The use of multiple means of determination to “triangulate” on the existence and character of a common phenomenon, object, or result has had a long tradition in science but has seldom been a matter of primary focus. As with many traditions, it is traceable to Aristotle, who valued having multiple explanations of a phenomenon, and it may also be involved in his distinction between special objects of sense and common sensibles. It is implicit though not emphasized in the distinction between (...) primary and secondary qualities from Galileo onward. It is arguably one of several conceptions involved in Whewell’s method of the “consilience of inductions” (Laudan 1971) and is to be found in several places in Peirce. (From M. Brewer and B. Collins, eds., (1981); Scientific Inquiry in the Social Sciences (a festschrift for Donald T. Campbell), San Francisco: Jossey-Bass, pp. 123–162.). (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.

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 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)

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)

Purpose. The work is aimed at comprehending good and evil as vectors of free will in the structure of anthropic time. Methodology. The study is based on: 1) the general theory of systems – while justifying the possibility of representing the anthropic time as a system in general; 2) synergetics – while considering the anthropic time as a complex self-organizing system; 3) the concept of «а whole in a whole» – while identifying the optimal principle of correlation of the time (...) units, taking into attention their ethical multi-vectority. Originality. In the context of the reconstruction of the concept of anthropic time: 1) the authors revealed ethical vectors of expansion of free will as the driving principle of human temporality ; 2) the authors justified the optimality of using the principle of complementarity in solving the problem of harmonizing the coexistence of units of anthropic time. Conclusion. 1) In a line with the tradition of anthropologization of the problem of good and evil, these intentions of human activity are interpreted as vectors of free will in the structure of anthropic time; 2) the paper represented anthropic time as a system in general and as a complex self-organizing system in particular ; 3) constituting of the system of anthropic time by the existential-actionable concept allowed to overcome the position of the one-vectored time, i.e.to reveal the ethical binarity of the anthropic time vectors prepared by the duality of expansion of free will as its driving principle; 4) formulation of the problem of discrepancy between the intentions of different temporal systems showed the optimality of the complementarity principle in solving the question how to harmonize the relations of anthropic time units; 5) the conducted research opens prospects for consideration of external determinants of anthropic time, as well as for search of variants of their correlation with the internal mover in the structure of human temporality. (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)

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)

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)

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)

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)

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)

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)

Power and leadership are typically theorized as exercises of sovereignty in the western tradition of thought. This essay takes up Michel Foucault’s challenge to escape the ‘spell of monarchy’ in our thinking in order to move beyond sovereign models of power. Interdisciplinary scholarship on complex adaptive systems provides fertile ground for this endeavor, illustrating the dynamics of post-sovereign power and opportunities for post-sovereign leadership. Viewing human organizations as complex adaptive systems helps us to theorize leadership without over-simplifying its nature or (...) exaggerating its potential. It also undermines the prevailing identification of sovereign power as the only antidote for anarchy. (shrink)

Integrated Information Theory 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. 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, 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)

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)

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)

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)

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)

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)

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 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 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)

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. (2008), 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 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)

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)

Understanding artificial intelligence and belief formation have interesting bidirectional synergies. From explaining the logical derivation of beliefs and their internal consistency, to giving a quantitative account of mightiness, AI still has plenty of unexploited metaphors that can illuminate belief formation. In addition, acknowledging that AI should integrate itself with our belief processes makes it possible to focus on more promising lines such as Interpretable Machine Learning.

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)

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)

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)

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)

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)

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)

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)

Inclusive fitness theory provides conditions for the evolutionary success of a gene. These conditions ensure that the gene is selfish in the sense of Dawkins (The selfish gene, Oxford University Press, Oxford, 1976): genes do not and cannot sacrifice their own fitness on behalf of the reproductive population. Therefore, while natural selection explains the appearance of design in the living world (Dawkins in The blind watchmaker: why the evidence of evolution reveals a universe without design, W. W. Norton, New York, (...) 1996), inclusive fitness theory does not explain how. Indeed, Hamilton’s rule is equally compatible with the evolutionary success of prosocial altruistic genes and antisocial predatory genes, whereas only the former, which account for the appearance of design, predominate in successful organisms. Inclusive fitness theory, however, permits a formulation of the central problem of sociobiology in a particularly poignant form: how do interactions among loci induce utterly selfish genes to collaborate, or to predispose their carriers to collaborate, in promoting the fitness of their carriers? Inclusive fitness theory, because it abstracts from synergistic interactions among loci, does not answer this question. Fitness-enhancing collaboration among loci in the genome of a reproductive population requires suppressing alleles that decrease, and promoting alleles that increase the fitness of its carriers. Suppression and promotion are effected by regulatory networks of genes, each of which is itself utterly selfish. This implies that genes, and a fortiori individuals in a social species, do not maximize inclusive fitness but rather interact strategically in complex ways. It is the task of sociobiology to model these complex interactions. (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)

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)

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)

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 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.