Modern empirical macroeconomic models, known as structural autoregressions (SVARs) are dynamic models that typically claim to represent a causal order among contemporaneously valued variables and to merely represent non-structural (reduced-form) co-occurence between lagged variables and contemporaneous variables. The strategy is held to meet the minimal requirements for identifying the residual errors in particular equations in the model with independent, though otherwise not directly observable, exogenous causes (“shocks”) that ultimately account for change in the model. In nonstationary models, such shocks accumulate (...) so that variables have discernible trends. Econometricians have conceived of variables that trend in sympathy with each other (so-called “cointegrated variables”) as sharing one or more of these unobserved trends as a common cause. It is possible for estimates of the values of both the otherwise unobservable individual shocks and the otherwise unobservable common trends to be backed-out of cointegrated systems of equations. The issue addressed in this paper is whether and in what circumstances these values can be regarded as observations of real entities rather than merely artifacts of the representation of variables in the model. The issue is related, on the one hand, to practical methodological problems in the use of SVARs for policy analysis—e.g., does it make sense to estimate of shocks or trends in one model and then use them as measures of variables in a conceptually distinct model? The issue is also related to debates in the philosophical analysis of causation—particularly, whether we are entitled, as assumed by the developers of Bayes-net approaches, to rely on the causal Markov condition (a generalization of Reichenbach’s common-cause condition) or whether cointegration generates a practical example of Nancy Cartwright’s “byproducts” objection to the causal Markov condition. (shrink)

Complex systems are used, studied and instantiated in science, with what con-sequences? To be clear and systematic in response it is necessary to distin-guish the consequences, for science, of science using and studying complex systems, for philosophy of science, of science using and studying complex systems, for philosophy of science, of philosophy of science modelling sci-ence as a complex system. Each of these is explored in turn, especially. While has been least studied, it will be shown how modelling science as (...) a complex process may change our conception of science and thereby query what a philosophy of science adequate to this complexity might look like. (shrink)

The point of this paper is to provide a principled framework for a naturalistic, interactivist-constructivist model of rational capacity and a sketch of the model itself, indicating its merits. Being naturalistic, it takes its orientation from scientific understanding. In particular, it adopts the developing interactivist-constructivist understanding of the functional capacities of biological organisms as a useful naturalistic platform for constructing such higher order capacities as reason and cognition. Further, both the framework and model are marked by the finitude and fallibility (...) that science attributes to organisms, with their radical consequences, and also by the individual and collective capacities to improve their performances that learning organisms display. Part A prepares the ground for the exposition through a critique of the dominant Western analytic tradition in rationalising science, followed by a brief exposition of the naturalist framework that will be employed to frame the construction. This results in two sets of guidelines for constructing an alternative. Part B provides the new conception of reason as a rich complex of processes of improvement against epistemic values, and argues its merits. It closes with an account of normativity and our similarly developing rational knowledge of it, including (reflexively) of reason itself. (shrink)

The debate over the explanatory nature of cognitive models has been waged mostly between two factions: the mechanists and the dynamical systems theorists. The former hold that cognitive models are explanatory only if they satisfy a set of mapping criteria, particularly the 3M/3m* requirement. The latter have argued, pace the mechanists, that some cognitive models are both dynamical and constitute covering-law explanations. In this paper, I provide a minimal model interpretation of dynamical cognitive models, arguing that this both provides needed (...) clarity to the mechanist versus dynamicist divide in cognitive science and also paves the way towards further insights about scientific explanation generally. (shrink)

In the evolutionary approach to the repeated prisoner's dilemma, strategies spread in populations of emulating and experimenting agents through the principle of survival of the fittest. Although no pure strategy is evolutionarily stable in such populations, the processes of differential strategy propagation provide a promising area of study. This paper employs computer simulations to uncover how these processes govern the oscillating and open-ended evolution of alternative forms of behaviour. Certain `ecological' relationships between important strategy types which are found to be (...) responsible for these behavioural shifts are explored. (shrink)

For several decades, economists have been preoccupied with an attempt to place their entire subject on the ‘sound microfoundations’ of general equilibrium theory, with its individualistic premises. However, this project has run into seemingly intractable problems. This essay examines underlying questions such as the appropriate building block of analysis and the structure of explanation in economics. The examination of biology is found to be instructive, due to debates concerning the limitations of reductionism within that discipline. The final part of the (...) paper argues for the autonomy of a non‐reductionist macroeconomics, based on the institution as the unit of analysis. (shrink)

The more recent computer developments cause us to take a new look at human intelligence. The prevailing occidental view of human intelligence represents a very one-sided, logocentric approach, so that it is becoming more urgent to look for a more complete view. In this way, specific strengths of so-called human information processing are becoming particularly evident in a new way. To provide a general substantiation for this view, some elements of a phenomenological model for a dialectical coherence of human expressions (...) of life are briefly outlined. The starting point is the everyday experience of constantly being confronted with contradictory situations. A model of polar, or dualistic, dialectic is proposed, which attempts to systematically establish the contradictions and contingencies of human life in theoretical structures. It is assumed that formal logic fails to work — strictly speaking — when applied to real situations of human interaction. Instead, definite negations are supposed to be involved. In this way, four polarities, pairs of concepts which are mutually dependent on each other and negate each other definitely, are presented: process and structure, the individual and general (societal), acting and imagining, subject-subject-relation and subject-object-relation (love and work). The latter gives rise to the dialectic of emotion and cognition, which plays a decisive role in a comparison of human and computer-“intelligence”.To cope with the specific human strengths, which are expressed through these polarities, self-learning computers would have to be able to act and to love like human beings and to grow up in a society like people. Furthermore, the learning process would have to implement the process-structure-dialectic with its aspects of finality. In spite of the recent breath-taking achievements of computers, one can not imagine how computers would ever achieve this. Computers are, however, thought of, by virtue of their complexity, being qualitatively different from machines. But human abilities still represent a new level of complexity: the level of dialectic. (shrink)

I distinguish two kinds of contribution that have been made by recent minimalist accounts of joint action in philosophy and cognitive science relative to established philosophical accounts of shared intentional action. The “complementarists” seek to analyze a functionally different kind of joint action from the kind of joint action that is analyzed by established philosophical accounts of shared intentional action. The “constitutionalists” seek to expose mechanisms that make performing joint actions possible, without taking a definite stance on which functional characterization (...) of joint action is the appropriate one. I elucidate the contrasting methodological underpinnings of these minimalist research programs in accordance with Bechtel and Richardson’s account of the heuristics of decomposition and localization as a research strategy for the study of complex systems. (shrink)

Cognitivism in psychology and philosophy is roughly the position that intelligent behavior can (only) be explained by appeal to internal that is, rational thought in a very broad sense. Sections 1 to 5 attempt to explicate in detail the nature of the scientific enterprise that this intuition has inspired. That enterprise is distinctive in at least three ways: It relies on a style of explanation which is different from that of mathematical physics, in such a way that it is not (...) basically concerned with quantitative equational laws; the states and processes with which it deals are in the sense that they are regarded as meaningful or representational; and it is not committed to reductionism, but is open to reduction in a form different from that encountered in other sciences. Spelling these points out makes it clear that the Cognitivist study of the mind can be rigorous and empirical, despite its unprecedented theoretical form. The philosophical explication has another advantage as well: It provides a much needed framework for articulating questions about whether the Cognitivist approach is right or wrong. The last three sections take that advantage of the account, and address several such questions, pro and con. (shrink)

Phyllis Illari and Jon Williamson propose a formulation for a general mechanistic account, the purpose of which is to capture the similarities across mechanistic accounts in the sciences. Illari and Williamson extract insight from mechanisms in astrophysics—which are notably different from the typical biological mechanisms discussed in the literature on mechanisms—to show how their general mechanistic account accommodates mechanisms across various sciences. We present argumentation that demonstrates why an amendment is necessary to the ontology referred to by the general mechanistic (...) account provided by Illari and Williamson. The amendment is required due to the variability of some components in computing mechanisms: the very same component serves as either entity or activity, both between levels and within the same level of the explanatory hierarchy. We argue that the proper ontological account of these mechanistic components involves disambiguation via explicitly indexing them as entities or activities. (shrink)

In examining representations of cities, disease, and human biology, this paper reflects on what technologies reveal of the conditions to which they’re turned.

What counts as a computation and how it relates to cognitive function are important questions for scientists interested in understanding how the mind thinks. This paper argues that pragmatic aspects of explanation ultimately determine how we answer those questions by examining what is needed to make rigorous the notion of computation used in the (cognitive) sciences. It (1) outlines the connection between the Church-Turing Thesis and computational theories of physical systems, (2) differentiates merely satisfying a computational function from true computation, (...) and finally (3) relates how we determine a true computation to the functional methodology in cognitive science. All of the discussion will be directed toward showing that the only way to connect formal notions of computation to empirical theory will be in virtue of the pragmatic aspects of explanation. (shrink)

This work considers the future of driving in terms of both its short- and long-term horizons. It conjectures that human-controlled driving will follow in the footsteps of a wide swath of other, now either residual or abandoned human occupations. Pursuits that have preceded it into oblivion. In this way, driving will dwindle down into only a few niche locales wherein enthusiasts will still persist, much in the way that steam train hobbyists now continue their own aspirational inclinations. Of course, the (...) value of any such prognostication is in direct proportion to the degree that information is conveyed, and prospective uncertainty reduced. In more colloquial terms: the devil is in the details of these coming transitions. It is anticipated that we will see a progressive transformation of the composition of on-road traffic that will be registered most immediately in the realm of professional transportation in which the imperative for optimization exceeds that in virtually all other user segments. The transition from manual control to full automation will be more punctate than gradualist in is evolutionary development. As performance optimization slowly exhausts the commercial sector, it will progressively transition more into the discretionary realm by dint of simple technology transfer alone. The hedonic dimension of everyday driving will be dispersed and pursued by progressively fewer individuals. The traveling window of generational expectation will soon mean that human driving will be largely ‘forgotten,’ as each sequential generation matures without this, still presently common, experience. Indications of this stage of progress are beginning to... (shrink)

We investigate the entrepreneurial opportunities and ethical dilemmas presented by technological turbulence. More specifically we investigate the line between Baumol’s [J. Polit. Econ. 98 (1990) 893] productive (e.g. innovation), unproductive (e.g. rent seeking) and destructive (e.g. criminal) entrepreneurship through three examples of Internet innovation – spam (destructive), music file sharing (unproductive), and Internet pharmacies (potentially productive). The emergence of accessible Internet technologies, under present norms, has created the potential for all three entrepreneurial activities. Because of the propensity for self-serving biases (...) and for bending the rules, the need for creativity in overcoming obstacles and overall liabilities of newness, entrepreneurs are likely to challenge established industrial morals and laws. Unlike new entrants, incumbents must abide by the currently accepted norms, and thus suffer from “liabilities of oldness”. The challenge for new entrants is to change sociopolitical legitimacy, whereas incumbents need to defend the established norms. We discuss competitive and other issues that result from technological turbulence and innovation. (shrink)

Many argue that transgenic technology will have wide-ranging implications for farmers in developing nations. A key concern is that competencies may be destroyed by predominantly foreign multinational transgenic technologies, exacerbating problems of social exclusion in the case of subsistence farmers. Conversely, those that fail to adopt the technology may become uncompetitive, particularly in commodity-based export markets. Drawing on interview data conducted in Brazil and supporting data collected in North America, Europe and China, we found that the impact of transgenic technology (...) varies. It has less impact on farmers that adapt the products to their crop systems and environment, and greater negative implications for less formally educated subsistence farmers in consequence of both complexity and compatibility. Earlier attempts at industrializing agriculture through technological innovation led to vastly improved agricultural output and exports, but the benefits of productivity was not equitably distributed [D. Lee: 2005, American Journal of Agricultural Economics 87, 1325-1334], nor was it designed to meet specific local environmental and socioeconomic farmer conditions, exacerbating social exclusion. Multinationals attempting to introduce transgenic technology without considering the broader social and ethical implications will invite resistance. We discuss the implications for policy makers, multinationals and small-scale farmers. (shrink)

Interactivity has been linked to better performance in problem solving, due in part to a more efficient allocation of attentional resources, a better distribution of cognitive load, but perhaps more important by enabling the reasoner to shape and reshape the physical problem presentation to promote the development of the problem solution. Interactivity in solving quotidian arithmetic problems involves gestures, pointing, and the recruitment of artefacts to facilitate computation and augment efficiency. In the experiment reported here, different types of interactivity were (...) examined with a series of mental arithmetic problems. Using a repeated-measures design, participants solved series of five 11-digit sums in four conditions that varied in the type of interactivity: no interactivity, pointing, pen and paper, and tokens. Performance in the four conditions was measured in terms of accuracy, calculation error, and efficiency. These quantitative analyses were supplemented by a detailed qualitative examination of a participant’s actions in the different conditions. The integration of artefacts, such as tokens or a pen, offered reasoners the opportunity to reconfigure the physical presentation of the problem, enacting different arithmetic strategies: the affordance landscape shifts as the problem trajectory is enacted through interactivity, and this generally produced better “mental” arithmetic performance. Participants also felt more positive about and better engaged with the task when they could reconfigure the problem presentation through interactivity. These findings underscore the importance of engineering task environments in the laboratory that offer a window on how problem solving unfolds through a coalition of mental and physical resources. (shrink)

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