An analysis of two heuristic strategies for the development of mechanistic models, illustrated with historical examples from the life sciences. In Discovering Complexity, William Bechtel and Robert Richardson examine two heuristics that guided the development of mechanistic models in the life sciences: decomposition and localization. Drawing on historical cases from disciplines including cell biology, cognitive neuroscience, and genetics, they identify a number of "choice points" that life scientists confront in developing mechanistic explanations and show how different choices result in (...) divergent explanatory models. Describing decomposition as the attempt to differentiate functional and structural components of a system and localization as the assignment of responsibility for specific functions to specific structures, Bechtel and Richardson examine the usefulness of these heuristics as well as their fallibility—the sometimes false assumption underlying them that nature is significantly decomposable and hierarchically organized. When Discovering Complexity was originally published in 1993, few philosophers of science perceived the centrality of seeking mechanisms to explain phenomena in biology, relying instead on the model of nomological explanation advanced by the logical positivists (a model Bechtel and Richardson found to be utterly inapplicable to the examples from the life sciences in their study). Since then, mechanism and mechanistic explanation have become widely discussed. In a substantive new introduction to this MIT Press edition of their book, Bechtel and Richardson examine both philosophical and scientific developments in research on mechanistic models since 1993. (shrink)

Book review of Bechtel and Richardson, Discovering Complexity (1993). Review suggests that one theme of the book -- that scientific reason is "constituted" in part by a cognitive strategy of finding complexity -- is not fully supported.

The very expertise with which psychologists wield their tools for achieving laboratory control may have had the unwelcome effect of blinding psychologists to the possibilities of discovering principles of behavior without conducting experiments. When creatively interrogated, a diverse range of large, real-world data sets provides powerful diagnostic tools for revealing principles of human judgment, perception, categorization, decision-making, language use, inference, problem solving, and representation. Examples of these data sets include patterns of website links, dictionaries, logs of group interactions, collections (...) of images and image tags, text corpora, history of financial transactions, trends in twitter tag usage and propagation, patents, consumer product sales, performance in high-stakes sporting events, dialect maps, and scientific citations. The goal of this issue is to present some exemplary case studies of mining naturally existing data sets to reveal important principles and phenomena in cognitive science, and to discuss some of the underlying issues involved with conducting traditional experiments, analyses of naturally occurring data, computational modeling, and the synthesis of all three methods. (shrink)

What kinds of norms constrain mechanistic discovery and explanation? In the mechanistic literature, the norms for good explanations are directly derived from answers to the metaphysical question of what explanations are. Prominent mechanistic accounts thus emphasize either ontic (Craver, in: Kaiser, Scholz, Plenge, Hüttemann (eds) Explanation in the special sciences: the case of biology and history, Springer, Dordrecht, pp 27–52, 2014) or epistemic norms (Bechtel in Mental mechanisms: philosophical perspectives on cognitive neuroscience, Routledge, London, 2008). Still, mechanistic philosophers on both (...) sides agree that there is no sharp distinction between the processes of discovery and explanation (Bechtel and Richardson in Discovering complexity. Decomposition and localization as strategies in scientific research, MIT Press, Cambridge, 2010; Craver and Darden in In search of mechanisms: discoveries across the life sciences, University of Chicago Press, Chicago, 2013). Thus, it seems reasonable to expect that ontic and epistemic accounts of explanation will be accompanied by ontic and epistemic accounts of discovery, respectively. As we will show here, however, recent discovery accounts implicitly rely on both ontic and epistemic norms to characterize the discovery process. In this paper, we develop an account that makes explicit that, and how, ontic and epistemic norms work together throughout the discovery process. By describing mechanism discovery as a process of pattern recognition (Haugeland, in: Having thought. Essays in the metaphysics of mind, Harvard University Press, Cambridge, pp 267–290, 1998) we demonstrate that scientists have to develop epistemic activities to distinguish a pattern from its background. Furthermore, they have to determine which epistemic activities successfully describe how the pattern is implemented by identifying the pattern’s components. Our approach reveals that ontic and epistemic norms are equally important in mechanism discovery. (shrink)

Scientific discovery is often regarded as romantic and creative - and hence unanalyzable - whereas the everyday process of verifying discoveries is sober and more suited to analysis. Yet this fascinating exploration of how scientific work proceeds argues that however sudden the moment of discovery may seem, the discovery process can be described and modeled. Using the methods and concepts of contemporary information-processing psychology (or cognitive science) the authors develop a series of artificial-intelligence programs that can simulate the (...) human thought processes used to discover scientific laws. The programs - BACON, DALTON, GLAUBER, and STAHL - are all largely data-driven, that is, when presented with series of chemical or physical measurements they search for uniformities and linking elements, generating and checking hypotheses and creating new concepts as they go along. "Scientific Discovery examines the nature of scientific research and reviews the arguments for and against a normative theory of discovery; describes the evolution of the BACON programs, which discover quantitative empirical laws and invent new concepts; presents programs that discover laws in qualitative and quantitative data; and ties the results together, suggesting how a combined and extended program might find research problems, invent new instruments, and invent appropriate problem representations. Numerous prominent historical examples of discoveries from physics and chemistry are used as tests for the programs and anchor the discussion concretely in the history of science. Pat Langley is an Associate Professor in the Department of Information and Computer Science at the University of California, Irvine.Herbert Simon is a Professor in the Departments of Psychology, Computer Science, and Philosophy at Carnegie-Mellon University. Gary L. Bradshaw is an Assistant Professor in the Department of Psychology and Institute of Cognitive Science at the University of Colorado, Boulder. Jan M. Zytkow is an Associate Professor in the Computer Science Department at Wichita State University. (shrink)

Examines the processes of scientific creativity and discovery, and proposes a model of scientific development.

If the decades of the forties through the sixties were dominated by discussion of Hempel's “covering law“ explication of explanation, that of the seventies was preoccupied with Salmon's “statistical relevance” conception, which emerged as the principal alternative to Hempel's enormously influential account. Readers of Wesley C. Salmon's Scientific Explanation and the Causal Structure of the World, therefore, ought to find it refreshing to discover that its author has not remained content with a facile defense of his previous investigations; on (...) the contrary, Salmon offers an original account of different kinds of explications, advances additional criticisms of various alternative theories, and elaborates a novel “two-tiered“ analysis of explanation that tacitly depends upon a “two-tiered” account of homogeneity. Indeed, if the considerations that follow are correct, Salmon has not merely refined his statistical relevance account but has actually abandoned it in favor of a “causal/mechanistic“ construction. This striking development suggests that the theory of explanation is likely to remain as lively an arena of debate in the eighties as it has been in the past. (shrink)

This paper is concerned with the construction of theories of software systems yielding adequate predictions of their target systems’ computations. It is first argued that mathematical theories of programs are not able to provide predictions that are consistent with observed executions. Empirical theories of software systems are here introduced semantically, in terms of a hierarchy of computational models that are supplied by formal methods and testing techniques in computer science. Both deductive top-down and inductive bottom-up approaches in the discovery of (...) semantic software theories are refused to argue in favour of the abductive process of hypothesising and refining models at each level in the hierarchy, until they become satisfactorily predictive. Empirical theories of computational systems are required to be modular, as modular are most software verification and testing activities. We argue that logic relations must be thereby defined among models representing different modules in a semantic theory of a modular software system. We exclude that scientific structuralism is able to define module relations needed in software modular theories. The algebraic Theory of Institutions is finally introduced to specify the logic structure of modular semantic theories of computational systems. (shrink)

In this essay we argue that the notion of machine necessarily includes its being designed for a purpose. Therefore, being a mechanical system is not enough for being a machine. Since the experimental scientific method excludes any consideration of finality on methodological grounds, it is then also insufficient to fully understand what machines are. Instead in order to understand a machine it is first required to understand its purpose, along with its structure, in clear parallel with Aristotle’s final and (...) formal causes. Obviously, purpose and structure are not machine components that can physically interact with other components; nonetheless they are essential to understanding their operation. This casts an interesting light on the relationship between mind and body: for just as an artifact’s finality and structure explain its operation, so also consciousness is the explanation—not the efficient cause—of specifically human behavior. What machines and human beings have in common is that, in order to understand them, it is necessary to appeal to the principle of finality. Yet while finality is given and extrinsic in the case of machines, we human beings are characterized by the ability to self-propose our own ends. Since the principle of finality is essential to understanding the production of machines, the traditional view in modern Western philosophy that finality lies beyond the scope of objective/scientific knowledge should be rectified to allow for a genuine science of the artificial. We think a correct understanding of final causality will overcome current resistance to this principle. (shrink)

A scientific community cannot practice its trade without some set of received beliefs. These beliefs form the foundation of the "educational initiation that prepares and licenses the student for professional practice". The nature of the "rigorous and rigid" preparation helps ensure that the received beliefs are firmly fixed in the student's mind. Scientists take great pains to defend the assumption that scientists know what the world is like...To this end, "normal science" will often suppress novelties which undermine its foundations. (...) Research is therefore not about discovering the unknown, but rather "a strenuous and devoted attempt to force nature into the conceptual boxes supplied by professional education". (shrink)

The empirical exploration of the neural mechanisms of consciousness is undoubtedly going to be one of the most central lines of research in the scientific study of consciousness. Therefore, it is important for the researchers involved in these studies to have a clear idea of the phenomenon they are searching for and of the capabilities of the methods they are using to accomplish the task. The main point of my paper ‘Can functional brain imaging discover consciousness in the brain?’ (...) was to explicate and clarify these issues that, although central metatheoretical problems for cognitive neuroscience, have not received much attention from either the experimental neuroscientists or the philosophers involved in the study of consciousness. (shrink)

Few philosophers of science have influenced as many readers as Thomas S. Kuhn. Yet no comprehensive study of his ideas has existed--until now. In this volume, Paul Hoyningen-Huene examines Kuhn's work over four decades, from the days before The Structure of Scientific Revolutions to the present, and puts Kuhn's philosophical development in a historical framework. Scholars from disciplines as diverse as political science and art history have offered widely differing interpretations of Kuhn's ideas, appropriating his notions of paradigm shifts (...) and revolutions to fit their own theories, however imperfectly. Hoyningen-Huene does not merely offer another interpretation--he brings Kuhn's work into focus with rigorous philosophical analysis. Through extended discussions with Kuhn and an encyclopedic reading of his work, Hoyningen-Huene looks at the problems and justifications of his claims and determines how his theories might be expanded. Most significantly, he discovers that The Structure of Scientific Revolutions can be understood only with reference to the historiographic foundation of Kuhn's philosophy. Discussing the concepts of paradigms, paradigm shifts, normal science, and scientific revolutions, Hoyningen-Huene traces their evolution to Kuhn's experience as a historian of contemporary science. From here, Hoyningen-Huene examines Kuhn's well-known thesis that scientists on opposite sides of a revolutionary divide "work in different worlds," explaining Kuhn's notion of a world-change during a scientific revolution. He even considers Kuhn's most controversial claims--his attack on the distinction between the contexts of discovery and justification and his notion of incommensurability--addressing both criticisms and defenses of these ideas. Destined to become the authoritative philosophical study of Kuhn's work, Reconstructing Scientific Revolutions both enriches our understanding of Kuhn and provides powerful interpretive tools for bridging Continental and Anglo-American philosophical traditions. (shrink)

Phronesis is often described as a ‘practical wisdom’ adapted to the matters of everyday human life. Phronesis enables one to judge what is at stake in a situation and what means are required to bring about a good outcome. In medicine, phronesis tends to be called upon to deal with ethical issues and to offer a critique of clinical practice as a straightforward instrumental application of scientific knowledge. There is, however, a paucity of empirical studies of phronesis, including in (...) medicine. Using a hermeneutic and phenomenological approach, this inquiry explores how phronesis is manifest in the stories of clinical practice of eleven exemplary physicians. The findings highlight five overarching themes: ethos (or character) of the physician, clinical habitus revealed in physician know-how, encountering the patient with attentiveness, modes of reasoning amidst complexity, and embodied perceptions (such as intuitions or gut feeling). The findings open a discussion about the contingent nature of clinical situations, a hermeneutic mode of clinical thinking, tacit dimensions of being and doing in clinical practice, the centrality of caring relations with patients, and the elusive quality of some aspects of practice. This study deepens understandings of the nature of phronesis within clinical settings and proposes ‘Clinical phronesis’ as a descriptor for its appearance and role in the daily practice of (exemplary) physicians. (shrink)

How do scientific models represent in a way that enables us to discover new truths about reality and draw inferences about it? Contemporary accounts of scientific discovery answer this question by focusing on the cognitive mechanisms involved in the generation of new ideas and concepts in terms of a special sort of reasoning—or model-based reasoning—involving imagery. Alternatively, I argue that answering this question requires that we recognise the crucial role of the propositional imagination in the construction and development (...) of models for the purpose of generating hypotheses that are plausible candidates for truth. I propose simple fictionalism as a new account of models as Waltonian games of make-believe and suggest that models can lead to genuine scientific discovery when they are used as representations that denote real world phenomena and generate two main kinds of theoretical hypotheses, model-world comparisons and direct attributions. (shrink)

In “Scientific Knowledge,” Philip Kitcher challenges arguments that deny the truth of the theoretical claims of science, and he attempts to discover reasons for endorsing the truth of such claims. He suggests that the discovery of such reasons might succeed if we ask why anyone thinks that the theoretical claims we accept are true and then look for answers that reconstruct actual belief‐generating processes. To this end, Kitcher presents the “homely argument” for scientific truth, which claims that when (...) a field of science is continually applied to yield precise predictions, then it is at least approximately true. He defends this approach and offers a supplementary account that gives more attention to detail. This account includes a historical aspect that must answer to skeptical challenges and a social aspect. (shrink)

Can we expect our scientific theories to make up a unified structure, or do they form a kind of “patchwork” whose pieces remain independent from each other? Does the proliferation of sometimes-incompatible representations of the same phenomenon compromise the ability of science to deliver reliable knowledge? Is there a single correct way to classify things that science should try to discover, or is taxonomic pluralism here to stay? These questions are at the heart of philosophical debate on the unity (...) or plurality of science, one of the most central issues in philosophy of science today. This book offers a critical overview and a new structure of this debate. It focuses on the methodological, epistemic, and metaphysical commitments of various philosophical attitudes surrounding monism and pluralism, and offers novel perspectives and pluralist theses on scientific methods and objects, reductionism, plurality of representations, natural kinds, and scientific classifications. (shrink)

The application of hierarchy theory to ecological systems presents those who seek a radical change in human perspectives toward nature with a unique window of opportunity. Because hierarchy theory has enabled scientific ecologists to discover that the window through which one chooses to observe a system influences its reality, they may now be more amenable to including the perspectives of deep and feminist ecologists into their self-definition. A synergy between deep, feminist, and scientific ecology could improve environmental policy (...) by encouraging more ecofeminists to encompass the marginalisation of nonhuman life-forms within the ethic of care, more deep ecologists to encompass the issues of overconsumption and militarisation within the anthropocentric-biocentric polarity, and more scientific ecologists to scrutinise the politics behind their investigations. (shrink)

This study is concerned with processes for discovering new theories in science. It considers a computational approach to scientific discovery, as applied to the discovery of theories in cognitive science. The approach combines two ideas. First, a process-based scientific theory can be represented as a computer program. Second, an evolutionary computational method, genetic programming, allows computer programs to be improved through a process of computational trialand-error. Putting these two ideas together leads to a system that can automatically (...) generate and improve scientific theories. The application of this method to the discovery of theories in cognitive science is examined. Theories are built up from primitive operators. These are contained in a theory language that defines the space of possible theories. An example of a theory generated by this method is described. These results support the idea that scientific discovery can be achieved through a heuristic search process, even for theories involving a sequence of steps. However, this computational approach to scientific discovery does not eliminate the need for human input. Human judgment is needed to make reasonable prior assumptions about the characteristics of operators used in the theory generation process, and to interpret and provide context for the computationally generated theories. (shrink)

The aim of this paper is twofold: The general aim is to shed light on the structure of species discoveries new to biology by bringing together a practice-oriented philosophy of science perspective with a philosophy of language perspective. The more specific aim is to argue that and to show how the overall structure of biological species discoveries comprises aspects of both institutional and non-institutional reality. The author proceeds as follows: he shows that placing the focus on the topic of (...) class='Hi'>scientific discoveries enables us to circumvent two long-standing problems. He analyzes three fictional cases of discoveries in order to bring about a greater sensitivity for the concept of discovery. He takes a closer look at a real example – the discovery of a deep-sea anglerfish – and identifies the main structural features of species discovery processes in biology. In order to connect these results with Searle’s account of institutional reality, he provides an overview of the conceptual apparatus needed here. In bringing Searle’s account together with the structural features of species discoveries developed before, he shows to what extent declarative speech acts play a central role in species discovery processes in biology. (shrink)

It is often claimed that there can be no such thing as a logic of scientific discovery, but only a logic of verification. By 'logic of discovery' is usually meant a normative theory of discovery processes. The claim that such a normative theory is impossible is shown to be incorrect; and two examples are provided of domains where formal processes of varying efficacy for discovering lawfulness can be constructed and compared. The analysis shows how one can treat operationally (...) and formally phenomena that have usually been dismissed with fuzzy labels like 'intuition' and 'creativity'. (shrink)

Formalizing shared ethical standards is an activity of scientific societies designed to achieve a collective goal of promoting ethical conduct. A scientist who is faced with the choice of becoming a “whistleblower” by exposing misconduct does so in the context of these ethical standards. Examination of ethics policies of scientific societies which are members of the Council of Scientific Society Presidents (CSSP) shows a breadth of purpose and scope in these policies. Among the CSSP member societies, some (...) ethics policies chiefly present the ethical culture of the community in an educational context and do not have enforcement procedures. Other policies are more comprehensive and include standards for certification, procedures for addressing ethical issues, and established sanctions. Of the 36 member societies of CSSP that have developed a code or adopted a code of another professional society, 18 specifically identified a responsibility to expose ethical misconduct, demonstrating an acknowledgment of the possible critical role of the whistleblower in addressing ethical issues. Scientific societies may revise their ethics codes based upon experience gained in addressing cases of ethical misconduct. In most cases, the action of a whistleblower is the initial step in addressing an ethics violation; the whistleblower may either be in the position of an observer or a victim, such as in the case of someone who discovers that his or her own work has been plagiarized. The ethics committee of a scientific society is one of several possible outlets through which the whistleblower can voice a complaint or concern. Ethical violations can include falsification, fabrication, plagiarism and other authorship disputes, conflict of interest and other serious violations. Commonly, some of these violations may involve publication in the scientific literature. Thus addressing ethical issues may be intertwined with a scientific society’s role in the dissemination of new scientific results. For a journal published by a scientific society, the editor can refer at some point to the ethics committee of the society. Whereas, in the case of a journal published by a commercial publisher, the editor may be without direct support of the associated scientific community in handling the case. The association of a journal with a scientific society may thus direct a whistleblower towards addressing the issue within the scientific community rather than involving the press or talking to colleagues who may gossip. A formal procedure for handling ethics cases may also discourage false accusers. Another advantage of handling complaints through ethics committees is that decisions to contact home institutions or funding agencies can be made by the ethics committee and are not the responsibility of the whistleblower or the editor of the journal. The general assessment is that the establishment of ethics policies, especially policies covering publication in society journals, will promote a culture supportive of whistleblowers and discouraging to false accusers. (shrink)

Gottfried Wilhelm Leibniz is the self-proclaimed inventor of the binary system and is considered as such by most historians of mathematics and/or mathematicians. Really though, we owe the groundwork of today’s computing not to Leibniz but to the Englishman Thomas Harriot and the Spaniard Juan Caramuel de Lobkowitz, whom Leibniz plagiarized. This plagiarism has been identified on the basis of several facts: Caramuel’s work on the binary system is earlier than Leibniz’s, Leibniz was acquainted—both directly and indirectly—with Caramuel’s work and (...) Leibniz had a natural tendency to plagiarize scientific works. (shrink)

According to scientific realism, the aim of science is to discover the truth about both observable and unobservable aspects of the mind-independent, objective reality, which we inhabit. It has been objected by Putnam and others that such a metaphysically realist position presupposes a God’s Eye point of view, of which no coherent sense can be made. In this paper, I will argue for two claims. First, scientific realism does not require the adoption of a God’s Eye point of (...) view. Instead, scientific realism is a hypothesis about the relationship between scientific theory and reality which may be proposed from within our human perspective. Second, even if scientific realism did require a God’s Eye point of view, this would not necessarily be to the detriment of realism. For it is possible to develop an intelligible external perspective on human epistemic relations to our environing reality. (shrink)

Elwyn Richardson’s work at Oruaiti School from 1949 to 1962 has been almost exclusively interpreted as a unique experiment in art and craft education, partially as a result of impact of his book, In The Early World. The book is viewed as evidence of innovative departmental policies that allowed teachers wide latitude for experimentation, access to ample high-quality art materials and professional support. This interpretation of his work is, however, limiting as it obscures the scientific basis of Richardson’s approach. (...) The art and craft work at Oruaiti arose directly out of a scientific foundation that was shaped more by Richardson’s interest in environmental study than by the dominant ideas about child art. (shrink)

The way scientific discovery has been conceptualized has changed drastically in the last few decades: its relation to logic, inference, methods, and evolution has been deeply reloaded. The ‘philosophical matrix’ moulded by logical empiricism and analytical tradition has been challenged by the ‘friends of discovery’, who opened up the way to a rational investigation of discovery. This has produced not only new theories of discovery, but also new ways of practicing it in a rational and more systematic way. Ampliative (...) rules, methods, heuristic procedures and even a logic of discovery have been investigated, extracted, reconstructed and refined. The outcome is a ‘scientific discovery revolution’: not only a new way of looking at discovery, but also a construction of tools that can guide us to discover something new. This is a very important contribution of philosophy of science to science, as it puts the former in a position not only to interpret what scientists do, but also to provide and improve tools that they can employ in their activity. (shrink)

This paper examines the interplay between conceptual structure and the evolution of scientific concepts, arguing that concepts are fundamentally ‘forward-looking’ constructs. Drawing on empirical studies of similarity and categorization, I explicate the way in which the conceptual taxonomy highlights the ‘relevant respects’ for similarity judgments involved in categorization. I then propose that this taxonomy provides some of the cognitive underpinnings of the ongoing development of scientific concepts. I use the concept synapse to illustrate my proposal, showing how conceptual (...) taxonomy both facilitates and constrains the accommodation of newly discovered phenomena. I end by briefly considering the implications of the proposed approach for a normative evaluation of scientific concepts. (shrink)

I present a case study of scientific discovery, where building two functional and behavioral approximations of neurons, one physical and the other computational, led to conceptual and implementation breakthroughs in a neural engineering laboratory. Such building of external systems that mimic target phenomena, and the use of these external systems to generate novel concepts and control structures, is a standard strategy in the new engineering sciences. I develop a model of the cognitive mechanism that connects such built external systems (...) with internal models, and I examine how new discoveries, and consensus on discoveries, could arise from this external‐internal coupling and the building process. The model is based on the emerging framework of common coding, which proposes a shared representation in the brain between the execution, perception, and imagination of movement. (shrink)

Some scientific realists suggest that scientific communities have improved in their ability to discover alternative theoretical possibilities and that the problem of unconceived alternatives therefore poses a less significant threat to contemporary scientific communities than it did to their historical predecessors. I first argue that the most profound and fundamental historical transformations of the scientific enterprise have actually increased rather than decreased our vulnerability to the problem. I then argue that whether we are troubled by even (...) the prospect of increasing theoretical conservatism in science should depend on the position we occupy in the ongoing debate concerning scientific realism itself. (shrink)

One hundred and fifty years ago, a hopeful young researcher reported a recent discovery he had made. Working in the bowels of a medieval castle in the German city of Tübingen, he had isolated a then entirely new type of molecule. This was the birth of a field that would fundamentally change the course of biology, medicine, and beyond. His discovery: DNA. His name: Friedrich Miescher. In this article, the authors try to find answers to the question why—despite the fact (...) that virtually everyone nowadays knows DNA—hardly anyone remembers the man who discovered it. In the history of science, the discovery of DNA was a seminal moment. Why then did it not enter into public memory? Ground‐breaking discoveries can occur in a historical context that is not ready to appreciate them. But that's not all that decides who is remembered and who is forgotten. Scientific pioneers sometimes fail to publicize their findings in a way that ensures that they receive the attention they merit. As discussed here, their personalities and habits may cause discoveries to be “overwritten” by more recent researchers, resulting in distorted cultural memories no longer reflecting the initial event. (shrink)

If successful scientific inquiry is to be possible, there must be a world that is independent of how we believe it to be, and in which there are kinds and laws; and we must have the sensory apparatus to perceive particular things and events, and the capacity to represent them, to form generalized explanatory conjectures, and check how these conjectures stand up to further experience. Whether these preconditions are met is not a question the sciences can answer; it is (...) specifically philosophical. This is why the myriad forms of scientistic philosophy in vogue today (neurophilosophy, experimental philosophy, naturalized metaphysics, evangelical-atheist reductionism, etc), are all hollow at the core. Does this mean we must return to the old, a priori analytic model? No! What is needed instead is scientific philosophy in the sense Peirce articulated more than a century ago: philosophy motivated by a genuine desire to discover the truth, and relying not solely on reason but also on experience—only not the special, recherché experience required by the sciences, but close attention to aspects of everyday experience so familiar we hardly notice them. (shrink)

Insights into the intelligence throughout the natural and technical environment, in the fabric of our devices and dwellings, in our clothes, and under our skin. Is there a way to understand the materials that surround us not as passive objects, but as other intelligences interacting with our own? In Parallel Minds, expert in materials science and nanotechnology Laura Tripaldi delivers not only detailed insights into the properties and emergent behaviors of matter as revealed by state-of-the-art chemistry, synthetic biology, and nanotech, (...) but also a rich philosophical reflection that crosses the frontier between nature and culture, where the most cutting-edge scientific syntheses resonate with ancient myth. The result is a technomaterial bestiary full of unexpected encounters with “strange minds”—from cobwebs to kevlar and carbon fibre, from centaurs to amoebas to arachnids, from polycephalic slime to resonating plasmons, from viruses to golems. Parallel Minds reveals the intelligence at large throughout the natural and technical environment, in the fabric of our devices and dwellings, in our clothes, and even under our skin. Full of lateral ideas and unexpected images, Tripaldi’s book imbues the study and synthesis of materials with a new urgency. For not only do the materials that surround us participate actively in the construction of the world in which we live, but harnessing their ability to interact intelligently with their environment could be the key to the future of our species. (shrink)

THIS BOOK REVEALS an amazingly long-overlooked psychological reality that dawned on the author when he woke up from a dream and thought: “Suppose I had never woken up? Though others would know, how would I ever know it was over?” Based on cognitive science research and analysis, the author found that consciousness is not extinguished with death but, from a dying person’s perspective, only imperceptibly “paused.” -/- Given this, from your perspective, you’ll never lose your mind, self, and soul. And, (...) given dreams and near-death experiences, you may experience a timeless natural—i.e., scientifically supported—afterlife, which can be a heaven of utmost happiness. -/- Charles Darwin’s theory of natural selection was an earth-shattering revelation about how life evolved. This book is about an equally earth-shattering scientific theory about how a human life ends, including its possible impact on society and on you. (shrink)

Why does an object or phenomenon become the subject of scientific inquiry? Why do some of these objects remain provocative, while others fade from center stage? And why do objects sometimes return as the focus of research long after they were once abandoned? Addressing such questions, _Biographies of Scientific Objects_ is about how whole domains of phenomena—dreams, atoms, monsters, culture, society, mortality, centers of gravity, value, cytoplasmic particles, the self, tuberculosis—come into being and sometimes pass away as objects (...) of scientific study. With examples drawn from both the natural and social sciences, and ranging from the sixteenth to the twentieth centuries, this book explores the ways in which scientific objects are both real and historical. Whether discovered or invented, these objects of inquiry broaden and deepen in meaning—growing more "real"—as they become entangled in webs of cultural significance, material practices, and theoretical derivations. Thus their biographies will matter to anyone concerned with the formation of scientific knowledge. Contributors are Jed Z. Buchwald, Lorraine Daston, Rivka Feldhay, Jan Goldstein, Gerard Jorland, Doris Kauffman, Bruno Latour, Theodore M. Porter, Hans-Jörg Rheinberger, Marshall Sahlins, and Peter Wagner. (shrink)

This article considers the implications for film analysis of the presence or absence of a manual crank. More specifically, it looks at the 16 mm Time and Motion Study Projector as used in behavioral research in the 1960s and 1970s. The controversial concept of ‘interactional synchrony’, or the dance-like coordination of people in conversation, emerged from the use of this hand-turned projector. William S. Condon developed the concept along with the technique of microanalysis. Starting with the projector manufactured by Bell (...) & Howell, he made numerous improvements to facilitate observation—‘sweeping’ over segments of very short duration to discover the rhythmic synchrony of all filmed participants. It led him to a theory of ‘process’ in communication, and in the reception of speech in particular. People always ‘danced’ to the tune of their own voice, and their listeners ‘danced’ to the tune of the speaker—at intervals of one-sixth or one-eighth of a second. This also led Condon to an epistemology of discovery derived partly from philosophy but mostly from his machinery. The universe, he said, is a ‘continuum of order’ whose structures are preserved through translations of order: of thought into speech, speech into vibrations, vibrations into neurons, and back into behavior. The only exceptions are people with disabilities, like the autistics Condon studied from the 1970s onward. But the very distinction of normal and pathological was epiphenomenal to his scanning technique; it was rooted in material and formal qualities of film and of the projector whose crank he turned often. (shrink)

This book offers a superbly clear analysis of the standard arguments for and against scientific realism. In surveying claims on both sides of the debate, Kukla organizes them in ways that expose unnoticed connections. He identifies broad patterns of error, reconciles seemingly incompatible positions, and discovers unoccupied positions with the potential to influence further debate. Kukla's overall assessment is that neither the realists nor the antirealists may claim a decisive victory.

Discussions over whether these natural kinds exist, what is the nature of their existence, and whether natural kinds are themselves natural kinds aim to not only characterize the kinds of things that exist in the world, but also what can knowledge of these categories provide. Although philosophically critical, much of the past discussions of natural kinds have often answered these questions in a way that is unresponsive to, or has actively avoided, discussions of the empirical use of natural kinds and (...) what I dub “activities of natural kinding” and “natural kinding practices”. The natural kinds of a particular discipline are those entities, events, mechanisms, processes, relationships, and concepts that delimit investigation within it—but we might reasonably ask: How are these natural kinds discovered?, How are they made?, Are they revisable?, and Where do they come from? A turn to natural kinding practices reveals a new set of questions open for investigation: How do natural kinds explain through practice?, What are natural kinding practices and classifications and why should we care?, What is the nature of natural kinds viewed as a set of activities?, and How do practice approaches to natural kinds shape and reconfigure scientific disciplines? Natural kinds have traditionally been discussed in terms of how they classify the contents of the world. The metaphysical project has been one which identifies essences, laws, sameness relations, fundamental properties, and clusters of family resemblances and how these map out the ontological space of the world. But actually how this is done has been less important in the discussion than the resultant categories that are produced. I aim to rectify these omissions and suggest a new metaphysical project investigating kinds in practice. (shrink)

Philosophers of science are divided over the interpretations of scientific normativity. Larry Laudan defends a sort of goal-directed rules for scientific methodology. In contrast, Gerard Doppelt thinks methodological rules are a mixed batch of rules in that some are goal-oriented hypothetical rules and others are goal-independent categorical rules. David Resnik thinks that the debate between them is at a standstill now. He further thinks there are certain rules, such as the rule of consistency which is goal independent. However, (...) he proposes a holistic understanding of the scientific methodology. Taking a thread from Resnik, the present paper also advocates a holistic understanding of the scientific methodology. Given that many scientific practices deal with systems, the focus will be given to the systems by assuming each as a constellation of methodological norms. By taking each system as a set of mutually supportive methodological rules whose instrumental values underwrite the coherence relation among them, the paper aims to provide what could be a viable holistic epistemological account that can explain scientific normativity at work in a scientific system. The paper will lay down specific holistic criteria for understanding the scientific methodology. They will be used to show how a holistic account could satisfactorily account for the success of the Compact Muon Solenoid (CMS) experiment in discovering the Higgs boson and how the holistic account can account for the instrumental error behind the apparent faster-than-light neutrino anomaly of the Oscillation Project with Emulsion-t Racking Apparatus (OPERA) experiments respectively. (shrink)

When you gaze out at the night sky with its awe-inspiring display of stars and galaxies, do you ever ask yourself if it could be possible that you are actually looking into a mirror? What if we inhabit a universe that perfectly fits our needs here on Earth -- a truly human universe? That's the bold thesis author Deepak Chopra and physicist Menas Kafatos set out to prove: quite literally, "You are the universe." The startling truth is that the everyday (...) world of physical objects "out there" disguises a hidden dimension. By turning our investigation "in here" to the world of consciousness, the real reality emerges. You Are the Universe guides the reader into a realm in which each of us has the power to transform our personal existence, while at the same time fashioning a new story about how time, space, matter, and energy came into existence. Looking to overturn the traditional model of scientific reality, Chopra and Kafatos hold that each of us is a cocreator of reality and we can uncover the hidden dimensions where consciousness is a field of infinite possibilities. This seemingly impossible proposition follows from the cutting-edge modern thinking of the quantum universe and the great mysteries that must be unriddled before human beings actually know who they are. These include but are not limited to questions such as What came before the big bang? Why does the universe fit together so perfectly? Where did time come from? And do we live in a conscious universe? These mysteries are part and parcel of everyone's life. "All of us live in a participatory universe," the authors write. "Once you decide that you want to participate fully with mind, body, and soul, the paradigm shift becomes personal. The reality you inhabit will be yours to either embrace or change. (shrink)

The purpose of the two studies reported here was to develop an integrated model of the scientific reasoning process. Subjects were placed in a simulated scientific discovery context by first teaching them how to use an electronic device and then asking them to discover how a hitherto unencountered function worked. To do this task, subjects had to formulate hypotheses based on their prior knowledge, conduct experiments, and evaluate the results of their experiments. In the first study, using 20 (...) adult subjects, we identified two main strategies that subjects used to generate new hypotheses. One strategy was to search memory and the other was to generalize from the results of previous experiments. We described the former group as searching an hypothesis space, and the latter as searching an experiment space. In a second study, with 10 adults, we investigated how subjects search the hypothesis space by instructing them to state all the hypotheses that they could think of prior to conducting any experiments. Following this phase, subjects were then allowed to conduct experiments. Subjects who could not think of the correct rule in the hypothesis generation phase discovered the correct rule only by generalizing from the results of experiments in the experimental phase.Both studies provide support for the view that scientific reasoning can be characterized as search in two problem spaces. By extending Simon and Lea's (1974) Generalized Rule Inducer, we present a general model of Scientific Discovery as Dual Search (SDDS) that shows how search in two problem spaces (an hypothesis space and an experiment space) shapes hypothesis generation, experimental design, and the evaluation of hypotheses. The model also shows how these processes interact with each other. Finally, we interpret earlier findings about the psychology of scientific reasoning in terms of the SDDS model. (shrink)

The basic task of the essay is to exhibit science as a rational enterprise. I argue that in order to do this we need to change quite fundamentally our whole conception of science. Today it is rather generally taken for granted that a precondition for science to be rational is that in science we do not make substantial assumptions about the world, or about the phenomena we are investigating, which are held permanently immune from empirical appraisal. According to this standard (...) view, science is rational precisely because science does not make a priori metaphysical presuppositions about the world forever preserved from possible empirical refutation. It is of course accepted that an individual scientist, developing a new theory, may well be influenced by his own metaphysical presuppositions. In addition, it is acknowledged that a successful scientific theory, within the context of a particular research program, may be protected for a while from refutation, thus acquiring a kind of temporary metaphysical status, as long as the program continues to be empirically progressive. All such views unite, however, in maintaining that science cannot make permanent metaphysical presuppositions, held permanently immune from objective empirical evaluation. According to this standard view, the rationality of science arises, not from the way in which new theories are discovered, but rather from the way in which already formulated theories are appraised in the light of empirical considerations. And the fundamental problem of the rationality of science—the Humean problem of induction— concerns precisely the crucial issue of the rationality of accepting theories in the light of evidence. In this essay I argue that this widely accepted standard conception of science must be completely rejected if we are to see science as a rational enterprise. In order to assess the rationality of accepting a theory in the light of evidence it is essential to consider the ultimate aims of science. This is because adopting different aims for science will lead us, quite rationally, to accept different theories in the light of evidence. I argue that a basic aim of science is to explain. At the outset science simply presupposes, in a completely a priori fashion, that explanations can be found, that the world is ultimately intelligible or simple. In other words, science simply presupposes in an a priori way the metaphysical thesis that the world is intelligible, and then seeks to convert this presupposed metaphysical theory into a testable scientific theory. Scientific theories are only accepted insofar as they promise to help us realize this fundamental aim. At once a crucial problem arises. If scientific theories are only accepted insofar as they promise to lead us towards articulating a presupposed metaphysical theory, it is clearly essential that we can choose rationally, in an a priori way, between all the very different possible metaphysical theories that can be thought up, all the very different ways in which the universe might ultimately be intelligible. For holding different aims, accepting different metaphysical theories conceived of as blueprints for future scientific theories will, quite rationally, lead us to accept different scientific theories. Thus it is only if we can choose rationally between conflicting metaphysical blueprints for future scientific theories that we will be in a position to appraise rationally the acceptability of our present day scientific theories. We thus face the crucial problem: How can we choose rationally between conflicting possible aims for science, conflicting metaphysical blueprints for future scientific theories ? It is only if we can solve this fundamental problem concerning the aims of science that we can be in a position to appraise rationally the acceptability of existing scientific theories. There is a further point here. If we could choose rationally between rival aims, rival metaphysical blueprints for future scientific theories, then we would in effect have a rational method for the discovery of new scientific theories! Thus we reach the result: there is only a rational method for the appraisal of existing scientific theories if there is a rational method of discovery. I shall argue that the aim-oriented theory of scientific inquiry to be advocated here succeeds in exhibiting science as a rational enterprise in that it succeeds in providing a rational procedure for choosing between rival metaphysical blueprints: it thus provides a rational, if fallible, method of discovery, and a rational method for the appraisal of existing scientific theories—thus resolving the Humean problem. In Part I of the essay I argue that the orthodox conception of science fails to exhibit science as a rational enterprise because it fails to solve the Humean problem of induction. The presuppositional view advocated here does however succeed in resolving the Humean problem. In Part II of the essay I spell out the new aim-oriented theory of scientific method that becomes inevitable once we accept the basic presuppositional viewpoint. I argue that this new aim oriented conception of scientific method is essentially a rational method of scientific discovery, and that the theory has important implications for scientific practice. (shrink)

Walter Kaufmann completed this, the third and final volume of his landmark trilogy, shortly before his death in 1980. The trilogy is the crowning achievement of a lifetime of study, writing, and teaching. This final volume contains Kaufmann's tribute to Sigmund Freud, the man he thought had done as much as anyone to discover and illuminate the human mind. Kaufmann's own analytical brilliance seems a fitting reflection of Freud's, and his acute commentary affords fitting company to Freud's own thought. Kaufmann (...) traces the intellectual tradition that culminated in Freud's blending of analytic scientific thinking with humanistic insight to create "a poetic science of the mind." He argues that despite Freud's great achievement and celebrity, his work and person have often been misunderstood and unfairly maligned, the victim of poor translations and hostile critics. Kaufmann dispels some of the myths that have surrounded Freud and damaged his reputation. He takes pains to show how undogmatic, how open to discussion, and how modest Freud actually was. Kaufmann endeavors to defend Freud against the attacks of his two most prominent apostate disciples, Alfred Adler and Carl Gustav Jung. Adler is revealed as having been jealous, hostile, and an ingrate, a muddled thinker and unskilled writer, and remarkably lacking in self-understanding. Jung emerges in Kaufmann's depiction as an unattractive, petty, and envious human being, an anti-Semite, an obscure and obscurantist thinker, and, like Adler, lacking insight into himself. Freud, on the contrary, is argued to have displayed great nobility and great insight into himself and his wayward disciples in the course of their famous fallings-out. (shrink)