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)

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.

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)

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)

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 offers a practical argument for metaphysical emergence. The main message is that the growing reliance on so-called irrational scientific methods provides evidence that objects of science are indecomposable and as such, are better described by metaphysical emergence as opposed to the prevalent reductionistic metaphysics. I show that a potential counterargument that science will eventually reduce everything to physics has little weight given where science is heading with its current methodological trend. I substantiate my arguments by detailed examples from (...) biological engineering, but the conclusions are extendable beyond that discipline. (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)

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)

Since its formulation in the twentieth century, Systems Theory has lacked a truly unifying paradigm. One fundamental reason for this fragmentation is the persistent anthropocentric bias that separates what we label “natural” from what we deem “artificial.” This paper argues that such a distinction is not an ontological truth but rather a cultural construct that has shaped our understanding of reality. By dismantling this false opposition, we can envision a “Systemic Continuum,” where biological, technological, and social systems are studied within (...) a single theoretical framework. This approach could revolutionize our understanding of Artificial Intelligence, technological evolution, and the emergence of complex structures, paving the way for a more robust integration of the diverse strands within Systems Theory. (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)

In an illuminating article, Claus Beisbart argues that the recently-popular thesis that the probabilities of statistical mechanics (SM) are Best System chances runs into a serious obstacle: there is no one axiomatization of SM that is robustly best, as judged by the theoretical virtues of simplicity, strength, and fit. Beisbart takes this 'no clear winner' result to imply that the probabilities yielded by the competing axiomatizations simply fail to count as Best System chances. In this reply, we express sympathy for (...) the 'no clear winner' thesis. However, we argue that an importantly different moral should be drawn from this. We contend that the implication for Humean chances is not that there are no SM chances, but rather that SM chances fail to be sharp. (shrink)

This paper aims to elucidate a kind of ignorance that is more fundamental than a momentary lack of information, but also not a kind of ignorance that is built into the subject’s cognitive apparatus such that the subject can’t do anything about it. The paper sets forth the notion of cognitive confinement, which is a contingent, yet relatively stable state of being structurally or systematically unable to gain information from an environment, determined by patterns of interaction between the subject and (...) the world. In order to unpack the idea of cognitive confinement the paper discusses niche construction theory, and then, in greater detail, the notion of cognitive niche once proposed by John Tooby and Irven DeVore. Cognitive confinement is here imagined as a pathologized form of cognitive niche. This posit is substantiated by referring to a case that has come to the fore in recent years and raised debate around the world: the rise of so-called filter bubbles. They turn out to be instantiations of a more general phenomenon of cognitive confinement. (shrink)

Reductionism has dominated science and philosophy for centuries. Complexity has recently shown that interactions—which reductionism neglects—are relevant for understanding phenomena. When interactions are considered, reductionism becomes limited in several aspects. In this paper, I argue that interactions imply nonreductionism, non-materialism, non-predictability, non-Platonism, and non-Nihilism. As alternatives to each of these, holism, informism, adaptation, contextuality, and meaningfulness are put forward, respectively. A worldview that includes interactions not only describes better our world, but can help to solve many open scientific, philosophical, and (...) social problems caused by implications of reductionism. (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)

Einstein’s razor, a corollary of Ockham’s razor, is often paraphrased as follows: make everything as simple as possible, but not simpler. This rule of thumb describes the challenge that designers of a legal system face—to craft simple laws that produce desired ends, but not to pursue simplicity so far as to undermine those ends. Complexity, simplicity’s inverse, taxes cognition and increases the likelihood of suboptimal decisions. In addition, unnecessary legal complexity can drive a misallocation of human capital toward comprehending and (...) complying with legal rules and away from other productive ends. While many scholars have offered descriptive accounts or theoretical models of legal complexity, most empirical research to date has been limited to simple measures of size, such as the number of pages in a bill. No extant research rigorously applies a meaningful model to real data. As a consequence, we have no reliable means to determine whether a new bill, regulation, order, or precedent substantially effects legal complexity. In this paper, we begin to address this need by developing a proposed empirical framework for measuring relative legal complexity. This framework is based on “knowledge acquisition”, an approach at the intersection of psychology and computer science, which can take into account the structure, language, and interdependence of law. We then demonstrate the descriptive value of this framework by applying it to the U.S. Code’s Titles, scoring and ranking them by their relative complexity. We measure various features of a title including its structural size, the net flow of its intra-title citations and its linguistic entropy. Our framework is flexible, intuitive, and transparent, and we offer this approach as a first step in developing a practical methodology for assessing legal complexity. (shrink)

The received view in the history of the philosophy of psychology is that the logical positivists—Carnap and Hempel in particular—endorsed the position commonly known as “logical” or “analytical” behaviourism, according to which the relations between psychological statements and the physical-behavioural statements intended to give their meaning are analytic and knowable a priori. This chapter argues that this is sheer legend: most, if not all, such relations were viewed by the logical positivists as synthetic and knowable only a posteriori. It then (...) traces the origins of the legend to the logical positivists’ idiosyncratic extensional or at best weakly intensional use of what are now considered crucially strongly intensional semantic notions, such as “translation,” “meaning” and their cognates, focussing on a particular instance of this latter phenomenon, arguing that a conflation of explicit definition and analyticity may be the chief source of the legend. (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)

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)

Sagoff (2016) criticizes widely used “theoretical” methods in ecology; arguing that those methods employ models that rely on problematic metaphysical assumptions and are therefore uninformative and useless for practical decision-making. In this paper, I show that Sagoff misconstrues how such model-based methods work in practice, that the main threads of his argument are problematic, and that his substantive conclusions are consequently unfounded. Along the way, I illuminate several ways the model-based inferential methods he criticizes can be, and have been, usefully (...) informative. (shrink)

I propose a cautionary assessment of the recent debate concerning the impact of the dynamical approach on philosophical accounts of scientific explanation in the cognitive sciences and, particularly, the cognitive neurosciences. I criticize the dominant mechanistic philosophy of explanation, pointing out a number of its negative consequences: In particular, that it doesn’t do justice to the field’s diversity and stage of development, and that it fosters misguided interpretations of dynamical models’ contribution. In order to support these arguments, I analyze a (...) case study in computational neuroethology and show why it should not be understood through a mechanistic lens; I specially focus on Zednik’s mechanistic interpretation of the case study. In addition, I argue for a greater appreciation of the relation between explanation and other epistemic goals in the field, as well as an increased sensitivity towards the associated contextual factors. (shrink)

Scientific understanding as a subject of inquiry has become widely discussed in philosophy of science and is often addressed through case studies from history of science. Even though these historical reconstructions engage with details of scientific practice, they usually provide only limited information about the gradual formation of understanding in ongoing processes of model and theory construction. Based on a qualitative ethnographic study of an ecological research project, this article shifts attention from understanding in the context of historical case studies (...) to evidence of current case studies. By taking de Regt’s contextual theory of scientific understanding into the field, it confirms core tenets of the contextual theory suggesting a normative character with respect to scientific activities. However, the case study also shows the limitations of de Regt’s latest version of this theory as an attempt to explain the development of understanding in current practice. This article provides a model representing the emergence of scientific understanding that exposes main features of scientific understanding such as its gradual formation, its relation to skills and imagination, and its capacity for knowledge selectivity. The ethnographic evidence presented here supports the claim that something unique can be learned by looking into ongoing research practices that can’t be gained by studying historical case studies. (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)

In this article, an attempt is made to introduce a systematization of the loosely connected group of authors called Bildungstheorie. This ought to not only be of significance for German-speaking educational science, for the concept of Bildung is also increasingly used internationally for the formulation and development of pedagogical issues. It is proposed that the concept of complexity could be suitable for bringing attention to common presuppositions in the theoretical dealing with the problem of Bildung. The thesis is that Bildung (...) in theories of Bildung is described from various perspectives as complex, meaning it is an open and uncertain interplay of components irreducibly associated with planning and governance problems. As this thesis is corroborated by means of selected positions within Bildungstheorie, evidence is provided that complexity in educational science—differently than it may seem at first glance—is not for the first time today a theme of importance. Rather, it is demonstrated that a nascent discipline-specific complexity research can be linked to already existing traditions. (shrink)

Fleur Johns argues that the contraposition of a ‘bottom-up’ approach of politics of prototypical technique rather than the ‘top-down’ politics of the master plan or normative principle no longer seems as straightforwardly radical as it appeared when James C Scott posited the value of local knowledge or métis against grand plans of high modernization, just over 20 years ago. This paper seeks to follow Johns’ call, ‘to capture and probe some of the effects of sensibility, rationality or style widely reproduced (...) in the details of development work’. It draws upon fieldwork in Nairobi to open up a discussion of a shift in sensibility from a ‘bottom-up’ or ‘postliberal’ approach to a framing of open-ended encounter. The paper critiques this imaginary of relational encounter by engaging contemporary work in critical black studies. It suggests that the problem of critique is that it reproduces the problems of governing imaginaries, continually seeking to rework the human subject via adaptive capacities, sensitivities to difference and openness to alterity, while leaving intact the coloniality of being, the antiblack world. (shrink)

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

Probably the most challenging issue in science and advanced technology is the ever increasing complexity. The term complexity refers to the experience that the complex whole is more than the sum of the parts. Emergence of new properties is observed at all levels, from relatively simple physical systems up to high-end evolution in biology or state-of-the-art microprocessors in technology. In this study an effort is made to arrive at an understanding of the underlying ontological basis in terms of the classical (...) philosophy of Aristotle and Aquinas. In addition, the value of philosophy is emphasized as a means to develop the capacity for intuition. Only with this capacity it is possible to acquire an understanding of the great variety of concepts needed in the multidisciplinary approach to complex systems. (shrink)

This article considers the implications of complex systems models for the study of economics and the evaluation of public policies. I argue that complexity can enhance current approaches to formal economic analysis, but does so in ways that complement current approaches. I further argue that while complexity can influence how public policy analysis is conducted, it does not delimit the use of consequentialist approaches to policy comparison to the degree initially suggested by Hayek and most recently defended by Gaus.

Since their inception in the 1980s, complexity sciences have been described as a revolutionary new domain of research. By describing some of the practices and assumptions of its representatives, the present article shows that this field is an association of subdisciplines laying on existing disciplinary footholds. The general question guiding us here is: On what basis do complexity scientists consider their inquiry methods and results as valuable? To answer it, I describe five “epistemic argumentative regimes,” namely the ways in which (...) complexity scientists argue the credibility of their research, and five “ontological views,” that is the ways in which they interpret the material and formal causes of their study objects and models. Finally, the article proposes the term of “regime of evidence” to designate the specific combination of one ontological view with one or more epistemic argumentative regimes. (shrink)

The proliferation of digital data has been the impetus for the emergence of a new discipline for the study of social life: ‘computational social science’. Much research in this field is founded on the premise that society is a complex system with emergent structures that can be modeled or reconstructed through digital data. This paper suggests that computational social science serves practical and legitimizing functions for digital capitalism in much the same way that neoclassical economics does for neoliberalism. In recognition (...) of this homology, this paper develops a critique of the complexity perspective of computational social science and argues for a heterodox computational social science founded on the meta-theory of critical realism that is critical, methodological pluralist, interpretative and explanative. This implies diverting computational social science’ computational methods and digital data so as to not be aimed at identifying invariant laws of social life, or optimizing state and corporate practices, but to instead be used as part of broader research strategies to identify contingent patterns, develop conjunctural explanations, and propose qualitatively different ways of organizing social life. (shrink)

For the last three decades, physicists have been moving beyond the boundaries of their discipline, using their methods to study various problems usually instigated by economists. This trend labeled ‘econophysics’ can be seen as a hybrid area of knowledge that exists between economics and physics. Econophysics did not spring from nowhere—the existing literature agrees that econophysics emerged in the 1990s and historical studies on the field mainly deal with what happened during that decade. This article aims at investigating what happened (...) before the 1990s by clarifying the epistemic background that might have paved the way to the emergence of econophysics. This historical exploration led me to highlight the active role played by the Santa Fe Institute by promoting interdisciplinary research on complexity in 1980s. Precisely, by defining three research themes on economic complexity, the SFI defined a research agenda and a way of extending physics\biology to economics. This article offers a possible archeology of econophysics to clarify what could have contributed to the development of a particular episteme in the 1980s easing the advent of econophysics in the 1990s. (shrink)

Computational philosophy is the use of mechanized computational techniques to instantiate, extend, and amplify philosophical research. Computational philosophy is not philosophy of computers or computational techniques; it is rather philosophy using computers and computational techniques. The idea is simply to apply advances in computer technology and techniques to advance discovery, exploration and argument within any philosophical area. -/- After touching on historical precursors, this article discusses contemporary computational philosophy across a variety of fields: epistemology, metaphysics, philosophy of science, ethics and (...) social philosophy, philosophy of language and philosophy of mind, often with examples of operating software. Far short of any attempt at an exhaustive treatment, the intention is to introduce the spirit of each application by using some representative examples. (shrink)

Complexity science has witnessed a number of advances since the publication of Jervis's System Effects. These advances better allow us to untangle the messy elements in a system and predict sets of likely outcomes. However, just because a system is complex doesn't mean that all the ideas relating to complexity—such as agent-based modeling, path dependency, tipping points, between-class versus within-class effects, and networks—are necessarily relevant. One of our tasks is to determine whether they are—and, if so, their implications. As examples, (...) we use China's role in the formation of the United States housing bubble; the federal government's bailout of AIG and Bear Stearns but not Lehman Brothers; and China's failure to experience a regime change such as the Middle East's Arab Spring. (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 development of new theory is often spurred by novel techniques that provide better answers to existing questions, or that allow asking new ones. In the field of strategy and organization science, models of complex adaptive systems have renewed theoretical work on a fundamental question: how organizations can adapt effectively to their environments. This article has three objectives: to highlight some areas where models of organizations as complex adaptive systems have made substantial contributions: the search for solutions to sets of (...) interdependent choices, the challenge of balancing processes of exploration and exploitation, and the organization of imperfect decision makers; to point to several challenges and tradeoffs which can limit the explanatory power and eventual impact of the modeling enterprise; and to sketch out possible future directions of research that would do further justice to the notion of organizations as complex adaptive systems. (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)

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)

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)

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)

Robert Jervis's System Effects (1997) shares a great deal with game theory, complex-systems theory, and systems theory in international relations, yet it transcends them all by taking account of the role of ideas in human behavior. The ideational element inserts unpredictability into Jervis's understanding of system effects. Each member of a ?system? of interrelated actors interprets her situation to require certain actions based on the effects these will cause among other members of the system, but these other actors' responses to (...) one's action will be based on their own perceptions of their situation and their interpretations of what it requires. These ideas are fallible, but we cannot predict the mistakes people will make if the errors are based on information we do not have or do not interpret in the same way they do. Not only members of a system but social-scientific observers and policy makers are ignorant of others' information and interpretations, and therefore are as likely to err in their behavioral predictions as are members of the system. Thus, Jervis's book raises serious questions about how to evaluate policies directed toward producing positive system effects. The questions are unanswerable at this point, but they might be susceptible to analysis by an ambitious form of political theory. (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)

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)