of Gandhi's approach to social transformation in which we trust the means to arrive at appropriate ends and it releases activists from having to be keepers of the moral high-ground or having to try to change people's behaviour. (shrink)

There is growing need for hybrid curricula that integrate constructivist methods from Science and Technology Studies (STS) into both engineering and policy courses at the undergraduate and graduate levels. However, institutional and disciplinary barriers have made implementing such curricula difficult at many institutions. While several programs have recently been launched that mix technical training with consideration of “societal” or “ethical issues,” these programs often lack a constructivist element, leaving newly-minted practitioners entering practical fields ill-equipped to unpack the politics of knowledge (...) and technology or engage with skeptical publics. This paper presents a novel format for designing interdisciplinary coursework that combines conceptual content from STS with training in engineering and policy. Courses following this format would ideally be team taught by instructors with advanced training in diverse fields, and hence co-learning between instructors and disciplines is a key element of the format. Several instruments for facilitating both student and instructor collaborative learning are introduced. The format is also designed for versatility: in addition to being adaptable to both technical and policy training environments, topics are modularized around a conceptual core so that issues ranging from biotech to nuclear security can be incorporated to fit programmatic needs and resources. (shrink)

In their recent book, Ladyman and Wiesner (What is a complex system?, Yale University Press, 2020) delineate the bounds of the exciting interdisciplinary field of complexity science. In this work, they provide examples of generally accepted complex systems and common features which these possess to varying degrees. In this paper, I plan to extend their list to include the formal study of natural language, i.e. linguistics. In fact, I will argue that language exhibits many of the hallmarks of a complex (...) system, specifically a complex biological system. Thus, my aim is to advocate contra the the ‘Minimalist Program’ (Chomsky, The minimalist program, MIT Press, Cambridge, 1995), which motivates simple underlying mechanisms (i.e. Merge) in their idealisations, that biolinguistics should embrace a ‘Maximalist Program’ in which multiple subfields contribute component explanations to an emerging whole. (shrink)

Los conceptos de evolución y cambio evolutivo son a la vez laxos y polisémicos: se aplican a fenómenos muy diferentes y no siempre se definen con precisión. La aplicación extendida del paradigma neo-darwinista clásico, además, suele imponer un esquema adaptacionista al análisis de los hechos evolutivos, en el cual las funciones juegan un papel lógicamente anterior a los rasgos y sus formas. En este artículo proponemos, como etapa previa a la formulación de hipótesis sobre las causas del cambio, un modelo (...) de espacio forma-función que pueda responder a preguntas como cuándo se da un cambio en los rasgos de una arquitectura biológica y de qué tipo son estos cambios. Un modelo de este tipo nos permite ver claramente cuándo se da un cambio en la forma o en la función y qué alcance evolutivo tiene. (shrink)

The book’s core argument is that an artificial intelligence that could equal or exceed human intelligence—sometimes called artificial general intelligence (AGI)—is for mathematical reasons impossible. It offers two specific reasons for this claim: Human intelligence is a capability of a complex dynamic system—the human brain and central nervous system. Systems of this sort cannot be modelled mathematically in a way that allows them to operate inside a computer. In supporting their claim, the authors, Jobst Landgrebe and Barry Smith, marshal evidence (...) from mathematics, physics, computer science, philosophy, linguistics, and biology, setting up their book around three central questions: What are the essential marks of human intelligence? What is it that researchers try to do when they attempt to achieve "artificial intelligence" (AI)? And why, after more than 50 years, are our most common interactions with AI, for example with our bank’s computers, still so unsatisfactory? Landgrebe and Smith show how a widespread fear about AI’s potential to bring about radical changes in the nature of human beings and in the human social order is founded on an error. There is still, as they demonstrate in a final chapter, a great deal that AI can achieve which will benefit humanity. But these benefits will be achieved without the aid of systems that are more powerful than humans, which are as impossible as AI systems that are intrinsically "evil" or able to "will" a takeover of human society. (shrink)

Throughout most of the 20th century, analytical and reductionist approaches have dominated in biological, social, and humanistic sciences, including linguistics and communication. We generally believed we could account for fundamental phenomena in invoking basic elemental units. Although the amount of knowledge generated was certainly impressive, we have also seen limitations of this approach. Discovering the sound formants of human languages, for example, has allowed us to know vital aspects of the ‘material’ plane of verbal codes, but it tells us little (...) about significant aspects of their social functions. I firmly believe, therefore, that alongside a linguistics that looks ‘inward’ there should also be a linguistics that looks ‘outward’, or one even that is constructed ‘from the outside’, a linguistics that I refer to elsewhere as ‘holistic’ though it could be identified by a different name. My current vision is to promote simultaneously the perspective that goes from the part to the whole and that which goes from the whole to the parts, i.e., both from the top down and from the bottom up. This goal is shared with other disciplines which recognize that many phenomena related to life are interwoven, self-organising, emergent and processual. Thus, we need to re-examine how we have conceived of reality, both the way we have looked at it and the images we have used to talk about it. Several approaches now grouped under the label of complexity have been elaborated towards this objective of finding new concepts and ways of thinking that better fit the complex organisation of facts and events. (shrink)

This paper reviews the contemporary discussion on the epistemological and ontological effects of Big Data within social science, observing an increased focus on relationality and complexity, and a tendency to naturalize social phenomena. The epistemic limits of this emerging computational paradigm are outlined through a comparison with the discussions in the early days of digitalization, when digital technology was primarily seen through the lens of dematerialization, and as part of the larger processes of “postmodernity”. Since then, the online landscape has (...) become increasingly centralized, and the “liquidity” of dematerialized technology has come to empower online platforms in shaping the conditions for human behavior. This contrast between the contemporary epistemological currents and the previous philosophical discussions brings to the fore contradictions within the study of digital social life: While qualitative change has become increasingly dominant, the focus has gone towards quantitative methods; while the platforms have become empowered to shape social behavior, the focus has gone from social context to naturalizing social patterns; while meaning is increasingly contested and fragmented, the role of hermeneutics has diminished; while platforms have become power hubs pursuing their interests through sophisticated data manipulation, the data they provide is increasingly trusted to hold the keys to understanding social life. These contradictions, we argue, are partially the result of a lack of philosophical discussion on the nature of social reality in the digital era; only from a firm metatheoretical perspective can we avoid forgetting the reality of the system under study as we are affected by the powerful social life of Big Data. (shrink)

Darwin’s claim that Natural Selection, through optimization of fitness, explains complex biological design has not yet been properly formalized. Alan Grafen’s Formal Darwinism Project aims at providing such a formalization and at demonstrating that fitness maximization is coherent with results from Population Genetics, usually interpreted as denying it. We suggest that Grafen’s proposal suffers from some limitations linked to its concept of design as optimized fitness. In order to overcome these limitations, we propose a classification of evolutionary facts based on (...) a bi-dimensional complexity space, which adds robustness to fitness as measure of the quality of a design. In this space, each point represents an organismic architecture, and movement between two points would be an evolutionary fact. Natural Selection explains movement along the fitness axis, while non-selective mechanisms explain movement on the robustness axis. Moreover, we propose a thermodynamic metaphor to draw parallelisms between notions of fitness and entropy, robustness and energy, and movement in this space and reversible and irreversible cycles. We argue that this metaphor illustrates different evolutionary processes usually overlooked by proposals of formalization of Darwinian theory, such Grafen’s Formal Darwinism Project. (shrink)

This transdisciplinary doctoral thesis presents various theoretical, methodological and empirical approaches that together form an ecological approach to the study of social sciences. The key argument follows: to understand how sustainable behaviours and cultures may emerge, and how their development can be facilitated, we must further learn how behaviours emerge as a function of the person and the material and social environment. Furthermore, in this thesis the sustainability crises are framed as sustain-ability crises. We must better equip our cultures with (...) abilities to deal with the complexity and uncertainty of socio-ecological systems, and use these cultural skillsets to survive in and adapt to an increasingly unpredictable world. This thesis employs a plurality of ecological social sciences and related methodologies—such as ecological psychology, ecological rationality and agent-based modelling—to enlighten the question of how the collective adoption of sustainable behaviours can be leveraged, particularly by changing the affordances in the material environment. What is common to these ecological approaches is the appreciation of ‘processes’ over ‘products’: we must understand the various processes through which sustainable forms of behaviour or decision-making emerge to truly locate leverage points in social systems. Finally, this thesis deals extensively with uncertainty in complex systems. It proposes that we can look to local and traditional knowledge in learning how to deal adaptively with uncertainty. (shrink)

To reach sustainability transitions, we must learn to leverage social systems into tipping points, where societies exhibit positive-feedback loops in the adoption of sustainable behavioral and cultural traits. However, much less is known about the most efficient ways to reach such transitions or how self-reinforcing systemic transformations might be instigated through policy. We employ an agent-based model to study the emergence of social tipping points through various feedback loops that have been previously identified to constitute an ecological approach to human (...) behavior. Our model suggests that even a linear introduction of pro-environmental affordances (action opportunities) to a social system can have non-linear positive effects on the emergence of collective pro-environmental behavior patterns. We validate the model against data on the evolution of cycling and driving behaviors in Copenhagen. Our model gives further evidence and justification for policies that make pro-environmental behavior psychologically salient, easy, and the path of least resistance. (shrink)

This article attempts to show why an experimental hypothesis is plausible and merits testing; in brief, the hypothesis is that autism begins with a failure in early learning and that changing the environment of early learning would dramatically change its incidence. Strong statistical evidence supporting this hypothesis has been published by Waldman et al., but to date this evidence has largely been ignored, perhaps because it challenges prevalent beliefs about autism. This article also suggests that the current epidemic of autism (...) is serious enough, and intellectually mysterious enough, to merit attention from a wider community of brain scientists: New ideas are needed. A confirmation of this article’s hypothesis would have interesting implications for brain science. (shrink)

In the methodology of scientific research programs (MSRP) there are important features on the problem of prediction, especially regarding novel facts. In his approach, Imre Lakatos proposed three different levels on prediction: aim, process, and assessment. Chapter 5 pays attention to the characterization of prediction in the methodology of research programs. Thus, it takes into account several features: (1) its pragmatic characterization, (2) the logical perspective as a proposition, (3) the epistemological component, (4) its role in the appraisal of research (...) programs, and (5) its place as a value for scientific research. -/- The notion of “novel facts” is highly relevant in his conception, where several aspects are involved: the directions of novel facts, the different kinds of novelty, and the transition from six possible options of “novel facts” to four choices. Thereafter, the prediction of novel facts as the criterion of appraisal is considered. On the one hand, this requires analyzing the theoretical, empirical, and heuristic possibilities of appraisal; and, on the other, whether there is an overemphasis on the role of prediction in methodology of scientific research programs. As a consequence, there is an analysis of Lakatos’ criterion of appraisal in MSRP and economics. (shrink)

Since the foundation of the Santa Fe Institute, the new science of complex adaptive systems has seen extraordinary development, breaking with previous, more epistemological, trends in complexity theory. This article makes a critique of CAS as a model of the current global complexity. Its basic model, the cellular automaton, which focuses on the interactive dynamics among components, ignores the nature of any complex system as constructed by the observer/actor and is unable to explain the sociohistorical construction of the agents/subjects and (...) the social structure in which they are located, thus being unable to accurately represent the overall social complexity. (shrink)

Argues that truth, moral right, political right, and aesthetic value may be understood as arising out of a naturalist account of humanity, if naturalism is rightly conceived.

This dissertation argues that cognition is a kind of natural agency. Natural agency is the capacity that certain systems have to act in accordance with their own norms. Natural agents are systems that bias their repertoires in response to affordances in the pursuit of their goals. Cognition is a special mode of this general phenomenon. Cognitive systems are agents that have the additional capacity to actively take their worlds to be certain ways, regardless of whether the world is really that (...) way. In this way, cognitive systems are desituated. Desituatedness is the root of specifically cognitive capacities for representation and abstraction. There are two main reasons why this view needs defending. First, natural agency is typically viewed as incompatible with natural science because it is committed to a teleological mode of explanation. Second, cognition is typically held to be categorically distinct from natural agency. This dissertation argues against both of these views. It argues against the incompatibility of agency and natural science by demonstrating that systems biology, general systems theory, and sciences that deal with complex systems have typically underappreciated conceptual and theoretical resources for grounding agency in the causal structure of the world. These conceptual resources do not, however, reduce agency to systems theory because the normativity inherent in agency demands descriptive resources beyond those of even the most sophisticated systems theory. It argues against the categorical difference between natural agency and cognition by pointing out that separating cognition from a richer web of situated, ecologically embedded relations between the agent and the world generates the frame problem, which is an insuperable obstacle to making cognition that is sufficiently responsive to the complexity of the world. Rooting cognition in natural agency is a more robust empirical bet for theorizing cognition and artificial intelligence. (shrink)

The modern social world is unjust. It is also complex. What does this latter fact imply about the kind of approach that should be used in ameliorating the injustice expressed in the former fact? One answer, recently put forth by Jacob Barrett, is that _ideal theory_, which he understands as being fundamentally defined by the identification and subsequent pursuit of an aspirational macro-level institutional goal, lacks a place in social reform. The reason he thinks ideal theory lacks a place has (...) to do with its inability to deal with complexity. _Pace_ Barrett, I argue that ideal theory, suitably understood, can play a valuable role in social reform in a complex world. While some ideal theorists have underappreciated the extent to which complexity considerations complicate social reform, this does not mean that there is no place for it. This paper surveys the resources ideal theory has available to cope with what I call _the challenge of complexity_. Although the coping techniques will be successful to varying degrees, I believe, in aggregate, a compelling case can be made that ideal theory can combat the challenge of complexity. Still, one may worry that even if ideal theory can adequately deal with complexity, it cannot adequately deal with ever-changing social circumstances. Call this _the dancing landscape objection_. A static ideal theory cannot overcome it, but a _dynamic ideal theory_ could. In sum, dynamic ideal theory can contribute to social reform in a complex and mutable social world. (shrink)

Successful instances of interdisciplinary collaboration can eventually enter a process of disciplinarisation. This article analyses one of those instances: agent-based computational social science, an emerging disciplinary field articulated around the use of computational models to study social phenomena. The discussion centres on how, in knowledge transfer dynamics from traditional disciplinary areas, practitioners parsed several epistemic resources to produce new foundational disciplinary shared commitments, and how disagreements operated as a mechanism of differentiation in their production. Two parsing processes are examined to (...) illustrate this claim. The first one is the parsing of the qualitative–quantitative dualism, arguably the most important methodological disagreement in social science. The second one is the parsing of prediction, a key value in contemporary science. The analysis evidences that disagreements have fostered both external and internal dynamics of differentiation in agent-based computational social science. The former have permitted a more efficient use of epistemic resources, whereas the latter have forced practitioners to modify the foundational narrative and the agenda of the field. (shrink)

In liberal modernity, the democratic collective will of society was understood to emerge through the public and deliberative freedoms of associational life. Today, however, democratic discourse is much more focused on the formation of plural and diverse publics in the private and social sphere. In these ‘non-linear’ approaches, democracy is no longer seen to operate to constitute a collective will standing above society but as a mechanism to distribute power more evenly through the social empowerment of individuals and communities as (...) the ultimate decision-makers. Government is brought back ‘to the people’ and democracy is seen to circulate through the personal decisions made in everyday life. This article seeks to analyse the development of non-linear approaches to the political sphere, which seek to overcome the rationalist assumptions of the public/private divide, paying particular attention to the work of two key liberal theorists, John Dewey and Friedrich von Hayek. (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)

This essay argues that scientific systems have two main functions typical to self-organising adaptive and complex systems: Exploration for and exploitation of information. The self-organising nature, or spontaneous order, of scientific systems was prominently conceived by polymath Michael Polanyi. Revisiting Polanyi’s philosophy of science reveals why scientific freedom is still today as important a value as ever, even though the notion of “freedom” itself must be revised. Namely, freedom of inquiry should serve to maintain a diverse and adaptive balance between (...) exploration and exploitation. This essay argues that current trends within science policy and scientific communities, from impact assessments to targeted research funding, are often inherently biased towards advancing exploitative functions over explorative activities. Concerns are raised over whether these exploitative biases suppress the explorative nature of scientific inquiry, and thus disturb the self-organisation of scientific systems by favouring hasty and sometimes negligent exploitation. Further concerns are raised as to whether these impaired adaptive capacities of scientific systems lead to reduced resilience of broader society. Finally, Polanyi’s vision of a Society of Explorers, where free exploration is vindicated and safeguarded, is revived in a 21st century context. (shrink)

Biological systems are highly complex, and for this reason there is a considerable degree of uncertainty as to the consequences of making significant interventions into their workings. Since a number of new technologies are already impinging on living systems, including our bodies, many of us have become participants in large-scale “social experiments”. I will discuss biological complexity and its relevance to the technologies that brought us BSE/vCJD and the controversy over GM foods. Then I will consider some of the complexities (...) of our social dynamics, and argue for making a shift from using the precautionary principle to employing the approach of evaluating the introduction of new technologies by conceiving of them as social experiments. (shrink)

In the paper we consider an electricity provider company that makes decision on allocating resources on electric network maintenance. The investments decrease malfunction rate of network nodes. An accidental event or a malfunctioning on underground system can have various consequences and in different perspectives, such as deaths and injuries of pedestrians, fires in nearby locations, disturbances in the flow of vehicular traffic, loss to the company image, operating and financial losses, etc. For this reason it is necessary to apply an (...) approach of the risk management that considers the multidimensional view of the consequences. Furthermore an analysis of decision making should consider network dependencies between the nodes of the electricity distribution system. In the paper we propose the use of the simulation to assess the network effects in the multidimensional risk assessment in electricity grid. The analyzed effects include node overloading due to malfunction of adjacent nodes and blackouts that take place where there is temporarily no path in the grid between the power plant and a node. The simulation results show that network effects have crucial role for decisions in the network maintenance – outcomes of decisions to repair a particular node in the network can have significant influence on performance of other nodes. However, those dependencies are non-linear. The effects of network connectivity on its multidimensional performance assessment depend heavily on the overloading effect level. The simulation results do not depend on network type structure – however simulation outcomes for random networks have shown higher variance compared to small-world networks. (shrink)

A systematic theory of naturalism, bridging metaphysics and the science of complexity and emergence.

These preprints were automatically compiled into a PDF from the collection of papers deposited in PhilSci-Archive in conjunction with the PSA 2012.

The mass popular dissent which has marked the early twenty-first century, from al-Qaeda to the Arab Spring to the Occupy movement, can be read as expressions of collective, subjective, existential mutation. This reading is inspired by Félix Guattari, who described the 1979 Iranian revolution, the Polish Solidarity movement and the 1989 Chinese student demonstrations as demands for subjective singularisation. In each of these examples of social discontent, past and present, demands vary widely even within the same movement, spanning economics, lifestyle, (...) religion and politics, and ranging from cries for liberation to conservative returns to ancient tradition. In order to perform a schizoanalysis of such amorphous movements, Guattari developed a four-part ecosophic object, composed of existential Territories, Universes of value, material-energetic Flows and machinic Phyla. Assemblages can be dynamically mapped along these four dimensions. Of crucial importance in the age of extreme deterritorialisation is the existential Territory, which could potentially take the form of a homeland based on poetry or music rather than on ethnicity or even place. Such portable homelands would characterise the dissensual processual post-media era for which Guattari longed. (shrink)

Cellular automata (henceforth: CA) are discrete, abstract computational systems that have proved useful both as general models of complexity and as more specific representations of non-linear dynamics in a variety of scientific fields. Firstly, CA are (typically) spatially and temporally discrete: they are composed of a finite or denumerable set of homogeneous, simple units, the atoms or cells. At each time unit, the cells instantiate one of a finite set of states. They evolve in parallel at discrete time steps, following (...) state update functions or dynamical transition rules: the update of a cell state obtains by taking into account the states of cells in its local neighborhood (there are, therefore, no actions at a distance). Secondly, CA are abstract, as they can be specified in purely mathematical terms and implemented in physical structures. Thirdly, CA are computational systems: they can compute functions and solve algorithmic problems. Despite functioning in a different way from traditional, Turing machine-like devices, CA with suitable rules can emulate a universal Turing machine, and therefore compute, given Turing's Thesis, anything computable.... (shrink)

The task of designing effective economic and political institutions requires substantial foresight. The designer must anticipate not only the behavior of individual actors, but also how that behavior will aggregate. Rising complexity brought about by increases in speeds of adaptation, diversity, connectedness, and interdependence make institutional design all the more challenging. Given the focus on equilibria, the extant literature on mechanism design might appear incapable of coping with this complexity. Yet, I suggest that a deeper engagement with the origins of (...) the mechanism-design framework reveals insights that may help us design robust, adaptive institutions that can harness complexity. (shrink)

In some areas of cognitive science we are confronted with ultrafast cognition, exquisite context sensitivity, and scale-free variation in measured cognitive activities. To move forward, we suggest a need to embrace this complexity, equipping cognitive science with tools and concepts used in the study of complex dynamical systems. The science of movement coordination has benefited already from this change, successfully circumventing analogous paradoxes by treating human activities as phenomena of self-organization. Therein, action and cognition are seen to be emergent in (...) ultrafast symmetry breaking across the brain and body; exquisitely constituted of the otherwise trivial details of history, context, and environment; and exhibiting the characteristic scale-free signature of self-organization. (shrink)

Integrated Information Theory (IIT) stands out as one of the most promising theories for dealing with the hard problem of consciousness. Founded on five axioms derived from phenomenology, IIT seeks for the physical substrate of consciousness that complies with such axioms according to the criterion of maximally integrated information (Φ). Eventually, IIT identifies phenomenal consciousness with maximal Φ or, what is the same thing, with the strongest cause-effect power in the system. Among the scholars critical of this theory, some point (...) to the so-called Intrinsicality Problem (IP), namely that consciousness cannot be an intrinsic property of the system because maximal Φ crucially depends on the possible existence of bigger values of Φ if the initial system is appropriately linked to or embedded in larger systems. Although proposals in the recent literature aim to solve the IP by going beyond reductionism and physicalism, none of them tackle the real issue, i.e., the insufficiency of IIT’s causal-metaphysical structure. This papers endeavors to provide a solution to the IP in IIT within a hylomorphist ontology that includes formal causation. Complementing IIT with formal causation provides the theory with a criterion of individuation that solves the IP and, by relaxing identification between maximal Φ and consciousness, it lends a more robust metaphysical structure. To wit, maximal Φ is a necessary but not sufficient condition for the existence of consciousness. (shrink)

Evolution is often characterized as a tinkerer that creates efficient but messy solutions to problems. We analyze the nature of the problems that arise when we try to explain and understand cognitive phenomena created by this haphazard design process. We present a theory of explanation and understanding and apply it to a case problem – solutions generated by genetic algorithms. By analyzing the nature of solutions that genetic algorithms present to computational problems, we show that the reason for why evolutionary (...) designs are often hard to understand is that they exhibit non-modular functionality, and that breaches of modularity wreak havoc on our strategies of causal and constitutive explanation. (shrink)

Lately there has been a growing interest in evolutionary studies concerning how the regularities and patterns found in the living cell could have emerged spontaneously by way of self-assembly and self-organization. It is reasonable to postulate that the chemical compounds found in the primitive Earth would have mostly been very simple in nature, and would have been immersed in the natural dynamics of the physical world, some of which would have involved self-organization. It seems likely that some molecular processes self-organized (...) spontaneously into a hierarchy of complex behaviours. Our conceptual search herein reaches back to the time when prebiotic phenomena began to take shape. This was before the origin of life, so in this paper we hope to shed new light on some of the theoretical issues that surround the ways in which cellular organization might have evolved without the aid of replicated information. (shrink)

A growing body of literature focuses on practice as a central aspect of teacher education. Whereas this approach emerged mainly from teacher preparation programs in specific content areas such as math, science, and literacy studies, socially related educational fields have served as a peripheral player alone. Recently, however, scholars have suggested incorporating a practice-based approach to teacher education into the social studies. In this article, we draw on complexity theory to reexamine this proposal, evaluating the connections between teaching practices and (...) democratic citizenship. First, we introduce complexity theory. Second, we offer a critical examination of key publications discussing practice-based teacher education, using the components of complexity theory as an organizing scheme. We then highlight practice-based teacher education’s reductive aspects, leading to an argument that promoting democratic citizenship through civics teacher education should be seen as a complex endeavor where borders are blurred, interactions are nonlinear, and reality changes frequently. Finally, we offer to supplement the practice approach with aspects of teacher education that stem from complexity theory. (shrink)

Reduction is a concept first introduced by Descartes in explaining his view of the rationalization of philosophy through mathematics. He seeks to consider length, breadth, and depth for phenomena so that reducing the phenomenon to his own analytical geometric apparatus; thus shrinking the whole world into a small machine. In the present study, the authors took into account the deficiency in defining the reduction of phenomena to a mathematically sound system as the reason for a large group of problems and (...) therefore they came to redefine the Cartesian reductionism of phenomena by removing the search space through a learning system. In due definition, it is possible to reduce the NP problems to P space without using a quantum algorithm that requires a quantum computer to exist. The present study points out that the problems arising from the mathematical modeling of the Covid-19 pandemic are due to a deficiency in the definition of Cartesian reduction, which leads to an increase in the computational complexity of its diagnosis and treatment using computational tools. (shrink)