Upshot: In our response we focus on five questions that point to important common themes in the commentaries: why start in wicked problems, what kind of system is a scientific perspective, what is the nature of second-order research processes, what does this mean for understanding interdisciplinary work, and how may polyocular research help make real-world decisions.

Optimization is about finding the best available object with respect to an objective function. Mathematics and quantitative sciences have been highly successful in formulating problems as optimization problems, and constructing clever processes that find optimal objects from sets of objects. As computers have become readily available to most people, optimization and optimized processes play a very broad role in societies. It is not obvious, however, that the optimization processes that work for mathematics and abstract objects should be readily applied to (...) complex and open social systems. In this paper we set forth a framework to understand when optimization is limited, particularly for complex and open social systems. (shrink)

This is a contribution to the encyclopedia of systems biology on complexity.

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)

We develop and apply a multi-dimensional account of explanatory depth towards a comparative analysis of inflationary and bouncing paradigms in primordial cosmology. Our analysis builds on earlier work due to Azhar and Loeb (2021) that establishes initial conditions fine-tuning as a dimension of explanatory depth relevant to debates in contemporary cosmology. We propose dynamical fine-tuning and autonomy as two further dimensions of depth in the context of problems with instability and trans-Planckian modes that afflict bouncing and inflationary approaches respectively. In (...) the context of the latter issue, we argue that the recently formulated trans-Planckian censorship conjecture leads to a trade-off for inflationary models between dynamical fine-tuning and autonomy. We conclude with the suggestion that explanatory preference with regard to the different dimensions of depth is best understood in terms of differing attitudes towards heuristics for future model building. (shrink)

The purpose of this essay is to present and analyse the basic assumptions of Leszek Nowak’s conception of the unity of science. According to Nowak, the unity of science is manifested in the common application of the method of idealisation in scientific research. In accordance with his conception, regardless of the discipline they represent, researchers go through the same stages in building a theory. Two key ones among them are: introducing idealising assumptions into the representation and then their concretisation. In (...) this view, idealisation is the basis of the scientific method, while other cognitive procedures complement it. Nowak’s conception has particular relevance in the context of the dispute between naturalism and anti-naturalism and in the context of the continuing rift between social scientists and natural scientists. It calls into question the anti-naturalist thesis of the ontological uniqueness of social sciences and the resulting methodological consequences. I argue that Nowak’s conception is a cognitively valuable contribution to the contemporary epistemology of science, but it also has weaknesses, mainly due to the limitations of applying the idealisation-concretisation scheme in research practice. For it turns out, as I point out in this essay, that many idealising assumptions are not subject to concretisation and that concretisations do not always condition an increase in the explanatory and/or predictive power of the representations. (shrink)

Large sets of elements interacting locally and producing specific architectures reliably form a category that transcends the usual dividing line between biological and engineered systems. We propose to call them morphogenetically architected complex systems (MACS). While taking the emergence of properties seriously, the notion of MACS enables at the same time the design (or “meta-design”) of operational means that allow controlling and even, paradoxically, programming this emergence. To demonstrate our claim, we first show that among all the self-organized systems studied (...) in the field of Artificial Life, the specificity of MACS essentially lies in the close relation between their emergent properties and functional properties. Second, we argue that to be a MACS a system does not need to display more than weak emergent properties. Third, since the notion of weak emergence is based on the possibility of simulation, whether computational or mechanistic via machines, we see MACS as good candidates to help design artificial self-architected systems (such as robotic swarms) but also harness and redesign living ones (such as synthetic bacterial films). (shrink)

In recent years, many philosophers of science have attempted to articulate a theory of non-epistemic emergence that is compatible with mechanistic explanation and incompatible with reductionism. The 2005 account of Fred C. Boogerd et al. has been particularly influential. They argued that a systemic property was emergent if it could not be predicted from the behaviour of less complex systems. Here, I argue that Boogerd et al.'s attempt to ground emergence in complexity guarantees that we will see emergence, but at (...) the cost of rendering it either trivial or epistemic. There are three basic problems. First, neither the measures of complexity explicitly mentioned by Boogerd et al. nor the most popular measures in the literature can do the practical and theoretical work that they assign to complexity. Second, I argue that while the success of their view depends on restricting the base of information available to the reductionist, this cannot be done in a way that is metaphysically neutral with respect to emer.. (shrink)

Cancer is typically spoken of as a “complex” disease. But, in what sense are cancers “complex”? Is there one sense, or several? What implications does this complexity have – both for how we study, and how we intervene upon cancers? The aim of this paper is first, to clarify the variety of senses in which cancer is spoken of as "complex" in the scientific literature, and second, to discover what explanatory and predictive roles such features play.

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)

Scientific theories of consciousness identify its contents with the spatiotemporal structure of neural population activity. We follow up on this approach by stating and motivating Dynamical Emergence Theory, which defines the amount and structure of experience in terms of the intrinsic topology and geometry of a physical system’s collective dynamics. Specifically, we posit that distinct perceptual states correspond to coarse-grained macrostates reflecting an optimal partitioning of the system’s state space—a notion that aligns with several ideas and results from computational neuroscience (...) and cognitive psychology. We relate DET to existing work, offer predictions for empirical studies, and outline future research directions. (shrink)

Complexity sciences have become famous worldwide thanks to several popular books that served as echo chambers of their promises. These consisted in departing from “classical science” defined as deterministic, reductionist, analytic and mono-disciplinary. Their founders and supporters declared that complexity sciences were going to give rise (or that they have given rise) to a post-Laplacian, antireductionist, holistic and interdisciplinary approach. By taking a closer look at their content and practices, I argue in this article that, because of their physics-oriented, computationalist, (...) and mathematical assumptions, complexity sciences have paradoxically produced knowledge at odds with these four tenets. (shrink)

Complexity sciences are one of the most mediatized scientific fields of the last 40 years. While this domain has attracted the attention of many philosophers of science, its normative views have not yet been the object of any systematic study. This article is a contribution to the thin social science literature about complexity sciences and proposes a contribution focused on an analysis of the origins, models, and organization of the Santa Fe Institute (SFI), cradle of the field. The paper defends (...) the thesis that the notion of “complex adaptive systems” bears a project of naturalization of society through numerical and evolutionary lenses by promoting a Darwinian and capitalist view of the economy. At the same time, such a view has been embodied in the very way of functioning of the institute, which was conceived as an agile organization in a competitive environment and which relies on a fundraising philosophy that tends to commodify science. From a theoretical viewpoint, this text is anchored in the field of Science and Technology Studies and particularly in the coproductionist paradigm, which theorizes the dynamic entanglement of science and society. In terms of empirical sources, the article is based on interviews conducted by the author, and on the SFI's scientific publications as well as institutional archives. (shrink)

From the perspective of the complex system, university ranking is a complex system that involves multiagent actors, which evolve over time. Yet, current major university rankings fail to reflect the system dynamics of the university innovation system. In this paper, we apply the complex system model in the field of the university innovation system in the context of university ranking in the countries along the Belt and Road, which is a long-term overlooked field. We introduce a new method of university (...) ranking based on the “winning and losing” relationship to measure the relative competitiveness between universities. This paper contributes to complex system research, the Belt and Road research, and the university ranking arena. (shrink)

Many cognitive and evolutionary theories of religion argue that supernatural explanations are byproducts of our cognitive adaptations. An influential argument states that our supernatural explanations result from a tendency to generate anthropomorphic explanations, and that this tendency is a byproduct of an error management strategy because agents tend to be associated with especially high fitness costs. We propose instead that anthropomorphic and other supernatural explanations result as features of a broader toolkit of well-designed cognitive adaptations, which are designed for explaining (...) the abstract and causal structure of complex, unobservable, and uncertain phenomena that have substantial impacts on fitness. Specifically, we argue that (1) mental representations about the abstract vs. the supernatural are largely overlapping, if not identical, and (2) when the data-generating processes for scarce and ambiguous observations are complex and opaque, a naive observer can improve a bias-variance trade-off by starting with a simple, underspecified explanation that Western observers readily interpret as “supernatural.” We then argue that (3) in many cases, knowledge specialists across cultures offer pragmatic services that involve apparently supernatural explanations, and their clients are frequently willing to pay them in a market for useful and effective services. We propose that at least some ethnographic descriptions of religion might actually reflect ordinary and adaptive responses to novel problems such as illnesses and natural disasters, where knowledge specialists possess and apply the best available explanations about phenomena that would otherwise be completely mysterious and unpredictable. (shrink)

Undergraduate geoscience students are rarely exposed to history and philosophy of science. I will describe the experiences with a short course unfavourably placed in the first year of a bachelor of earth science. Arguments how HPS could enrich their education in many ways are sketched. One useful didactic approach is to develop a broader interest by connecting HPS themes to practical cases throughout the curriculum, and develop learning activities that allow students to reflect on their skills, methods and their field (...) in relation to other disciplines and interactions with society with abilities gained through exposure to HPS. Given support of the teaching staff, the tenets of philosophy of science in practice, of conceptual history of knowledge, and of ethics of science for society can fruitfully and directly be connected to the existing curriculum. This is ideally followed by a capstone HPS course late in the bachelor programme. (shrink)

Craig Callender claims that ‘time is the great informer’, meaning that the directions in which our ‘best’ physical theories inform are temporal. This is intended to be a metaphysical claim, and as such expresses a relationship between the physical world and information-gathering systems such as ourselves. This article gives two counterexamples to this claim, illustrating the fact that time and informative strength doubly dissociate, so the claim cannot be about physical theories in general. The first is a case where physical (...) theories inform in directions that we have no reason to regard as temporal. The second is a case where our best physical theories fail to inform in directions that we have independent (pre-theoretic) reasons to regard as temporal. Taking these two cases into account suggests that the connection Callender makes between time and informativeness is perspectival. The second case demonstrates that although scientists often seek information in temporal directions, the behaviour of the physical world can present serious difficulties for finding it. In response, this article proposes a perspectival reading of Callender’s claim, according to which the connection between time and informative strength has more to do with the aims and objectives of science than the workings of the physical world. (shrink)

The terms ‘structural injustice’ and ‘systemic injustice’ are commonly used, but their meanings are elusive. In this paper, I sketch an ontology of social systems that embeds accounts of social structures, relations, and practices. On this view, structures may be intrinsically problematic, or they may be problematic only insofar as they interact with other structures in the system to produce injustice. Because social practices that constitute structures set the backdrop for agency and identity, socially fluent agents reproduce the systems, often (...) unknowingly and unintentionally. The account aims to capture how agents both depend on and enact structures, and do so in ways that, as Ta-Nehisi Coates says, ‘land on the body’. (shrink)

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

In this paper, I shall provide a novel response to the argument from context-sensitivity against truth-conditional semantics. It is often argued that the contextual influences on truth-conditions outstrip the resources of standard truth-conditional accounts, and so truth-conditional semantics rests on a mistake. The argument assumes that truth-conditional semantics is legitimate if and only if natural language sentences have truth-conditions. I shall argue that this assumption is mistaken. Truth-conditional analyses should be viewed as idealised approximations of the complexities of natural language (...) meaning. From this perspective, disparity between the scientific model and its real-world target is to be expected. I elaborate on what such an approach to semantics would look like. (shrink)

The philosophy of blockchain technology is concerned, among other things, with blockchain ontology, how it might be characterised, how it is being created, implemented, and adopted, how it operates in the world, and how it evolves over time. This paper concentrates on whether Bitcoin/blockchain can be considered a complex system and, if so, whether it is a chaotic one. Beyond mere academic curiosity, a positive response would raise concerns about the likelihood of Bitcoin/blockchain entering a 2010-Flash-Crash-type of chaotic regime, with (...) catastrophic consequences for financial systems based on it. The paper starts by highlighting the relevant details of the Bitcoin/blockchain ecosystem formed by the blockchain itself, bitcoin end users, capital gains seekers, miners, full nodes maintainers, and developers, and their interactions. Then the Information Theory of Complex Systems is briefly discussed for later use. Finally, the blockchain is investigated with the help of Crutchfield's Statistical Complexity measure. The low non-null statistical complexity value obtained suggests that the blockchain may be considered algorithmically complicated but hardly a complex system and unlikely to enter a chaotic regime. (shrink)

Modelos representacionais são usados na prática científica para representar diferentes fenômenos. O propósito deste trabalho é examinar o uso de autômatos celulares para representar fenômenos emergentes, isto é, fenômenos com aspectos globais que não podem ser preditos apenas a partir de seus aspectos locais, procurando entender como se dá a representação nesse processo de modelagem. Uma abordagem sugerida é a acepção DEKI desenvolvida por Roman Frigg e James Nguyen, no qual o processo de representação envolve quatro aspectos: denotação do sistema-alvo (...) pelo modelo sob uma interpretação, exemplificação das propriedades relevantes no modelo, formulação de uma legenda que relaciona propriedades do modelo com propriedades do alvo e imputação das propriedades dadas pela chave ao alvo. Nessa acepção, AC representariam os sistemas-alvo denotados como sistemas complexos que podem ser interpretados em nível local e global, de modo que propriedades emergentes são exemplificadas em nível global. (shrink)

Social machines are systems formed by material and human elements interacting in a structured way. The use of digital platforms as mediators allows large numbers of humans to participate in such machines, which have interconnected AI and human components operating as a single system capable of highly sophisticated behavior. Under certain conditions, such systems can be understood as autonomous goal-driven agents. Many popular online platforms can be regarded as instances of this class of agent. We argue that autonomous social machines (...) provide a new paradigm for the design of intelligent systems, marking a new phase in AI. After describing the characteristics of goal-driven social machines, we discuss the consequences of their adoption, for the practice of artificial intelligence as well as for its regulation. (shrink)

This paper argues that machine learning and epidemiology are on collision course over causation. The discipline of epidemiology lays great emphasis on causation, while ML research does not. Some epidemiologists have proposed imposing what amounts to a causal constraint on ML in epidemiology, requiring it either to engage in causal inference or restrict itself to mere projection. We whittle down the issues to the question of whether causal knowledge is necessary for underwriting predictions about the outcomes of public health interventions. (...) While there is great plausibility to the idea that it is, conviction that something is impossible does not by itself motivate a constraint to forbid trying. We disambiguate the possible motivations for such a constraint into definitional, metaphysical, epistemological, and pragmatic considerations and argue that “Proceed with caution” is the outcome of each. We then argue that there are positive reasons to proceed, albeit cautiously. Causal inference enforces existing classification schema prior to the testing of associational claims, but associations and classification schema are more plausibly discovered in a back-and-forth process of gaining reflective equilibrium. ML instantiates this kind of process, we argue, and thus offers the welcome prospect of uncovering meaningful new concepts in epidemiology and public health—provided it is not causally constrained. (shrink)

Complexity and integration are longstanding widely debated issues in philosophy of science and recent contributions have largely focused on biology and biomedicine. This paper specifically considers some methodological novelties in cancer research, motivated by various features of tumours as complex diseases, and shows how they encourage some rethinking of philosophical discourses on those topics. In particular, we discuss the integrative-cluster approach, and analyse its potential in the epistemology of cancer. We suggest that, far from being the solution to tame cancer (...) complexity, this approach offers a philosophically interesting new manner of considering integration, and show how it can help addressing the apparent contrast between a pluralistic and a unitary account. (shrink)

Complexity and integration are longstanding widely debated issues in philosophy of science and recent contributions have largely focused on biology and biomedicine. This paper specifically considers some methodological novelties in cancer research, motivated by various features of tumours as complex diseases, and shows how they encourage some rethinking of philosophical discourses on those topics. In particular, we discuss the integrative-cluster approach, and analyse its potential in the epistemology of cancer. We suggest that, far from being the solution to tame cancer (...) complexity, this approach offers a philosophically interesting new manner of considering integration, and show how it can help addressing the apparent contrast between a pluralistic and a unitary account. (shrink)

Complexity and integration are longstanding widely debated issues in philosophy of science and recent contributions have largely focused on biology and biomedicine. This paper specifically considers some methodological novelties in cancer research, motivated by various features of tumours as complex diseases, and shows how they encourage some rethinking of philosophical discourses on those topics. In particular, we discuss the integrative-cluster approach, and analyse its potential in the epistemology of cancer. We suggest that, far from being the solution to tame cancer (...) complexity, this approach offers a philosophically interesting new manner of considering integration, and show how it can help addressing the apparent contrast between a pluralistic and a unitary account. (shrink)

Bedau's influential (1997) account analyzes weak emergence in terms of the non-derivability of a system’s macrostates from its microstates except by simulation. I offer an improved version of Bedau’s account of weak emergence in light of insights from information theory. Non-derivability alone does not guarantee that a system’s macrostates are weakly emergent. Rather, it is non-derivability plus the algorithmic compressibility of the system’s macrostates that makes them weakly emergent. I argue that the resulting information-theoretic picture provides a metaphysical account of (...) weak emergence rather than a merely epistemic one. (shrink)

Contemporary philosophy of science has seen a growing trend towards a focus on scientific practice over the epistemic outputs that such practices produce. This practice-oriented approach has yielded a clearer understanding of how reductive research strategies play a central role in contemporary scientific inquiry. In parallel, a growing body of work has sought to explore the role of non-reductive, or systems-level, research strategies. As a result, the relationship between reductive and non-reductive scientific practices is becoming of increased importance. In this (...) paper, I provide a framework within which research strategies can be compared. I argue that no strategy is reductive or non-reductive simpliciter, rather strategies are more, or are less, reductive than one another according to a frame of reference. That frame of reference is provided by a continuum of possible ways in which the target system might be conceptualised. I illustrate the utility of the framework by deploying it to analyse a recent debate in cancer research. When set within the framework, a prominent reductive strategy—the somatic mutation theory—and a prominent non-reductive strategy—the tissue organisational field theory—do not stand opposed to one another. Rather, they serve as boundary markers to chart the territory of approaches to carcinogenesis within which most strategies in the field fall. (shrink)

Crossing the road within the traffic system is an example of an action human agents perform successfully day-to-day in complex systems. How do they perform such successful actions given that the behaviour of complex systems is often difficult to predict? The contemporary literature contains two contrasting approaches to the epistemology of complex systems: an analytic and a post-modern approach. We argue that neither approach adequately accounts for how successful action is possible in complex systems. Agents regularly perform successful actions without (...) obeying (explicit or implicit) algorithmic rules (as the analytic approach suggests) and without an existential leap to action (as the post-modern approach suggests). We offer an alternative: A common-sense pragmatist epistemology, one that focuses on the kind of actions making up most agents’ successful moment-to-moment actions in complex systems. Successful actions obtain when agents apply ceteris paribus rules-of-thumb during predictive and decisional practices while achieving some desired goal. (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)

There is a deeply entrenched view in philosophy and physics, the closed systems view, according to which isolated systems are conceived of as fundamental. On this view, when a system is under the influence of its environment this is described in terms of a coupling between it and a separate system which taken together are isolated. We argue against this view, and in favor of the alternative open systems view, for which systems interacting with their environment are conceived of as (...) fundamental, and the environment's influence is represented via the dynamical equations that govern the system's evolution. Taking quantum theories of closed and open systems as our case study, and considering three alternative notions of fundamentality: (i) ontic fundamentality, (ii) epistemic fundamentality, and (iii) explanatory fundamentality, we argue that the open systems view is fundamental, and that this has important implications for the philosophy of physics, the philosophy of science, and for metaphysics. (shrink)

'The ecological emergency’ describes both our emergence into, and the way we relate within, a set of globally urgent circumstances, brought about through anthropogenic impact. I identify two phases to this emergency. Firstly, there is the anthropogenic impact itself, interpreted through various conceptual models. Secondly, however, is the increasingly entrenched commitment to divergent conceptual positions, that leads to a growing disparateness in attitudes, and a concurrent difficulty with finding any grounds for convergence in response. I begin by reviewing the environmental (...) ethics literature in order to clarify which components of the implicit narratives and beliefs of different positions create the foundations for such disparateness of views. I identify the conceptual frameworks through which moral agency and human responsibility are viewed, and that justify an ethical response to the ecological emergency. In particular, I focus on Paul Taylor's thesis of 'respect for nature' as a framework for revising both the idea that we are ‘moral’ and the idea that we are ‘agents’ in this unique way, and I open to question the idea that any response to the ecological emergency need be couched in ethical terms. This revision leads me to formulate an alternative conceptual model that makes use of Timothy Morton’s idea of enmeshment. I propose that we dramatically revise our idea of moral agency using the idea of enmeshment as a starting point. I develop an alternative framework that locates our capacity for responsibility within our capacity for realisation, both in the sense of understanding, and of making real, sets of conditions within our enmeshment. I draw parallels between this idea of ‘realisation as agency’ and the work of Dōgen and other non-dualists. I then propose a revised understanding of ‘the good’ of systems from a biophysical perspective, and compare this with certain features of Asian traditions of thought. I consider the practical implications of these revisions, and I conclude that the act of paying close attention, or realising, contains our agency, as does the attitude, or manner, with which we focus. This gives us the basis for a convergent response to the ecological emergency: the way of our engagement that is the key to responding to the ecological emergency. (shrink)

Paul Cilliers has developed a novel post-structural approach to complexity that has influenced several writers contributing to the current complexity literature. Concomitantly however, Cilliers advocates for modelling complex systems using connectionist neural networks (rather than analytic, rule-based models). In this paper, I argue that it is dilemmic to simultaneously hold these two positions. Cilliers’ post-structural interpretation of complexity states that models of complex systems are always contextual and provisional; there is no exclusive model of complex systems. This sentiment however appears (...) at odds with Cilliers’ promotion of connectionist neural networks as the best way to model complex systems. The lesson is that those who currently follow Cilliers’ post-structural approach to complexity cannot also develop a preferred model of complex systems, and those who currently advocate for some preferred model of complex systems cannot adopt the post-structural approach to complexity without giving up the purported objectivity and/or superiority of their preferred model. (shrink)

Context: The problems that are most in need of interdisciplinary collaboration are “wicked problems,” such as food crises, climate change mitigation, and sustainable development, with many relevant aspects, disagreement on what the problem is, and contradicting solutions. Such complex problems both require and challenge interdisciplinarity. Problem: The conventional methods of interdisciplinary research fall short in the case of wicked problems because they remain first-order science. Our aim is to present workable methods and research designs for doing second-order science in domains (...) where there are many different scientific knowledges on any complex problem. Method: We synthesize and elaborate a framework for second-order science in interdisciplinary research based on a number of earlier publications, experiences from large interdisciplinary research projects, and a perspectivist theory of science. Results: The second-order polyocular framework for interdisciplinary research is characterized by five principles. Second-order science of interdisciplinary research must: 1. draw on the observations of first-order perspectives, 2. address a shared dynamical object, 3. establish a shared problem, 4. rely on first-order perspectives to see themselves as perspectives, and 5. be based on other rules than first-order research. Implications: The perspectivist insights of second-order science provide a new way of understanding interdisciplinary research that leads to new polyocular methods and research designs. It also points to more reflexive ways of dealing with scientific expertise in democratic processes. The main challenge is that this is a paradigmatic shift, which demands that the involved disciplines, at least to some degree, subscribe to a perspectivist view. Constructivist content: Our perspectivist approach to science is based on the second-order cybernetics and systems theories of von Foerster, Maruyama, Maturana & Varela, and Luhmann, coupled with embodied theories of cognition and semiotics as a general theory of meaning from von Uexküll and Peirce. (shrink)

Complexity is heterogenous, involving nonlinearity, self-organisation, diversity, adaptive behaviour, among other things. It is therefore obviously worth asking whether purported measures of complexity measure aggregate phenomena, or individual aspects of complexity and if so which. This paper uses a recently developed rigorous framework for understanding complexity to answer this question about measurement. The approach is two-fold: find measures of individual aspects of complexity on the one hand, and explain measures of complexity on the other. We illustrate the conceptual framework of (...) complexity science and how it links the foundations to the practised science with examples from different scientific fields and of various aspects of complexity. Furthermore, we analyse a selection of purported measures of complexity that have found wide application and explain why and how they measure aspects of complexity. This work gives the reader a tool to take any existing measure of complexity and analyse it, and to take any feature of complexity and find the right measure for it. (shrink)

According to one large family of views, scientific explanations explain a phenomenon (such as an event or a regularity) by subsuming it under a general representation, model, prototype, or schema (see Bechtel, W., & Abrahamsen, A. (2005). Explanation: A mechanist alternative. Studies in History and Philosophy of Biological and Biomedical Sciences, 36(2), 421–441; Churchland, P. M. (1989). A neurocomputational perspective: The nature of mind and the structure of science. Cambridge: MIT Press; Darden (2006); Hempel, C. G. (1965). Aspects of scientific (...) explanation. In C. G. Hempel (Ed.), Aspects of scientific explanation (pp. 331–496). New York: Free Press; Kitcher (1989); Machamer, P., Darden, L., & Craver, C. F. (2000). Thinking about mechanisms. Philosophy of Science, 67(1), 1–25). My concern is with the minimal suggestion that an adequate philosophical theory of scientific explanation can limit its attention to the format or structure with which theories are represented. The representational subsumption view is a plausible hypothesis about the psychology of understanding. It is also a plausible claim about how scientists present their knowledge to the world. However, one cannot address the central questions for a philosophical theory of scientific explanation without turning one’s attention from the structure of representations to the basic commitments about the worldly structures that plausibly count as explanatory. A philosophical theory of scientific explanation should achieve two goals. The first is explanatory demarcation. It should show how explanation relates with other scientific achievements, such as control, description, measurement, prediction, and taxonomy. The second is explanatory normativity. It should say when putative explanations succeed and fail. One cannot achieve these goals without undertaking commitments about the kinds of ontic structures that plausibly count as explanatory. Representations convey explanatory information about a phenomenon when and only when they describe the ontic explanations for those phenomena. (shrink)

This paper explores some of the factors that make complex systems complex. We first examine the history of complex systems. It was Aristotle’s insight that how elements are joined together helps determine the properties of the resulting whole. We find (a) that scientific reductionism does not provide a sufficient explanation; (b) that to understand complex systems, one must identify and trace energy flows; and (c) that disproportionate causality, including global tipping points, are all around us. Disproportionate causality results from the (...) wide availability of energy stores. We discuss three categories of emergent phenomena—static, dynamic, and adaptive—and recommend retiring the term emergent, except perhaps as a synonym for creative. Finally, we find that virtually all communication is stigmergic. (shrink)

The economic crisis happening across the world over the last few years describes a range of interdependencies and interactions,and has highlighted the fundamentalf laws of neoclassical economic theory: its unedifying focus on prediction and, above all, its inability to explain how the economy really works. As such, it is increasingly recognised that economic phenomena cannot be exclusively investigated as being derived from deterministic, predictable and mechanistic dynamics. Instead, a new approach is required by which history-dependence, organic and ever-evolving processes are (...) also accounted for. As this view implies new challenges and opportunities for policy, we will focus our attention on innovative components of Complexity Theory for the study of economics and the evaluation of public policies. (shrink)

Political scientists have conventionally assumed that achieving democracy is a one-way ratchet. Only very recently has the question of ‘democratic backsliding’ attracted any research attention. We argue that democratic instability is best understood with tools from complexity science. The explanatory power of complexity science arises from several features of complex systems. Their relevance in the context of democracy is discussed. Several policy recommen- dations are offered to help stabilize current systems of representative democracy.

Three objections to Max Urchs's paper on complexity are discussed. First, Urchs's macroeconomic illustrations of the benefits of complexity thinking are open to more conventional interpretations. Second, Urchs formulates a thesis concerning the relationship between science and society which is untenable if taken as a historical claim and insufficiently developed if taken as a metaphor. Third, methodological problems in history and philosophy of science plague Urchs's discussion of neuroscience.