Many activities in Cognitive Science involve complex computer models and simulations of both theoretical and real entities. Artificial Intelligence and the study of artificial neural nets in particular, are seen as major contributors in the quest for understanding the human mind. Computational models serve as objects of experimentation, and results from these virtual experiments are tacitly included in the framework of empirical science. Simulations of cognitive functions, like learning to speak, or discovering syntactical structures in language, are the basis for (...) many claims about human capacities in language acquisition. This raises the question whether results obtained from experiments that are essentially performed on data structures are equivalent to results from "real" experiments. This paper examines some design methodologies for models of cognitive functions using artificial neural nets. The process of conducting the cognitive simulations is largely a projection of theories, or even unsubstantiated conjectures, onto simulated neural structures and an interpretation of the experimental results in terms of the human brain. The problem with this process is that results from virtual experiments are taken to refer unambiguously to the human brain; and the more the language of human cognitive function is deployed in both theory construction and (virtual) experimental interpretation, the more convincing the impression. Additionally, the complexity of the methodologies, principles, and visualization techniques, in the implementation of the computational model, masks the lack of actual similarities between model and real world phenomena. Some computational models involving artificial neural nets have had some success, even commercially, but there are indications that the results from virtual experiments have little value in explaining cognitive functions. The problem seems to be in relating computational, or mathematical, entities to real world objects, like neurons and brains. I argue that the role of Artificial Intelligence as a contributor to the knowledge base of Cognitive Science is diminished as a consequence. (shrink)

Philosophical conceptual analysis is an experimental method. Focusing on this helps to justify it from the skepticism of experimental philosophers who follow Weinberg, Nichols & Stich. To explore the experimental aspect of philosophical conceptual analysis, I consider a simpler instance of the same activity: everyday linguistic interpretation. I argue that this, too, is experimental in nature. And in both conceptual analysis and linguistic interpretation, the intuitions considered problematic by experimental philosophers are necessary but epistemically irrelevant. They are like variables introduced (...) into mathematical proofs which drop out before the solution. Or better, they are like the hypotheses that drive science, which do not themselves need to be true. In other words, it does not matter whether or not intuitions are accurate as descriptions of the natural kinds that undergird philosophical concepts; the aims of conceptual analysis can still be met. (shrink)

Recent trends in the philosophy of mind and cognitive science can be fruitfully characterized as part of the ongoing attempt to come to grips with the very idea of homo sapiens--an intelligent, evolved, biological agent--and its signature contribution is the emergence of a philosophical anthropology which, contra Descartes and his thinking thing, instead puts doing at the center of human being. Applying this agency-oriented line of thinking to the problem of representation, this paper introduces the Guidance Theory, according to which (...) the content and intentionality of representations can be accounted for in terms of the way they provide guidance for action. We offer a brief account of the motivation for the theory, and a formal characterization. (shrink)

Reproducing empirical results and repeating experimental processes is fundamental to science, but is of grave concern to scientists. Revisiting the same location is necessary for tracking biological processes, yet I argue that ‘location’ and ‘replication’ contain a basic ambiguity. The analysis of the practical meanings of ‘replication’ and ‘location’ will strip of incommensurability from its common conflation with empirical equivalence, underdetermination and indeterminacy of reference. In particular, I argue that three biodiversity re-surveys, conducted by the research institutions of Harvard, Berkeley, (...) and Hamaarag, all reveal incommensurability without indeterminacy in the smallest spatial scale, and indeterminacy without incommensurability in higher scales. (shrink)

Understanding scientific modelling can be divided into two sub-projects: analysing what model-systems are, and understanding how they are used to represent something beyond themselves. The first is a prerequisite for the second: we can only start analysing how representation works once we understand the intrinsic character of the vehicle that does the representing. Coming to terms with this issue is the project of the first half of this chapter. My central contention is that models are akin to places and characters (...) of literary fictions, and that therefore theories of fiction play an essential role in explaining the nature of model-systems. This sets the agenda. Section 2 provides a statement of this view, which I label the fiction view of model-systems, and argues for its prima facie plausibility. Section 3 presents a defence of this view against its main rival, the structuralist conception of models. In Section 4 I develop an account of model-systems as imagined objects on the basis of the so-called pretence theory of fiction. This theory needs to be discussed in great detail for two reasons. First, developing an acceptable account of imagined objects is mandatory to make the fiction view acceptable, and I will show that the pretence theory has the resources to achieve this goal. Second, the term ‘representation’ is ambiguous; in fact, there are two very different relations that are commonly called ‘representation’ and a conflation between the two is the root of some of the problems that beset scientific representation. Pretence theory provides us with the conceptual resources to articulate these two different forms of representation, which I call p-representation and t-representation respectively. Putting these elements together provides us with a coherent overall picture of scientific modelling, which I develop in Section 5. (shrink)

In this paper, I challenge the long-established view that the term phlogiston fails to refer. After a close examination of the reference of phlogiston during Lavoisier’s Chemical Revolution, I show that it referred throughout to a natural substance, fire matter. I state that Lavoisier eliminated the term but not its referent, which he renamed caloric, and I claim that it is in the historical and cultural context of the Chemical Revolution that the Lavoisier’s intentions can be understood.

In Science, Truth, and Democracy (2001a), Kitcher moderates the strongest ontological realist thesis he defended in The Advancement of Science (1993a), with the aim of making compatible the correspondence theory of truth with conceptual relativity. However, it is not clear that both things could be harmonized. If our knowledge of the world is mediated by our categories and concepts; if the selection of these categories and concepts may vary according to our interests, and they are not the consequence of the (...) existence of certain supposed natural kinds or some intrinsic structure of the world, it is very problematic to establish what our true statements correspond to. This paper analyzes the transformation in Kitcher's realism and expounds the main difficulties in this project. Finally, a modality of moderate ontological realism will be proposed that, despite of keeping the sprit of the conceptual relativity, is strong enough to support the correspondence theory of truth. (shrink)

Watson and Crick’s discovery of the structure of DNA led to developments that transformed many biological sciences. But what were the relevant developments and how did they transform biology? Much of the philosophical discussion concerning this question can be organized around two opposing views: theoretical reductionism and layer-cake antireductionism. Theoretical reductionist and their anti-reductionist foes hold two assumptions in common. First, both hold that biological knowledge is structured like a layer cake, with some biological sciences, such as molecular biology cast (...) at lower levels of organization, and others, such as classical genetics, cast at higher levels. Second, both assume that scientific knowledge is structured by theory and that the productivity of scientific research depends on whether the underlying theory identifies the fundamentals upon which the phenomena to be explained and investigated depend. In the first part of this paper, I challenge these assumptions. In the second part, I show how recasting the basic theory of classical genetics made it possible to retool the methodologies of genetics. It was the investigative power of these retooled methodologies, and not the explanatory power of a gene-based theory, that transformed biology. (shrink)

This paper aims to bring the epistemic dimensions of stem cell experiments out of the background, and show that they can be critically evaluated. After introducing some basic concepts of stem cell biology, I set out the current “gold standard” for experimental success in that field (§2). I then trace the origin of this standard to a 1988 controversy over blood stem cells (§3). Understanding the outcome of this controversy requires attention to the details of experimental techniques, the organization of (...) epistemic communities, and relations between the two (§4). With its resolution, a standard for experimental success was established for HSC research, which in turn serves as an exemplar for studies of other stem cells. This historical case study reveals a robust standard for experimental success in stem cell biology: to trace processes of development at the single-cell level, in the form of cell lineage hierarchies. Experiments conforming to this standard can be further critically assessed as means to the therapeutic end of stem cell research: use of stem cells to repair human organs and tissues. (shrink)

The paper shows epistemological, methodological and ontological peculiarities of chemistry taken as a classificatory science of materials using experimental methods. Without succumbing to standard interpretations of physical science, chemical methods of experimental investigation, classification, reference, theorizing, prediction and production of new entities are developed one by one as first steps towards a philosophy of chemistry. Chemistry challenges traditional concepts of empirical object, empirical predicate, reference frame and theory, but also the distinction commonly drawn between natural science and technology. Due to (...) its many peculiarities, I propose to treat chemistry philosophically as a special type of science, apart from other sciences. (shrink)

The main aim of our paper is to show that interpretative issues belonging to classical General Relativity (GR) might be preliminary to a deeper understanding of conceptual problems stemming from on-going attempts at constructing a quantum theory of gravity. Among such interpretative issues, we focus on the meaning of general covariance and the related question of the identity of points, by basing our investigation on the Hamiltonian formulation of GR. In particular, we argue that the adoption of a peculiar gauge-fixing (...) within the canonical reduction of ADM metric gravity may yield a new solution to the debate between substantivalists and relationists, by suggesting a \emph{tertium quid} between these two age-old positions. Such a third position enables us to evaluate the controversial relationship between entity realism and structural realism in a well-defined case study. After having indicated the possible developments of this approach in Quantum Gravity, we discuss the structuralist and holistic features of the class of spacetime models that are used in the above mentioned canonical reduction. (shrink)

This is a defense of the doctrine of scientific realism. SR is defined through the following two claims: Most essential unobservables posited by the well-established current scientific theories exist independently of our minds. We know our well-established scientific theories to be approximately true. I first offer positive argumentation for SR. I begin with the so-called 'success arguments' for SR: 1) scientific theories most of the times entail successful predictions; 2) science is methodologically successful in generating empirically successful theories. SR explains (...) these facts via inference to the best explanation. I combine Hacking's experimental argument for entity realism with Salmon's common-cause principle. I take entity realism to be foundational to SR: one may believe in the existence of some theoretical entities without believing in any particular theory in which these are embedded. Its motivation comes from experimental practice, where the manipulation of these entities often relies on incompatible theoretical accounts. The underdetermination topic is thereafter discussed. Several attempts to distinguish between an observable and an unobservable realm are critically discussed, as well as the possibility that for any given theory, there are empirically equivalents generated by means of algorithms. I present extensive argumentation to the effect that such algorithmic rivals are not to be taken seriously. Social constructivism is being critically treated. I proceed by distinguishing between a metaphysical, a semantic, and an epistemic variant of SC. I conclude that only a moderate metaphysical constructivism can stand on its own feet. Its claim is merely that some facts about the world are socially constructed. I finish with a plea for a selective SR, able to do justice to the presence of both instrumentalism and modest constructivism in scientific practice. (shrink)

One of the least explored areas of C.S. Peirce's wide range of work is his contributions to psychology and the philosophy of mind. This dissertation examines the corpus of this work, especially as it relates to the subjects of mind, habit, instinct, sentiment, emotion, perception, consciousness, cognition, and community. The argument is that Peirce's contributions to these areas of investigation were both highly original and heavily influenced by the main intellectual currents of his time. An effort has been made to (...) present Peirce's philosophy without apology, within the conceptual framework and idiom of its time, and without appeal to a comprehensive view that Peirce never articulated. Nevertheless, as several noted interpreters have argued, much of this work can be viewed through the lens of Peirce's innovative theory of signs and the notion of the semiotic triad as its central unifying feature, despite the fact that the general theory was itself under continuous refinement and remained incomplete at the time of his death. Another hermeneutical device employed is William James' better known and more accessible work which, when juxtaposed with Peirce's ideas, serves to bring them into sharper relief. While general and historical in the presentation of material, this study seeks, at the same time, to engage the criticism of contemporary Peirce scholars in an attempt to account for several of the conundrums inherent in Peirce's work. Among the problems with implications for his philosophy of mind and theory of inquiry are the limitations of his theory of continuity, his negative view of the self, his somewhat ambiguous position on the relation of psychology to logic, and the metaethical puzzle arising from application of his theory of probable inference to truly fateful decisions. These problems provide an interesting perspective and lend balance to the truly insightful contributions Peirce made to the discovery of the mind. (shrink)

Neuroeconomics is an emerging field crossing neuroscientific data, the use of brain-imaging tools, experimental and behavioral economics, and an attempt at a better understanding of the cognitive assumptions that underlie theoretical predictive economic models. In this paper the authors try two things: 1) To assess the epistemological biases that affect Neuroeconomics as it is currently done. A number of significant experiments are discussed in that perspective. 2) To imagine an original way - apart from what is already being done - (...) to run experiments in brain-imaging that are relevant to the discussion of rationality assumptions at the core of economic theory. (shrink)

The unpredictability of the development and results of a research program is often invoked in favor of a free, desinterested science that would be led mainly by scientific curiosity, in contrast with a use-inspired science led by definite practical expectations. This paper will challenge a crucial but underexamined assumption in this line of defense of scientific freedom, namely that a free science is the best system of science to generate unexpected results. We will propose conditions favoring the occurrence of unexpected (...) facts in the course of a scientific investigation and then establish that use-inspired science actually scores better in this area. (shrink)

A heated debate surrounds the significance of reproducibility as an indicator for research quality and reliability, with many commentators linking a "crisis of reproducibility" to the rise of fraudulent, careless and unreliable practices of knowledge production. Through the analysis of discourse and practices across research fields, I point out that reproducibility is not only interpreted in different ways, but also serves a variety of epistemic functions depending on the research at hand. Given such variation, I argue that the uncritical pursuit (...) of reproducibility as an overarching epistemic value is misleading and potentially damaging to scientific advancement. Requirements for reproducibility, however they are interpreted, are one of many available means to secure reliable research outcomes. Furthermore, there are cases where the focus on enhancing reproducibility turns out not to foster high-quality research. Scientific communities and Open Science advocates should learn from inferential reasoning from irreproducible data, and promote incentives for all researchers to explicitly and publicly discuss their methodological commitments, the ways in which they learn from mistakes and problems in everyday practice, and the strategies they use to choose which research component of any project needs to be preserved in the long term, and how. (shrink)

In the first half of this dissertation, I develop a heuristic methodology for analyzing scientific solutions to the problem of underdetermination. Heuristics are rough-and-ready procedures used by scientists to construct models, design experiments, interpret evidence, etc. But as powerful as they are, heuristics are also error-prone. Therefore, I argue that they key to prudently using a heuristic is the articulation of meta-heuristics---guidelines to the kinds of problems for which a heuristic is well- or ill-suited. Given that heuristics will introduce certain (...) errors into our scientific investigations, I emphasize the importance of a particular category of meta-heuristics involving the search for robust evidence. Robustness is understood to be the epistemic virtue bestowed by agreement amongst multiple modes of determination. The more modes we have at our disposal, and the more these confirm the same result, the more confident can we be that a result is not a mere artifact of some heuristic simplification. Through an analysis of case-studies in the philosophy of biology and clinical trials, I develop a principled method for modeling and evaluating heuristics and robustness claims in a qualitative problem space. The second half of the dissertation deploys the heuristic methodology to address ethical and epistemological issues in the science of clinical trials. To that end, I develop a network model for the problem space of clinical research, capable of representing the various kinds of experiments, epistemic relationships, and ethical justifications intrinsic to the domain. I then apply this model to ongoing research with the antibacterial agent, moxifloxacin, for the treatment of tuberculosis, tracking its development from initially successful and promising in vitro and animal studies to its disappointing and discordant performance across five human efficacy trials. Given this failure to find a robust result with moxifloxacin across animal and human studies, what should researchers now do? While my final analysis of this case does not definitively answer that question, I demonstrate how my methodology, unlike a statistical meta-analysis, helps to clarify the directions for further research. (shrink)

My scientific field is theoretical physics. My philosophical orientation is phenomenology, especially hermeneutical phenomenology, as modified and extended under the influence of Bernard Lonergan's cognitional theory. In fact, I was already deeply under the influence of Bernard Lonergan's workbefore I went to Louvain/Leuven to study phenomenology as a propaedeutic to my preparation in the philosophy of science. The specific topic of this paper is one close to the center of Philip's interest, namely, to articulate the right balance among theory, experiment, (...) and what Husserl called 'die Sache selbst' or the 'givenness' of scientific objects as experienced and understood. The method I shall adopt is that of Husserl's phenomenology of perception, as modified by Lonergan's method of 'self-appropriation.' I will be concerned then with the 'constitution' of experimental data in science - any science. (shrink)

Large part of contemporary science is in fact technoscience, in the sense that it crucially depends on several technologies for the generation, collection, and analysis of data. This prompts a re-examination of the relations between science and technologies. In this essay, I advance the view that we’d better move beyond the ‘subordination view’ and the ‘instrumental’ view. The first aims to establish the primacy of science over technology, and the second uses technology instrumentally to support a realist position about theoretical (...) entities. I suggest that we should instead concentrate on how science and technology interact. This will reveal that technology has a poietic character, namely it actively partakes in the production of knowledge. But this poietic character can only be understood within the cognitive activity of scientific communities. Current research in molecular epidemiology, notably the projects funded within the ‘European exposome initiative’, serves as a motivation for such discussion and as an illustration of the claims made. (shrink)

In this essay we introduce the idea of an epistemic triangle, with factual, theoretical, and conceptual investigations at its vertices, and argue that whereas scientific progress requires a balance among the three types of investigations, psychology's epistemic triangle is stretched disproportionately in the direction of factual investigations. Expressed by a variety of different problems, this unbalance may be created by a main operative theme—the obsession of psychology with a narrow and mechanical view of the scientific method and a misguided aversion (...) to conceptual inquiries. Hence, to redress psychology's epistemic triangle, a broader and more realistic conception of method is needed and, in particular, conceptual investigations must be promoted. Using examples from different research domains, we describe the nature of conceptual investigations, relate them to theoretical investigations, and illustrate their purposes, forms, and limitations. (shrink)

In 2002 the readers of the scientific magazine 'Physics World' voted Young's double-slit experiment applied to the interference of single electrons to be 'the most beautiful experiment in physics'; this experiment, in truth, had already been carried out 30 years beforehand. The present article aims to re-examine the latter real experiment and put it into its proper historical perspective. Even though the experiment was not afforded the importance it perhaps deserved among philosophers, its philosophical mplications add new arguments to the (...) already far-reaching debate triggered off by the ideal experiment. Within the context of quantum mechanics in particular, the experiment revealed for the first time the importance that ought to be attributed at the empirical level to single-case probability, that is, to the probability of a single electron's reaching the screen. I investigate how the empirical significance of the experimental results comes within the framework of the debate over the propensity interpretation of probability in quantum mechanics. I argue that the experiment, when examined in all its technical details does in fact throw light on the evidence for the propensity, as a physical property, of micro-objects. (shrink)

In biomedical measurement, biomarkers are used to achieve reliable prediction of, and useful causal information about patient outcomes while minimizing complexity of measurement, resources, and invasiveness. A biomarker is an assayable metric that discloses the status of a biological process of interest, be it normative, pathophysiological, or in response to intervention. The greatest utility from biomarkers comes from their ability to help clinicians (and researchers) make and evaluate clinical decisions. In this paper we discuss a specific methodological use of clinical (...) biomarkers in pharmacological measurement: Some biomarkers, called ‘surrogate markers’, are used to substitute for a clinically meaningful endpoint corresponding to events and their penultimate risk factors. We confront the reliability of clinical biomarkers that are used to gather information about clinically meaningful endpoints. Our aim is to present a systematic methodology for assessing the reliability of multiple surrogate markers (and biomarkers in general). To do this we draw upon the robustness analysis literature in the philosophy of science and the empirical use of clinical biomarkers. After introducing robustness analysis we present two problems with biomarkers in relation to reliability. Next, we propose an intervention-based robustness methodology for organizing the reliability of biomarkers in general. We propose three relevant conditions for a robust methodology for biomarkers: (R1) Intervention-based demonstration of partial independence of modes: In biomarkers partial independence can be demonstrated through exogenous interventions that modify a process some number of “steps” removed from each of the markers. (R2) Comparison of diverging and converging results across biomarkers: By systematically comparing partially-independent biomarkers we can track under what conditions markers fail to converge in results, and under which conditions they successfully converge. (R3) Information within the context of theory: Through a systematic cross-comparison of the markers we can make causal conclusions as well as eliminate competing theories. We apply our robust methodology to currently developing Alzheimer’s research to show its usefulness for making causal conclusions. (shrink)

In everyday usage, ‘realism’ is often used as a name for a practically or epistemically low-ambition attitude, while ‘idealism’ is often taken to denote a highambition—if not utopian—attitude. In philosophcal usage, mostly, it is the other way around: those who are called realists tend to claim more than their opponents—they are the philosophical optimists. Within philosophy itself, ‘realism’ adopts a variety of interrelated and contested meanings. It is used as the name for doctrines about issues such as perceptual access to (...) reality, the existence of universals, the goals and achievements of science, the nature of truth, the objectivity of morality, and many other things. Given this variety, no single shorthand definition of the term ‘realism’ can be provided. One manifestation of this variety is that the opponents of realism about these issues are not called uniformly by a single label (other than the rather uninformative ‘antirealism’): the labels used include idealism, phenomenalism, instrumentalism, conventionalism, fictionalism, noncognitivism, constructivism, relativism, irrealism, and others. Sometimes such labels vary from one dispute or domain to another even when similar ideas are being expressed. Sometimes they are used to make claims that are specific to the domain at hand and distinct from other antirealist theses. In what follows a brief tour will be taken along some of the representative philosophical highways and lanes, from ontology through semantics to epistemology. Along the way, realism will be confronted with some of its various opponents and internal conflicts. The philosophical landscape in the neighborhood of realism is nowadays much broader than it used to be: in a typical older encyclopedia, ‘realism’ was taken to name doctrines about universals or about perception, or both, to the exclusion of much of its present coverage, and many of the current opponents were missing from view altogether. (shrink)

At the beginning of the 20th century, Gestalt psychologists put forward the concept of psychoneural isomorphism, which was meant to replace Fechner’s obscure notion of psychophysical parallelism and provide a heuristics that may facilitate the search for the neural correlates of the mind. However, the concept has generated much confusion in the debate, and today its role is still unclear. In this contribution, I will attempt a little conceptual spadework in clarifying the concept of psychoneural isomorphism, focusing exclusively on conscious (...) visual perceptual experience and its neural correlates. Firstly, I will outline the history of our concept, and its alleged metaphysical and epistemic roles. Then, I will clarify the nature of isomorphism and rule out its metaphysical role. Finally, I will review some epistemic roles of our concept, zooming in on the work of Jean Petitot, and suggest that it does not play a relevant heuristic role. I conclude suggesting that psychoneural isomorphism might be an indicator of robustness for certain mathematical descriptions of perceptual content. (shrink)

Recientemente, Alexander Bird (2007) sugirió que la ciencia progresa cuando muestra “acumulación de conocimiento justificado”. Para validar su postura, Bird contrastó sus ideas con los conceptos sobre el progreso científico construidos por Thomas S. Kuhn y Larry Laudan, respectivamente. El objetivo de Bird fue mostrar que el criterio de “resolución de problemas” defendido por estos autores, es regresivo y, por ello, anti-intuitivo. En este texto analizo los argumentos de Bird en contra de estos autores y muestro en qué fallan. Posteriormente (...) se evalúa su postura a partir de sus propios fundamentos epistemológicos. Al final, presento algunas conclusiones que pueden inferirse del presente estudio. (shrink)

Both thought experiments and simulation experiments apparently belong to the family of experiments, though they are somewhat special members because they work without intervention into the natural world. Instead they explore hypothetical worlds. For this reason many have wondered whether referring to them as “experiments” is justified at all. While most authors are concerned with only one type of “imagined” experiment – either simulation or thought experiment – the present chapter hopes to gain new insight by considering what the two (...) types of experiment share, and what they do not. A close look reveals at least one fundamental methodological difference between thought and simulation experiments: while thought experiments are a cognitive process that employs intuition, simulation experiments rest on automated iterations of formal algorithms. It will be argued that this difference has important epistemological ramifications. (shrink)