Scientific Discovery

What constitutes a scientific discovery? What role do discoveries play in science, its dynamics and social practices? Must every discovery be attributed to an individual discoverer (or a small number of discoverers)? The paper explores these questions by first critically examining extant philosophical explications of scientific discovery—the models of scientific discovery, propounded by Kuhn, McArthur, Hudson, and Schindler. As a simple, natural and powerful alternative, we proffer the “change-driver model”: in a nutshell, it takes discoveries to be cognitive scientific results (...) that have epistemically advanced science. The model overcomes the shortcomings of its precursors, whilst preserving their insights. We demonstrate its intensional and extensional superiority, especially with respect to the link between scientific discoveries and the dynamics of science, as well as the award system of science. Both as an illustration, and as an application to a recent scientific and political controversy, we apply the considered models of discovery to one of the most momentous discoveries of science: the expansion of the universe. We oppose the 2018 proposal of the International Astronomers’ Union as too simplistic vis-`a-vis the historical complexity of the episode. The change- driver model yields a more nuanced and circumspect verdict: (i) The redshift-distance relation shouldn’t be named the “Hubble-Lemaître Law”, but “Slipher-Lundmark-Hubble-Humason Law”; (ii) Its interpretation in terms of an expanding universe, however, Lemaître ought to be given credit for; but (iii) The establishment of the expansion of the universe, as an evidentially sufficiently warranted result, is a communal achievement, emerging in the 1950s or 1960s. (shrink)

Susan Haack criticises the US courts' use of Karl Popper's epistemology in discriminating acceptable scientific testimony. She claims that acceptable testimony should be reliable and that Popper's epistemology is useless in discriminating reliability. She says that Popper's views have been found acceptable only because they have been misunderstood and she indicates an alternative epistemology which she says can discriminate reliable theories. However, her account of Popper's views is a gross and gratuitous misrepresentation. Her alternative epistemology cannot do what she claims (...) for it. The courts should not be concerned with reliability and, insofar as they use the term 'reliability,' it should be construed in a procedural rather than a substantive sense. Since Popper's epistemology gives something like a characterisation of science at its best, the courts should continue to invoke Popper's theories in their discrimination of acceptable testimony. (shrink)

It is usually accepted that deductions are non-informative and monotonic, inductions are informative and nonmonotonic, abductions create hypotheses but are epistemically irrelevant, and both deductions and inductions can’t provide new insights. In this article, I attempt to provide a more cohesive view of the subject with the following hypotheses: (1) the paradigmatic examples of deductions, such as modus ponens and hypothetical syllogism, are not inferential forms, but coherence requirements for inferences; (2) since any reasoner aims to be coherent, any inference (...) must be deductive; (3) a coherent inference is an intuitive process where the premises should be taken as sufficient evidence for the conclusion, which on its turn should be viewed as necessary evidence for the premises in some modal range; (4) inductions, properly understood, are abductions, but there are no abductions beyond the fact that in any inference the conclusion should be regarded as necessary evidence for the premises; (5) monotonicity is not only compatible with the retraction of past inferences given new information, but it is a requirement for it; (6) this explanation of inferences holds true for discovery processes, predictions and trivial inferences. (shrink)

Three new versions of Wason’s 2-4-6 rule discovery task incorporating error rates or feedback of uncertainty reduction, inspired by the error-statistical account in philosophy of science, were employed. In experiments 1 and 2, participants were instructed that some experimenter feedback would be erroneous (control was original 2-4-6 without error). The results showed that performance was impaired when there was probabilistic error. In experiment 3, participants were given uncertainty reduction feedback as they generated different number triples and the negative effects of (...) probabilistic error were not observed. These findings are informative not only about rule discovery tasks in general but also about contexts of inference under uncertainty. (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 or epistemic norms. Still, mechanistic philosophers on both sides agree that there is no sharp distinction between the processes of discovery and explanation. 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 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)

I defend a novel account of scientific progress centred around justification. Science progresses, on this account, where there is a change in justification. I consider three options for explicating this notion of change in justification. This account of scientific progress dispels with a condition for scientific progress that requires accumulation of truth or truthlikeness, and it emphasises the social nature of scientific justification.

Geographic Information Science (GIS) is an interdisciplinary science aiming to detect and visually represent patterns in spatial data. GIS is used by businesses to determine where to open new stores and by conservation biologists to identify field study locations with relatively little anthropogenic influence. Products of GIS include topographic and thematic maps of the Earth’s surface, climate maps, and spatially referenced demographic graphs and charts. In addition to its social, political, and economic importance, GIS is of intrinsic philosophical interest due (...) to its methodological richness and because it is an instructive analogue to other sciences. This chapter works towards a philosophy of GIS and cartography, or PGISC. In particular, it examines practices of classifying geographic space, objects, and relations. By focusing on the use of natural kinds in data modeling and map generalization practices, I show how the making and using of kinds is contextual, fallible, plural, and purposive. (shrink)

Supersymmetry (SUSY) has long been considered an exceptionally promising theory. A central role for the promise has been played by naturalness arguments. Yet, given the absence of experimental findings it is questionable whether the promise will ever be fulfilled. Here, I provide an analysis of the promises associated with SUSY, employing a concept of pursuitworthiness. A research program like SUSY is pursuitworthy if (1) it has the plausible potential to provide high epistemic gain and (2) that gain can be achieved (...) with manageable research efforts. Naturalness arguments have been employed to support both conditions (1) and (2). First, SUSY has been motivated by way of analogy: the proposed symmetry between fermions and bosons is supposed to 'protect' the small Higgs mass from large quantum corrections just as the electron mass is protected through the chiral symmetry. Thus, SUSY held the promise of solving a major problem of the Standard Model of particle physics. Second, naturalness arguments have been employed to indicate that such gain is achievable at relatively low cost: SUSY discoveries seemed to be well in reach of upcoming high-energy experiments. While the first part of the naturalness argument may have the right form to facilitate considerations of pursuitworthiness, the second part of the argument has been problematically overstated. (shrink)

Scientists imagine constantly. They do this when generating research problems, designing experiments, interpreting data, troubleshooting, drafting papers and presentations, and giving feedback. But when and how do scientists learn how to use imagination? Across 6 years of ethnographic research, it has been found that advanced career scientists feel comfortable using and discussing imagination, while graduate and undergraduate students of science often do not. In addition, members of marginalized and vulnerable groups tend to express negative views about the strength of their (...) imaginations and the general usefulness of imagination in science. After introducing these findings and discussing the typical relationship between a scientist and their imagination across a career, we argue that reducing the number or power of active imaginations in science is epistemically counterproductive. We suggest several ways to bring imagination back into science in a more inclusive way, especially through courses on imagination for scientists, good role models, and exemplar-based learning. (shrink)

Explanation is a foundational goal in the exact sciences. Besides the contemporary considerations on ‘description’, ‘classification’, and ‘prediction’, we often see these terms in thriving applications of artificial intelligence (AI) in chemistry hypothesis generation. Going beyond describing ‘things in the world’, these applications can make accurate numerical property calculations from theoretical or topological descriptors. This association makes an interesting case for a logic of discovery in chemistry: are these induction-led ventures showing a shift in how chemists can problematize research questions? (...) In this article, I present a fresh perspective on the current context of discovery in chemistry. I argue how data-driven statistical predictions in chemistry can be explained as a quasi-logical process for generating chemical theories, beyond the classic examples of organic and theoretical chemistry. Through my position on formal models of scientific explanation, I demonstrate how the dawn of AI can provide novel insights into the explanatory power of scientific endeavors. (shrink)

It has been suggested that particle physics has reached the "dawn of the post-naturalness era." I provide an explanation of the current shift in particle physicists' attitude towards naturalness. I argue that the naturalness principle was perceived to be supported by the theories it has inspired. The potential coherence between major beyond the Standard Model (BSM) proposals and the naturalness principle led to an increasing degree of credibility of the principle among particle physicists. The absence of new physics at the (...) Large Hadron Collider (LHC) has undermined the potential coherence and has led to the principle's loss of significance. (shrink)

The type-level abstraction is a formal way to represent molecular structures in biological practice. Graphical representations of molecular structures of biological objects are also used to identify functional processes of things. This paper will reveal that category theory is a formal mathematical language not only to visualize molecular structures of biological objects as type-level abstraction formally but also to understand how to infer biological functions from the molecular structures of biological objects. Category theory is a toolkit to understand biological knowledge (...) at the type-level formally, not individual token-level, as well as typical heuristic strategies in molecular biology. (shrink)

In this paper I discuss Mark Steiner’s view of the contribution of mathematics to physics and take up some of the questions it raises. In particular, I take up the question of discovery and explore two aspects of this question – a metaphysical aspect and a related epistemic aspect. The metaphysical aspect concerns the formal structure of the physical world. Does the physical world have mathematical or formal features or constituents, and what is the nature of these constituents? The related (...) epistemic question concerns humans’ cognitive ability to reach the formal structure of the physical world. Among other things, I explore the interaction of mathematical and non-mathematical cognition in physical discovery. (shrink)

Can an ugly experiment be a good experiment? Philosophers have identified many beautiful experiments and explored ways in which their beauty might be connected to their epistemic value. In contrast, the present chapter seeks out (and celebrates) ugly experiments. Among the ugliest are those being designed by AI algorithms. Interestingly, in the contexts where such experiments tend to be deployed, low aesthetic value correlates with high epistemic value. In other words, ugly experiments can be good. Given this, we should conclude (...) that beauty is not generally necessary or sufficient for epistemic value, and increasing beauty will not generally tend to increase epistemic value. (shrink)

The ongoing COVID-19 pandemic has brought science to the fore of public discourse and, considering the complexity of the issues involved, with it also the challenge of effective and informative science communication. This is a particularly contentious topic, in that it is both highly emotional in and of itself; sits at the nexus of the decision-making process regarding the handling of the pandemic, which has effected lockdowns, social behaviour measures, business closures, and others; and concerns the recording and reporting of (...) disease mortality. To clarify a point that has caused much controversy and anger in the public debate, the first part of the present article discusses the very fundamentals underlying the issue of causative attribution with regards to mortality, lays out the foundations of the statistical means of mortality estimation, and concretizes these by analysing the recording and reporting practices adopted in England and their widespread misrepresentations. The second part of the article is empirical in nature. I present data and an analysis of how COVID-19 mortality has been reported in the mainstream media in the UK and the USA, including a comparative analysis both across the two countries as well as across different media outlets. The findings clearly demonstrate a uniform and worrying lack of understanding of the relevant technical subject matter by the media in both countries. Of particular interest is the finding that with a remarkable regularity (????>0.998), the greater the number of articles a media outlet has published on COVID-19 mortality, the greater the proportion of its articles misrepresented the disease mortality figures. (shrink)

Between the 1930s and the mid 1970s, it was commonly believed that in 1880 Karl Marx had proposed to dedicate to Charles Darwin a volume or translation of Capital but that Darwin had refused. The detail was often interpreted by scholars as having larger significance for the question of the relationship between Darwinian evolutionary biology and Marxist political economy. In 1973–4, two scholars working independently—Lewis Feuer, professor of sociology at Toronto, and Margaret Fay, a graduate student at Berkeley—determined simultaneously that (...) the traditional story of the proposed dedication was untrue, being based on a long-standing misinterpretation of the relevant correspondence. Between the two, and among several other scholars who became their respective allies, there developed a contest of authority and priority over the discovery. From 1975 to 1982, the controversy generated a considerable volume of spilled ink in both scholarly and popular publications. Drawing on previously unexamined archival resources, this article revisits the ‘case’ of the so-called ‘Darwin–Marx correspondence’ as an instance of the phenomenon of ‘multiple discovery’. A familiar occurrence in the natural sciences, multiple discovery is rarer in the humanities and social sciences. The present case of a priority dispute in the history of ideas followed patterns familiar from such disputes in the natural sciences, while also diverging from them in ways that shed light on the significance of disciplinary norms and research infrastructures. (shrink)

This paper investigates how intuitions about scientific discovery using artificial intelligence can be used to improve our understanding of scientific discovery more generally. Traditional accounts of discovery have been agent-centred: they place emphasis on identifying a specific agent who is responsible for conducting all, or at least the important part, of a discovery process. We argue that these accounts experience difficulties capturing scientific discovery involving AI and that similar issues arise for human discovery. We propose an alternative, collective-centred view as (...) superior for understanding discovery, with and without AI. This view maintains that discovery is performed by a collective of agents and entities, each making contributions that differ in significance and character, and that attributing credit for discovery depends on various finer-grained properties of the contributions made. Detailing its conceptual resources, we argue that this view is considerably more compelling than its agent-centred alternative. Considering and responding to several theoretical and practical challenges, we point to concrete avenues for further developing the view we propose. (shrink)

Criticism is a staple of the scientific enterprise and of the social epistemology of science. Philosophical discussions of criticism have traditionally focused on its roles in relation to objectivity, confirmation, and theory choice. However, attention to criticism and to criticizability should also inform our thinking about scientific pursuits: the allocation of resources with the aim of developing scientific tools and ideas. In this paper, we offer an account of scientific pursuitworthiness which takes criticizability as its starting point. We call this (...) the apokritic model of pursuit. Its core ideas are that pursuits are practices governed by norms for asking and answering questions, and that criticism arises from the breach of these norms. We illustrate and advertise our approach using examples from institutional grant review, neuroscience, and sociology. We show that the apokritic model can unify several indices of criticizability, that it can account for the importance of criticizing pursuits in scientific practice, and that it can offer ameliorative advice to erstwhile pursuers. (shrink)

"La struttura delle rivoluzioni scientifiche", dopo più di mezzo secolo dalla sua pubblicazione, è ancora in grado di offrire un contributo alla pratica filosofica? In questo articolo, attraverso i concetti peirceani di Abito, Abduzione e Verità, si propone una lettura pragmaticista del testo di Kuhn che intende rilanciare un fecondo confronto, ancora poco considerato, tra i due filosofi.

In this Element, we’ll explore the nature of both imagination and creative thinking in an effort to understand the relation between them and also to understand their role in the vast array of activities in which they are typically implicated, from art, music, and literature to technology, medicine, and science. Focusing on the contemporary philosophical literature, we will take up several interrelated questions: What is imagination, and how does it fit into the cognitive architecture of the mind? What is creativity? (...) Is imagination required for creativity? Is creativity required for imagination? Is a person simply born either imaginative or not (and likewise, either creative or not), or are imagination and creativity skills that can be cultivated? And finally, are imagination and creativity uniquely human capacities, or can they be had by nonbiological entities such as AI systems? (shrink)

This paper addresses the role of analogical reasoning in archaeoastronomy - the discipline which studies the connections between the ancient monuments and the heavens. Archaeoastronomy is a highly interdisciplinary science, placed at the border between the humanities – especially archaeology – and the scientific approach to cultural heritage. As a consequence, its scientific foundations are a delicate matter. We plan to investigate here the question of what constitutes the evidence for analogical inferences in archaeoastronomy and to what extent one can (...) achieve confirmation of archaeoastronomical hypotheses by means of such analogies. Our claim will be that, when deployed in accordance with the methodology articulated in this paper, analogies can be a highly effective epistemic tool for generating and supporting hypotheses about the relation of archaeological sites with astronomical events. (shrink)

Tomis Kapitan’s work on Peirce’s conception of abduction was instrumental for our coming to see how Peircean abduction both relates to and is importantly different from inference to the best explanation (IBE). However, he ultimately concluded that Peirce’s conception of abduction was a muddle. Despite the deeply problematic nature of Peirce’s theory of abduction in these respects, Kapitan’s work on Peircean abduction offers insight into the nature of abductive inquiry that is importantly relevant to the task of making sense of (...) explanatory inquiry in the sciences in general. The view developed here stems from his work and involves disambiguating three forms of inference involved in Peircean abduction in terms of Reichenbach’s and Laudan’s context models of inquiry. Importantly, this includes understanding that abduction involves the context of pursuit. (shrink)

The history of developmental biology is interwoven with debates as to whether mechanistic explanations of development are possible or whether alternative explanatory principles or even vital forces need to be assumed. In particular, the demonstrated ability of embryonic cells to tune their developmental fate precisely to their relative position and the overall size of the embryo was once thought to be inexplicable in mechanistic terms. Taking a causal perspective, this Element examines to what extent and how developmental biology, having turned (...) molecular about four decades ago, has been able to meet the vitalist challenge. It focuses not only on the nature of explanations but also on the usefulness of causal knowledge – including the knowledge of classical experimental embryology – for further scientific discovery. It also shows how this causal perspective allows us to understand the nature and significance of some key concepts, including organizer, signal and morphogen. This title is also available as Open Access on Cambridge Core. (shrink)

I challenge Gareth Eaton’s recent claim that Theodore Richards should be counted among the discoverers of isotopes. In evaluating Eaton’s claim, I draw on two influential theories of scientific discovery, one developed by Thomas Kuhn, and one developed by Augustine Brannigan. I argue that though Richards’ experimental work contributed to the discovery, his work does not warrant attributing the discovery to him. Richards’ reluctance to acknowledge isotopes is well documented. Further, the fact that he made no claim to having made (...) the discovery also undermines Eaton’s argument. (shrink)

In 1981, David Hubel and Torsten Wiesel received the Nobel Prize for their research on cortical columns—vertical bands of neurons with similar functional properties. This success led to the view that “cortical column” refers to the basic building block of the mammalian neocortex. Since the 1990s, however, critics questioned this building block picture of “cortical column” and debated whether this concept is useless and should be replaced with successor concepts. This paper inquires which experimental results after 1981 challenged the building (...) block picture and whether these challenges warrant the elimination “cortical column” from neuroscientific discourse. I argue that the proliferation of experimental techniques led to a patchwork of locally adapted uses of the column concept. Each use refers to a different kind of cortical structure, rather than a neocortical building block. Once we acknowledge this diverse-kinds picture of “cortical column”, the elimination of column concept becomes unnecessary. Rather, I suggest that “cortical column” has reached conceptual retirement: although it cannot be used to identify a neocortical building block, column research is still useful as a guide and cautionary tale for ongoing research. At the same time, neuroscientists should search for alternative concepts when studying the functional architecture of the neocortex. keywords: Cortical column, conceptual development, history of neuroscience, patchwork, eliminativism, conceptual retirement. (shrink)

Scientific progress depends crucially on scientific discoveries. Yet the topic of scientific discoveries has not been central to debate in the philosophy of science. This book aims to remedy this shortcoming. Based on a broad reading of the term “science” (similar to the German term “Wissenschaft”), the book convenes experts from different disciplines who reflect upon several intertwined questions connected to the topic of making scientific discoveries. -/- Among these questions are the following: What are the preconditions for making scientific (...) discoveries? What is it that we (have to) do when we make discoveries in science? What are the objects of scientific discoveries, how do we name them, and how do scientific names function? Do discoveries in, say, physics and biology, share an underlying structure, or do they differ from each other in crucial ways? Are other fields such as theology and environmental studies loci of scientific discovery? What is the purpose of making scientific discoveries? Explaining nature or reality? Increasing scientific knowledge? Finding new truths? If so, how can we account for instructive blunders and serendipities in science? -/- In the light of the above, the following is an encompassing question of the book: What does it mean to make a discovery in science, and how can scientific discoveries be distinguished from non-scientific discoveries? (shrink)

Jan G. Michel argues that we need a philosophy of scientific discovery. Before turning to the question of what such a philosophy might look like, he addresses two questions: Don’t we have a philosophy of scientific discovery yet? And do we need one at all? To answer the first question, he takes a closer look at history and finds that we have not had a systematic philosophy of scientific discovery worthy of the name for over 150 years. To answer the (...) second question, Michel puts forward three arguments that show the importance of a philosophy of scientific discovery. Briefly, he arrives at the following answers: No, we don’t yet have a philosophy of scientific discovery, and yes, we definitely need one. To remedy this shortcoming, Michel analyzes the concept of discovery, leading him to the insight that scientific discoveries have an underlying structure with certain structural features. Some of these features may be important but not indispensable to scientific discovery processes; these include eureka moments, serendipities, joint discoveries, special science funding, and others. In addition, Michel identifies three indispensable structural features which he examines in detail and which he places in a picture with a certain dynamics according to which the process of making scientific discoveries can be seen as a path, leading us from finding and acceptance to knowledge. (shrink)

Within science fiction the topic of ‘first contact’ is a popular theme. How will an encounter with aliens unfold? Will we succeed in communicating with them? Although such questions are present in the background of many science fiction novels, they are not always explicitly dealt with and even if so, often in a poor way. In this article, I will introduce a typology of five dominant types of solutions to the problem of first contact in science fiction works. The first (...) four solutions are the more dominant, but also the least interesting ones. There is a fifth category that addresses the question of first contact in a more interesting way, exemplified by the work of Stanisław Lem. This fifth option defines itself as a critique of the four previous categories, or of their shared assumption of what Lem (1967) has called ‘the myth of cognitive universality’. Lem is sceptical of the common optimism that first contact will always be successful. In books such as Solaris (1961), His Master’s Voice (1967) and Fiasco (1986), humanity makes first contact with an alien phenomenon, but fails to comprehend the phenomenon. Fundamentally, it will be argued that Lem’s work shows that in such an encounter we will typically not only lack the right answers to our questions, but that we also often lack the correct questions: we simply do not have the right categories or instruments to even recognize, let alone meaningfully interrogate, the alien phenomenon. The article ends with an exploration of the implications of Lem’s pessimism and whether it is the most plausible option for first contact. Moreover, the article will draw some lessons for philosophy of science, by exploring the parallel with the confrontation of novel or deviant phenomena in science. Lem’s work is helpful here because it succeeds in articulating what has not always been appreciated in the philosophy of science, namely that the right questions by which to interrogate scientific phenomena are not given, but that their articulation always requires work. (shrink)

When two or more (groups of) researchers independently investigating the same domain arrive at the same result, a multiple discovery occurs. The pervasiveness of multiple discoveries in science suggests the intuition that they are in some sense inevitable—that one should view them as results that force themselves upon us, so to speak. We argue that, despite the intuitive force of such an “inevitabilist insight,” one should reject it. More specifically, we distinguish two facets of the insight and argue that: (a) (...) the profusion of multiple discoveries in scientific practice does not support the inevitabilist side of the inevitability/contingency of science controversy; and (b) the crucial role of background knowledge in scientific inquiry complicates the attempt to interpret the pervasiveness of multiple discoveries in realist terms. (shrink)

The distinction between context of discovery and context of justification points out to the difference between the generation a new idea or hyphotesis and the testing of it. Although the distinction is attributed to Hans Reichenbach and Karl Popper, Larry Laudan argues that the history of distinction is dates back to the debates of scientific in the seventeenth century. While in the seventeenth and eighteenth centuries there was no need to distinguish between discovery and justification, in the twentieth century discovery (...) and justification were considered two separate processes. In this paper, it will be argued that the distinction between the context of discovery and justification is untenable given that the history of science is a part of scientific research, as expressed by philosophers such as Kuhn and Feyerabend. (shrink)

This article is concerned with one of the notable but forgotten research strands that developed out of French nineteenth-century positivism, a strand that turned attention to the study of scientific discovery and was actively pursued by French epistemologists around the turn of the nineteenth century. I first sketch the context in which this research program emerged. I show that the program was a natural offshoot of French neopositivism; the latter was a current of twentieth-century thought that, even if implicitly, challenged (...) the positivism of first-generation positivists such as Comte. I then survey what French epistemologists—including Ernest Naville, Élie Rabier, Pierre Duhem, Édouard Le Roy, Abel Rey, André Lalande, Théodule-Armand Ribot, Edmond Goblot, and Jacques Picard, among others—had to say about the logic, psychology, and sociology of discovery. My story demonstrates the inaccuracy of existing historical accounts of the philosophical study of scientific discovery. (shrink)

The focus of this article is a question that has been neglected in debates about digitalization: Could machines replace human scientists? To provide an intelligible answer to it, we need to answer a further question: What is it that makes (or constitutes) a scientist? I offer an answer to this question by proposing a new demarcation criterion for science which I call “the discoverability criterion”. I proceed as follows: (1) I explain why the target question of this article is important, (...) and (2) show that it leads to a variant of the demarcation problem of science. (3) By arguing that it is probably an essential feature of science that we can make scientific discoveries, I suggest a novel way of dealing with this problem by proposing a new demarcation criterion. Before introducing it, (4) I analyze an exemplary case of a real scientific discovery, and (5) argue that scientific discovery processes have a general underlying structure. (6) I introduce my discoverability criterion for science and present my master argument that helps us understand which criteria have to be fulfilled in order to decide whether machines can replace human scientists or not. (7) I conclude by answering the article’s target question and bringing forward a take-home message. (shrink)

[Comment] I am sympathetic to Avner de Shalit’s position that a political philosophy should incorporate public values, but I see their role differently. Philosophers of science standardly distinguish between values being introduced in the context of discovery (inputs into the investigation or arguments) and in the context of justification (acceptance or rejection of substantive claims in light of the arguments or investigation). I argue that de Shalit is wrong to put the public values in the context of discovery; with respect (...) to normative theories (such as political theories), the values should be introduced in the context of justification. [Open access]. (shrink)

This article reconstructs the development of Kurt Walter Zeidler's argument for a reformulation of Kant's transcendental dialectic as a theory of the foundation of transcendental logic. It therefore examines his doctoral dissertation "Logik des Erkenntnisprozesses. Dedukton - Induktion - Abduktion" (1979), where he discusses Norwood Russell Hansons 'logic of discovery' and finds an analogy between Charls S. Peirce's definiton of 'abduction' and Hegel's defintion of 'analogy', as well as his early papers, collected in "Grundlegungen. Zur Theorie der Vernunft und Letztbegründung" (...) (2015), and his habilitation dissertation "Vernunft und Erfahrung. Untersuchungen zum Erkenntnisproblem in Philosophie und Wissenschaftstheorie" (1986), where he first seeks to verify the claim of Hegel and Peirce, that the synthetical unity of apperception is to be analyzed as a unity of three forms of syllogism corresponding to Aristotle's three figures of syllogism, through a close study of Kant's transcendental deduction of the categories as well as of the transcendental ideas, before he comes to reformulate these deductions in the light of the original unity of sensuality and understanding. The development of this argument is critically examined in three respects, first, in reference to Zeidler's reading of Peirce, Hegel and Schelling, second, with respect to Zeidler's analysis of scientific rationality as well as of the architectonic of the Critique of pure reason, and third, in view of the influence of Erhard Oeser and Erich Heintel on Zeidler's thought. (shrink)

In the process of scientific discovery, knowledge ampliation is pursued by means of non-deductive inferences. When ampliative reasoning is performed, probabilities cannot be assigned objectively. One of the reasons is that we face the problem of the unconceived alternatives: we are unable to explore the space of all the possible alternatives to a given hypothesis, because we do not know how this space is shaped. So, if we want to adequately account for the process of knowledge ampliation, we need to (...) develop an account of the process of scientific discovery which is not exclusively based on probability calculus. We argue that the analytic view of the method of science advocated by Cellucci is interestingly suited to this goal, since it rests on the concept of plausibility. In this perspective, in order to account for how probabilities are in fact assigned in uncertain contexts and knowledge ampliation is really pursued, we have to take into account plausibility-based considerations. (shrink)

My dissertation is on scientific phenomena, their characterization, and their role in scientific inquiry. I focus on three questions. First, what do characterizations of scientific phenomena represent? To answer this, I investigate what it means to characterize a phenomenon, as opposed to describing the results of individual studies. Second, how do researchers develop these characterizations? This question relates to the logic of discovery: I examine how researchers use existing theories and methods to explore systems, search for phenomena, and develop representations (...) of them. Third, how do researchers evaluate these characterizations? This question relates to the logic of justification: I investigate how empirical findings serve as defeasible evidence for the characterizations of phenomena, and in light of what evidence we should accept, suspend judgment about, or reject them. (shrink)

In a recent work published in this journal, “Van Fraassen e a inferência da melhor explicação” (2016), Minikoski and Rodrigues da Silva identify four critical lines proposed by Bas van Fraassen against the form of abductive reasoning known as ‘inference to the best explanation’ (IBE). The first one, put forward by the Dutch philosopher in his seminal book The Scientific Image (1980), concerns the distinction between observable and unobservable entities. Minikoski and Rodrigues da Silva consider that the distinction is of (...) no relevance to the scientific practice. For this reason, they address van Fraassen’s allegations against IBE qua justification of the existence of unobservable entities in a couple of pages and prefer focusing on the other lines they identified. The aim of this work is to pour over the analysis that the two authors perform about van Fraassen’s mentioned argument and some realists’ replies, particularly in the section that Minikoski and Rodrigues da Silva devote to this topic. This will allow us to clarify van Fraassen’s vision on scientific practice and on the ‘immersion in the theoretical world-picture’. The importance and the relevance of the distinction between observables and unobservables will also be reaffirmed. (shrink)

I will examine the first of Thomas Kuhn’s Thalheimer Lectures delivered in 1984, with the purpose of establishing a connection between Kuhn’s historiographical thought and his criticism of the traditional distinction between the context of discovery and the context of justification, or, as I call it, the DJ distinction. In order to do this, I will start by exploring the Kuhnian view of the so-called static approach in philosophy of science, taking as my main reference the work of Bacon, Descartes, (...) and foundationalist epistemology. I will continue by examining the relationship between Kuhnian historiography and the DJ distinction, comparing the first Thalheimer Lecture with other texts published by Kuhn. Finally, I will assert that Kuhn’s rejection of the DJ distinction is the result of adopting a historiographical matrix whose philosophical consequences are irreconcilable with the static approach in history and philosophy of science, for which the DJ distinction is essential. (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 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)

The ocean terrain spanning the globe is vast and complex—far from an immense flat plain of mud. To map these depths accurately and wisely, we must understand how cartographic abstraction and generalization work both in analog cartography and digital GIS. This chapter explores abstraction practices such as selection and exaggeration with respect to mapping the oceans, showing significant continuity in such practices across cartography and contemporary GIS. The role of measurement and abstraction—as well as of political and economic power, and (...) sexual and personal bias—in these sciences is illustrated by the biographies of Marie Tharp and Bruce Heezen, whose mapping of the Mid-Atlantic Ridge precipitated a paradigm shift in geology. (shrink)

In his account of scientific revolutions, Thomas Kuhn suggests that after a revolutionary change of theory, it is as if scientists are working in a different world. In this paper, we aim to show that the notion of world change is insightful. We contrast the reporting of the discovery of neon in 1898 with the discovery of hafnium in 1923. The one discovery was made when elements were identified by their atomic weight; the other discovery was made after scientists came (...) to classify elements by their atomic number. By considering two instances of the reporting of the discovery of a new chemical element 25 years apart, we argue that it becomes clear how chemists can be said to have been responding to different worlds as a result of the change in the concept of a chemical element. They saw, did, and reported different things as they conducted their research on the new chemical elements. (shrink)

Causation is the main foundation upon which the possibility of science rests. Without causation, there would be no scientific understanding, explanation, prediction, nor application in new technologies. How we discover causal connections is no easy matter, however. Causation often lies hiddenfrom view and it is vital that we adopt the right methods for uncovering it. The choice of methods will inevitably reflect what one takes causation to be, making an accurate account of causation an even more pressing matter. This enquiry (...) informs the correct norms for an empirical study of the world. In Causation in Science and the Methods of Scientific Discovery, Rani Lill Anjum and Stephen Mumford propose nine new norms of scientific discovery. A number of existing methodological and philosophical orthodoxies are challenged as they argue that progress in science is being held back by an overlysimplistic philosophy of causation. (shrink)

This book is a collection of eight in-depth and detailed research papers authored by Dr. Raman K Attri between 1996 to 2005. The book presents early-career scientific work by the author as a scientist at a research organization. The book provides the conceptual background and key electronics and mechanical design principles used in designing sensors and instrumentation systems to measure snow hydrological parameters. The systems discussed in this book can be used to measure snow depth, layer temperature, temperature distribution profile, (...) surface porosity, etc. The snow parameters measured from instruments and sensors discussed in this book are integrated into larger systems and are used in computer-driven models for snow avalanche predictions. The book presents the design challenges and design methods from electronics and instrumentation design point of view. While the book provides essential understanding of analog electronics design and associated mechanical design for snow hydrological sensors, the book also presents the background theoretical and mathematical models from snow hydrology physics that governs this electronics design. (shrink)

This book is a collection of three papers authored by Dr. Raman K Attri between 1999 to 2005. The book provides a theoretical and conceptual understanding of concepts and principles of detection and measurements of the seismic signal. The papers provide fundamental concepts in seismic instrumentation design. The first paper presents a simplified mathematical framework of the seismic events and backend computational software logic that will enable software engineers to develop a customized seismic analysis and computation software. The second paper (...) presents a simplified description of various earthquake parameters of interest to a seismologist and how these complex parameters are computed using equations. In the third paper, a visionary concept is presented to integrate geo-scientific instrumentation equipment such as seismic measurement systems to information technology network that would create a centralized web-enabled database that would allow to transmit the data acquired by geographically distributed but networked observatories to better predict or alert about the phenomena like earthquakes. (shrink)

These last decades, the many contributions to the literary output on science and religion have dealt with topics that are on the cutting edge of scientific discovery, topics mainly in the area of theoretical physics, cognitive science, and evolutionary biology. Philosophers of religion, responding to this trend, have therefore struggled with intricate arguments, and have often made use of the highly technical language of these sciences. The overall result was that truly original philosophical contributions, ones that present new perspectives regarding (...) this area, have been very rare. Of these few new research programs, one seems to be particularly promising, especially because of the way it has been throwing new light on how science relates to other disciplines. The originality of this research-area lies in the fact that it refers not to particular scientific discoveries, considered individually, but to the general dynamics of the practical side of science. The crucial concept is expertise, which involves the appeal to authority for the justification of arguments. Many people like to think that scientific knowledge is far from all this, that it is purely objective and that it floats way above the murky waters of subjectivism. Those who are directly involved in scientific practice however know that science is not so clean. Appeal to authority remains very much part of the natural sciences, whether we like it or not. Some philosophers have recently ventured into these somewhat dark caverns of scientific thought and practice, and the result of their work has become very significant. In this paper, I will first offer a brief overview of this philosophical work, and then explore how the new insights regarding scientific expertise and scientific appeal to authority can throw light not only on how science works but also on the issue of authoritative knowhow within the Church. To avoid getting lost within the dim world of abstract principles, I will focus on one particular concrete case, the one of Vatican astronomers. This is a particularly interesting case because this group’s complex role lies precisely at the intersection between theological and scientific expertise. (shrink)

For centuries the case of Galileo Galilei has been the cornerstone of every major argument against the church and its supposedly unscientific dogmatism. The church seems to have condemned Galileo for his heresies, just because it couldn’t and wouldn’t handle the truth. Galileo was a hero of science wrongfully accused and now – at last – everyone knows that. But is that true? This paper tries to examine the case from the point of modern physics and the conclusions drawn are (...) startling. It seems that contemporary church was too haste into condemning itself. The evidence provided by Galileo to support the heliocentric system do not even pass simple scrutiny, while modern physics has ruled for a long time now against both heliocentric and geocentric models as depictions of the “truth”. As Einstein eloquently said, the debate about which system is chosen is void of any meaning from a physics’ point of view. At the end, the selection of the center is more a matter of choice rather than a matter of ‘truth’ of any kind. And this choice is driven by specific philosophical axioms penetrating astronomy for hundreds of years now. From Galileo to Hubble, the Copernican principle has been slowly transformed to a dogma followed by all mainstream astronomers. It is time to challenge our dogmatic adherence to the anti-humanism idea that we are insignificant in the cosmos and start making true honest science again, as Copernicus once postulated. (shrink)

In this article, network science is discussed from a methodological perspective, and two central theses are defended. The first is that network science exploits the very properties that make a system complex. Rather than using idealization techniques to strip those properties away, as is standard practice in other areas of science, network science brings them to the fore, and uses them to furnish new forms of explanation. The second thesis is that network representations are particularly helpful in explaining the properties (...) of non-decomposable systems. Where part-whole decomposition is not possible, network science provides a much-needed alternative method of compressing information about the behavior of complex systems, and does so without succumbing to problems associated with combinatorial explosion. The article concludes with a comparison between the uses of network representation analyzed in the main discussion, and an entirely distinct use of network representation that has recently been discussed in connection with mechanistic modeling. (shrink)

. Scientists, for the most part, want to get it right. However, the social structures that govern their work undermine that aim, and this leads to nonreplicable findings in many fields. Because the social structure of science is a decentralized system, it is difficult to intervene. In this article, I discuss how we might do so, focusing on self-corrective-labor schemes. First, I argue that we need to implement a scheme that makes replication work outcome independent, systematic, and sustainable. Second, I (...) use these three criteria to evaluate extant proposals, which place the responsibility for replication on original researchers, consumers of their research, students, or many labs. Third, on the basis of a philosophical analysis of the reward system of science and the benefits of the division of cognitive labor, I propose a scheme that satisfies the criteria better: the professional scheme. This scheme has two main components. First, the scientific community is organized into two groups: discovery researchers, who produce new findings, and confirmation researchers, whose primary function is to do confirmation work. Second, a distinct reward system is established for confirmation researchers so that their career advancement is separated from whether they obtain positive experimental results. (shrink)