Driven by an appreciation of the field’s early stage of development, I apply the concept of exploratory experimentation, originally put forward in the late 90s philosophy of biology, to current research in cognitive neuroscience. I concentrate on functional magnetic resonance imaging and how this wide-spread technique is used, from experimental design to data analysis. I claim that, although subject to certain significant modifications with respect to the concept’s original rendering, the exploratory character of neuroimaging experiments can be appreciated considering their (...) goals, centered on the stabilization of experimental systems for phenomenological description, and the relevance of their methodological facet. Although I do not claim that there is a specific kind of experiment that one can single out as definitely exploratory, exploration can be seen as a general trait imbuing fMRI-based experimentation. (shrink)

Model organisms are a living form of scientific models. Despite the widespread use of model organisms in scientific research, the actual representational relationship between model organisms and their target species is often poorly characterized in the context of cross-species research. Many model organisms do not represent the target species adequately, let alone accurately. This is partly due to the complex and emergent life phenomena in the organism, and partly due to the fact that a model organism is always taken to (...) represent a broad range of diverse organisms. More often than not, model organisms are taken as a reference point for an extrapolation to be made to the unknown characteristics of other species. I propose to view model organisms as analogue simulators which represent the emergent phenomenon in the context of cross-species research. A model organism represents a wide range of species by simulating their molecular microstates which underlie various emergent phenomena. I show that although model organisms represent the target species inadequately at many levels of complexity, they have epistemic values as a simulator in virtue of which the emergent phenomenon can be modeled dynamically, a virtue that is hardly attainable by non-dynamic models. (shrink)

Computational modeling is one of the primary approaches to constructing protein–protein interfaces in the laboratory. The algorithm-driven computational protein design has been successfully applied to the construction of functional proteins with improved binding affinity and increased thermostability. It is intriguing how a computational protein modeling approach can construct and shape the reality of new functional proteins from scratch. I articulate an account of abstraction and exploration-driven strategies in this computational endeavor. I aim to show that how a computational modelling approach, (...) which is laden with mathematics and algorithms, can have a constructive force on the target protein. (shrink)

Thought experiments are one among the oldest and effectively employed tools of scientific reasoning. Hacking (Philos Sci 2:302–308, 1992) argues that thought experiments in contrast to real experiments do not have a life of their own. In this paper, I attempt to show that contrary to Hacking’s contentions, thought experiments do have a life of their own. The paper is divided into three main sections. In the first section, I review the reasons that Hacking sets out for believing in the (...) life of experiments. Second section discusses Hacking’s characterization of thought experiments. The section also reviews his arguments for denying a life to thought experiments. In the third section, I argue for a life of thought experiments. In this section, I discuss the historical evolution of the EPR thought experiment and Galileo’s Free Falling Bodies in detail to show the untenability of Hacking’s arguments. The third section is followed by a conclusion that thought experiments do have a life of their own. (shrink)

It is now well-appreciated by philosophers that contemporary large-scale ‘-omics’ studies in biology stand in non-trivial relationships to more orthodox hypothesis-driven approaches. These relationships have been clarified by Ratti (2015); however, there remains much more to be said regarding how an important field of genomics cited in that work—‘genome-wide association studies’ (GWAS)—fits into this framework. In the present article, we propose a revision to Ratti’s framework more suited to studies such as GWAS. In the process of doing so, we introduce (...) to the philosophical literature novel exploratory experiments in (phospho)proteomics, and demonstrate how these experiments interplay with the above considerations. (shrink)

Experimentation represents today a ‘hot’ topic in computing. If experiments made with the support of computers, such as computer simulations, have received increasing attention from philosophers of science and technology, questions such as “what does it mean to do experiments in computer science and engineering and what are their benefits?” emerged only recently as central in the debate over the disciplinary status of the discipline. In this work we aim at showing, also by means of paradigmatic examples, how the traditional (...) notion of controlled experiment should be revised to take into account a part of the experimental practice in computing along the lines of experimentation as exploration. Taking inspiration from the discussion on exploratory experimentation in the philosophy of science—experimentation that is not theory-driven—we advance the idea of explorative experiments that, although not new, can contribute to enlarge the debate about the nature and role of experimental methods in computing. In order to further refine this concept we recast explorative experiments as socio-technical experiments, that test new technologies in their socio-technical contexts. We suggest that, when experiments are explorative, control should be intended in a posteriori form, in opposition to the a priori form that usually takes place in traditional experimental contexts. (shrink)

Molecular biologists exploit information conveyed by mechanistic models for experimental purposes. In this article, I make sense of this aspect of biological practice by developing Keller’s idea of the distinction between ‘models of’ and ‘models for’. ‘Models of (phenomena)’ should be understood as models representing phenomena and are valuable if they explain phenomena. ‘Models for (manipulating phenomena)’ are new types of material manipulations and are important not because of their explanatory force, but because of the interventionist strategies they afford. This (...) is a distinction between aspects of the same model. In molecular biology, models may be treated either as ‘models of’ or as ‘models for’. By analysing the discovery and characterization of restriction–modification systems and their exploitation for DNA cloning and mapping, I identify the differences between treating a model as a ‘model of’ or as a ‘model for’. These lie in the cognitive disposition of the modeller towards the model: a modeller will look at a model as a ‘model of’ if interested in its explanatory force, or as a ‘model for’ if interested in the material manipulations it can possibly afford. (shrink)

The 1980s, it is often claimed, was the decade when experimentation finally became a philosophical topic. This was the responsibility, the claim continues, of one particular movement within philosophy of science, called “new experimentalism.” The aim of this article is to complicate this historical narrative. We argue that in the 1980s, the study of experimentation was carried out not by one movement with one particular aim but rather in a diverse and open-ended way by people with different aims and backgrounds. (...) We then argue that from the late 1990s onward, this diversity disappeared and made room for disciplinary divisions—questions concerning experimentation became philosophical, others sociological, and so on. The reason for this, we claim, was that science and technology studies, philosophy of technology, and philosophy of science took over aspects of the 1980s study of experimentation. In this way, we argue, these elements became institutionalized, whereas others were forgotten. The importance of this process of institutionalization is illustrated by means of a discussion of other, similar approaches to the philosophy of experimentation that have not been able to ensure continuity because they did not find an institutional home. (shrink)

Recent claims, mainly from computer scientists, concerning a largely automated and model-free data-intensive science have been countered by critical reactions from a number of philosophers of science. The debate suffers from a lack of detail in two respects, regarding the actual methods used in data-intensive science and the specific ways in which these methods presuppose theoretical assumptions. I examine two widely-used algorithms, classificatory trees and non-parametric regression, and argue that these are theory-laden in an external sense, regarding the framing of (...) research questions, but not in an internal sense concerning the causal structure of the examined phenomenon. With respect to the novelty of data-intensive science, I draw an analogy to exploratory as opposed to theory-directed experimentation. (shrink)

The discovery and ongoing investigation of microRNAs suggest important conceptual and methodological lessons for philosophers and historians of biology. This paper provides an account of miRNA research and the shift from viewing these tiny regulatory entities as minor curiosities to seeing them as major players in the post-transcriptional regulation of genes. Conceptually, the study of miRNAs is part of a broader change in understandings of genetic regulation, in which simple switch-like mechanisms were reinterpreted as aspects of complex cellular and genome-wide (...) processes. Among them are the activities of small RNAs, previously regarded as non-functional. Methodologically, the miRNA story suggests new ways of characterizing biological research that should prove helpful to philosophers of science who seek to develop more pluralistic, pragmatic models of scientific inquiry. miRNA research displays iterative movements between multiple modes of investigation that include not only the proposal and testing of hypotheses but also exploratory, technology-oriented and question-driven modes of research. As an exemplary story of scientific discovery and development, the miRNA case illustrates transitions from genetics to genomics and systems biology, and it shows how diverse configurations of research practice are related to major scientific advances. (shrink)

Along three measurements at the Large Hadron Collider (LHC), a high energy particle accelerator, we analyze procedures and consequences of exploratory experimentation (EE). While all of these measurements fulfill the requirements of EE: probing new parameter spaces, being void of a target theory and applying a broad range of experimental methods, we identify epistemic differences and suggest a classification of EE. We distinguish classes of EE according to their respective goals: the exploration where an established global theory cannot provide the (...) details of a local phenomenon, exploration of an astonishing discovery and exploration to find a new entity. We find that these classes also differ with respect to the existence of an identifiable target and their impact on the background theory. The characteristics distinguish EE from other kinds of experimentation, even though these different kinds have not yet been systematically studied. The formal rigor and precision of LHC physics facilitates to analyze concept formation in its early state. In particular we emphasize the importance for nil–results for conceptualization and argue that conceptualization can also be achieved from nil–results only. (shrink)

In this essay, we examine the use of resting state fMRI data for psychological inferences. We argue that resting state studies hold the paired promises of discovering novel functional brain networks, and of avoiding some of the limitations of task-based fMRI. However, we argue that the very features of experimental design that enable resting state fMRI to support exploratory science also generate a novel confound. We argue that seemingly key features of resting state functional connectivity networks may be artefacts resulting (...) from sampling a ‘mixture distribution’ of diverse brain networks active at different times during the scan. We explore the consequences of this ‘mixture view’ for attempts to theorize about the cognitive or psychological functions of resting state networks, as well as the value of exploratory experiments. (shrink)

In this article, I introduce the notion of horizon for scientific practice (HSP), representing limits or boundaries within which scientists ply their trade, to facilitate analysis of scientific discovery and progress. The notion includes not only constraints that delimit scientific practice, e.g. of bringing experimentation to a temporary conclusion, but also possibilities that open up scientific practice to additional scientific discovery and to further scientific progress. Importantly, it represents scientific practice as a dynamic and developmental integration of activities to investigate (...) and analyze the natural world. I use the discovery of the clotting factor, thrombin, and the experiments conducted by the Johns Hopkins physiologist, William Howell, on the enzymatic nature of thrombin to illustrate the notion of HSP. In a concluding section, I compare the notion of HSP to other notions for scientific practice proposed in the history and philosophy of science literature. (shrink)

ABSTRACTExperimentation is traditionally considered a privileged means of confirmation. However, why and how experiments form a better confirmatory source relative to other strategies is unclear, and recent discussions have identified experiments with various modeling strategies on the one hand, and with ‘natural’ experiments on the other hand. We argue that experiments aiming to test theories are best understood as controlled investigations of specimens. ‘Control’ involves repeated, fine-grained causal manipulation of focal properties. This capacity generates rich knowledge of the object investigated. (...) ‘Specimenhood’ involves possessing relevant properties given the investigative target and the hypothesis in question. Specimens are thus representative members of a class of systems, to which a hypothesis refers. It is in virtue of both control and specimenhood that experiments provide powerful confirmatory evidence. This explains the distinctive power of experiments: although modelers exert extensive control, they do not exert this control over specimens; although natural experiments utilize specimens, control is diminished. (shrink)

This paper explores the case of using robots to simulate evolution, in particular the case of Hamilton’s Law. The uses of robots raises several questions that this paper seeks to address. The first concerns the role of the robots in biological research: do they simulate something or do they participate in something? The second question concerns the physicality of the robots: what difference does embodiment make to the role of the robot in these experiments. Thirdly, how do life, embodiment and (...) social behavior relate in contemporary biology and why is it possible for robots to illuminate this relation? These questions are provoked by a strange similarity that has not been noted before: between the problem of simulation in philosophy of science, and Deleuze’s reading of Plato on the relationship of ideas, copies and simulacra. (shrink)

ArgumentIn the theory-dominated view of scientific experimentation, all relations of theory and experiment are taken on a par; namely, that experiments are performed solely to ascertain the conclusions of scientific theories. As a result, different aspects of experimentation and of the relations of theory to experiment remain undifferentiated. This in turn fosters a notion of theory-ladenness of experimentation (TLE) that is toocoarse-grainedto accurately describe the relations of theory and experiment in scientific practice. By contrast, in this article, I suggest that (...) TLE should be understood as anumbrella conceptthat has different senses. To this end, I introduce a three-fold distinction among the theories of high-energy particle physics (HEP) as background theories, model theories, and phenomenological models. Drawing on this categorization, I contrast two types of experimentation, namely, “theory-driven” and “exploratory” experiments, and I distinguish between the “weak” and “strong” senses of TLE in the context of scattering experiments from the history of HEP. This distinction enables identifying the exploratory character of the deep-inelastic electron-proton scattering experiments – performed at the Stanford Linear Accelerator Center (SLAC) between the years 1967 and 1973 – thereby shedding light on a crucial phase of the history of HEP, namely, the discovery of “scaling,” which was the decisive step towards the construction of quantum chromo-dynamics as a gauge theory of strong interactions. (shrink)

In this paper, I propose an account that accommodates the possibility of experimentation being exploratory in cases where the procedures necessary to plan and perform an experiment are dependent on the theoretical accounts of the phenomena under investigation. The present account suggests that experimental exploration requires the implementation of an exploratory procedure that serves to extend the range of possible outcomes of an experiment, thereby enabling it to pursue its objectives. Furthermore, I argue that the present account subsumes the notion (...) of exploratory experimentation, which is often attributed in the relevant literature to the works of Friedrich Steinle and Richard Burian, as a particular type of experimental exploration carried out in the special cases where no well-formed theoretical framework of the phenomena under investigation exists. I illustrate the present account in the context of the ATLAS experiment at CERN’s Large Hadron Collider, where the long-sought Higgs boson has been discovered in 2012. I argue that the data selection procedure carried out in the ATLAS experiment illustrates an exploratory procedure in the sense suggested by the present account. I point out that this particular data selection procedure is theory-laden in that its implementation is crucially dependent on the theoretical models of high energy particle physics which the ATLAS experiment is aimed to test. However, I argue that the foregoing procedure is not driven by the above-mentioned theoretical models, but rather by a particular data selection strategy. I conclude that the ATLAS experiment illustrates that, contrary to what previous studies have suggested, there are cases of experimentation in which exploration serves to test theoretical predictions and that theory-ladenness plays an essential role in experimentation being exploratory. (shrink)

In contemporary human brain mapping, it is commonly assumed that the “mind is what the brain does”. Based on that assumption, task-based imaging studies of the last three decades measured differences in brain activity that are thought to reflect the exercise of human mental capacities (e.g., perception, attention, memory). With the advancement of resting state studies, tractography and graph theory in the last decade, however, it became possible to study human brain connectivity without relying on cognitive tasks or constructs. It (...) therefore is currently an open question whether the assumption that “the mind is what the brain does” is an indispensable working hypothesis in human brain mapping. This paper argues that the hypothesis is, in fact, dispensable. If it is dropped, researchers can “meet the brain on its own terms” by searching for new, more adequate concepts to describe human brain organization. Neuroscientists can establish such concepts by conducting exploratory experiments that do not test particular cognitive hypotheses. The paper provides a systematic account of exploratory neuroscientific research that would allow researchers to form new concepts and formulate general principles of brain connectivity, and to combine connectivity studies with manipulation methods to identify neural entities in the brain. These research strategies would be most fruitful if applied to the mesoscopic scale of neuronal assemblies, since the organizational principles at this scale are currently largely unknown. This could help researchers to link microscopic and macroscopic evidence to provide a more comprehensive understanding of the human brain. The paper concludes by comparing this account of exploratory neuroscientific experiments to recent proposals for large-scale, discovery-based studies of human brain connectivity. (shrink)

Farmers all over the world perform experiments, and have done so since long before modern experimental science and its recognized forerunners. There is a rich anthropological literature on these experiments, but the philosophical issues that they give rise to have not received much attention. Based on the anthropological literature, this study investigates methodological and philosophical issues pertaining to farmers’ experiments, including the choice of interventions to be tested, the planning of experiments, and the use of control fields and other means (...) to deal with confounding factors. Farmers’ experiments have some advantages over the field trials of agricultural scientists, but also some comparative disadvantages. The two experimental traditions are complementary, and neither of them can replace the other. Several aspects of farmers’ experiments are shown to have a direct bearing on central topics in the philosophy of science. (shrink)

Farmers all over the world perform experiments, and have done so since long before modern experimental science and its recognized forerunners. There is a rich anthropological literature on these experiments, but the philosophical issues that they give rise to have not received much attention. Based on the anthropological literature, this study investigates methodological and philosophical issues pertaining to farmers’ experiments, including the choice of interventions to be tested, the planning of experiments, and the use of control fields and other means (...) to deal with confounding factors. Farmers’ experiments have some advantages over the field trials of agricultural scientists, but also some comparative disadvantages. The two experimental traditions are complementary, and neither of them can replace the other. Several aspects of farmers’ experiments are shown to have a direct bearing on central topics in the philosophy of science. (shrink)

Farmers all over the world perform experiments, and have done so since long before modern experimental science and its recognized forerunners. There is a rich anthropological literature on these experiments, but the philosophical issues that they give rise to have not received much attention. Based on the anthropological literature, this study investigates methodological and philosophical issues pertaining to farmers’ experiments, including the choice of interventions to be tested, the planning of experiments, and the use of control fields and other means (...) to deal with confounding factors. Farmers’ experiments have some advantages over the field trials of agricultural scientists, but also some comparative disadvantages. The two experimental traditions are complementary, and neither of them can replace the other. Several aspects of farmers’ experiments are shown to have a direct bearing on central topics in the philosophy of science. (shrink)

The life sciences are said to be in the midst of a replication crisis because a majority of published results are irreproducible, and scientists rarely replicate existing data. Here I argue that point 2 of this assessment is flawed because there is a hitherto unidentified form of replication in the experimental life sciences, which I call ‘microreplications’. Using a case study from biochemistry, I illustrate how MRs depend on a key element of experimentation, namely, experimental controls. I end by reflecting (...) on what MRs mean for the broader debate about the replication crisis. (shrink)

The 2011 Nobel Prize in Physics was awarded to researchers from the Supernova Cosmology Project and the High-z Supernova Search Team for the discovery of the accelerating expansion of the universe. In this paper, I provide a historical analysis of the supernova cosmology evidence put forward by these teams for the accelerating universe, in terms of an iterative model of scientific progress developed by Hasok Chang in the context of his study of the development of measurement standards. I argue, using (...) the key concept of epistemic iteration, that the iterative model adequately accounts for evidence production in experimental science as well. In order to apply Chang’s model to the experimental evidence for the accelerating universe, I introduce the concept of endorsement as a particular mode of progress, and argue that supernova scientists produced an endorsed measurement system to claim evidence for their discovery. Furthermore, I show that the credibility of the evidence was not based on a particular measurement, rather, what proved to be decisive was the “robust consistency” of many individual results. (shrink)

The philosophical interest in experimental practice in neuroscience has brought renewed attention to the study of the development and use of techniques and tools for data production. John Bickle has argued that the construction and progression of theories in neuroscience are entirely dependent on the development and ingenious use of research tools. In Bickle's account, theory plays a tertiary role, as it depends on what the tools allow researchers to manipulate, and the tools, in turn, are developed not in order (...) to test theories but as solutions to engineering problems. However, Bickle's account is not entirely precise in explaining what informs researchers' decision-making in their atheoretical laboratory tinkering. Identifying the sources that guide researchers in tool development and use is crucial if one wishes to contribute to the philosophical or meta-scientific understanding of experimental practice in neuroscience. In the following paper, I claim that decision-making in tools' development and use in neuroscience is doubly guided. Pre-existing theory and concepts determine information's relevance, whereas tools' functioning in controlled situations determines information's reliability. Accordingly, experimenters' decision-making is situated both in the context of analysing, modelling or interpreting information and in the context of producing information. I study the case of the tungsten microelectrode developed by David Hubel during the 1950s. First, I show that pre-existing theory and concepts determine in advance what information would be relevant to obtain from the microelectrode. Second, I show that Hubel's tinkering follows the guidelines derived from the very structure of what we recognise as reliable experimentally produced information. Finally, I suggest that data-production processes allow experimenters to assess what to expect from an experimental system in terms of concept- and theory-generation and confirmation, thereby endorsing Bickle's tenet on the tertiary role of theory in neuroscience. (shrink)

In the late 19th century, physiologists such as David Ferrier, Eduard Hitzig, and Hermann Munk argued that cerebral brain functions are localized in discrete structures. By the early 20th century, this became the dominant position. However, another prominent physiologist, Friedrich Goltz, rejected theories of cerebral localization and argued against these physiologists until his death in 1902. I argue in this paper that previous historical accounts have failed to comprehend why Goltz rejected cerebral localization. I show that Goltz adhered to a (...) falsificationist methodology, and I reconstruct how he designed his experiments and weighted different kinds of evidence. I then draw on the exploratory experimentation literature from recent philosophy of science to trace one root of the debate to differences in how the German localizers designed their experiments and reasoned about evidence. While Goltz designed his experiments to test hypotheses about the functions of predetermined cerebral structures, the localizers explored new functions and structures in the process of constructing new theories. I argue that the localizers relied on untested background conjectures to justify their inferences about functional organization. These background conjectures collapsed a distinction between phenomena they produced direct evidence for (localized symptoms) and what they reached conclusions about (localized functions). (shrink)

Philosophers of science diverge on the question what drives the growth of scientific knowledge. Most of the twentieth century was dominated by the notion that theories propel that growth whereas experiments play secondary roles of operating within the theoretical framework or testing theoretical predictions. New experimentalism, a school of thought pioneered by Ian Hacking in the early 1980s, challenged this view by arguing that theory-free exploratory experimentation may in many cases effectively probe nature and potentially spawn higher evidence-based theories. Because (...) theories are often powerless to envisage workings of complex biological systems, theory-independent experimentation is common in the life sciences. Some such experiments are triggered by compelling observation, others are prompted by innovative techniques or instruments, whereas different investigations query big data to identify regularities and underlying organizing principles. A distinct fourth type of experiments is motivated by a major question. Here I describe two question-guided experimental discoveries in biochemistry: the cyclic adenosine monophosphate mediator of hormone action and the ubiquitin-mediated system of protein degradation. Lacking underlying theories, antecedent data bases, or new techniques, the sole guides of the two discoveries were respective substantial questions. Both research projects were similarly instigated by theory-free exploratory experimentation and continued in alternating phases of results-based interim working hypotheses, their examination by experiment, provisional hypotheses again, and so on. These two cases designate theory-free, question-guided, stepwise biochemical investigations as a distinct subtype of the new experimentalism mode of scientific enquiry. (shrink)

Stem cell biology is driven by experiment. Its major achievements are striking experimental productions: "immortal" human cell lines from spare embryos (Thomson et al. 1998); embryo-like cells from "reprogrammed" adult skin cells (Takahashi and Yamanaka 2006); muscle, blood and nerve tissue generated from stem cells in culture (Lanza et al. 2009, and references therein). Well-confirmed theories are not so prominent, though stem cell biologists do propose and test hypotheses at a profligate rate. 1 This paper aims to characterize the role (...) of experiment in stem cell biology, so as to answer the following question: how do experiments contribute to our knowledge of stem cells and related phenomena? The .. (shrink)

Data production in experimental sciences depends on localised experimental systems, but the epistemic properties of data transcend the contingencies of the processes that produce them. Philosophers often believe that experimental systems instantiate but do not produce the epistemic properties of data. In this paper, we argue that experimental systems' local functioning entails intrinsic capacities to produce the epistemic properties of data. We develop this idea by applying Derrida's model of arche-writing to study a case of theory-oriented experimental practice. Derrida's model (...) relativises or dissolves the conceptual distinction between the moment of data production and a subsequent moment of data dissemination. It thus has consequences for understanding both data production (despite being intrinsically local, data production a priori generates transferrable and modellable information) and data dissemination (when modelling information, researchers needs to refer this information to the context of its production). We study a case of data production in a non-exploratory experimental system designed to test a pre-existing hypothesis in visual neuroscience. A case of theory-oriented experimental practice should allow us to identify the autonomous functioning of experimental systems in data production more clearly, insofar as it allows us to study the limits of pre-existing theory in the activities of these systems. We suggest that pre-existing concepts, hypotheses and theories condition the relevance but not the production of experimental data. (shrink)

A number of scholars have recently drawn attention to the importance of iteration in scientific research. This paper builds on these previous discussions by drawing a distinction between epistemic and methodological forms of iteration and by clarifying the relationships between them. As defined here, epistemic iteration involves progressive alterations to scientific knowledge claims, whereas methodological iteration refers to an interplay between different modes of research practice. While distinct, these two forms of iteration are related in important ways. Contemporary research on (...) the biological effects of nanomaterials illustrates that methodological iteration can help to “initiate,” “equip,” and “stimulate” epistemic iteration. (shrink)

Exploratory experiments are widely characterized as experiments that do not test hypotheses. Experiments that do test hypotheses are characterized as confirmatory experiments. Philosophers have pointed out that research programmes can be both confirmatory and exploratory. However, these definitions preclude single experiments being characterized as both exploratory and confirmatory; how can an experiment test and not test a hypothesis? Given the intuition that some experiments are exploratory, some are confirmatory, and some are both, a recharacterization of the relationship between exploratory and (...) confirmatory experimentation is needed. I discuss ‘phase IV’ trials to show what this recharacterization could look like. Phase IV trials can be exploratory and confirmatory insofar as they concurrently test hypotheses and explore for unforeseen phenomena. Even if it is uncontroversial that a single experiment can have multiple aims, the recharacterization of the relationship between exploratory and confirmatory experimentation is still required for these aims to be held together coherently. I offer an alternative characterization of the relationship between exploratory and confirmatory experimentation where the former remains a distinct kind of experimentation but is not characterized as non-hypothesis-testing. (shrink)

Since the discovery of dark matter in the 1980s, multiple experiments have been set up to detect dark matter particles through some other mode than gravity. Particle physicists provide detailed jus...

I develop an account of productive surprise as an epistemic virtue of scientific investigations which does not turn on psychology alone. On my account, a scientific investigation is potentially productively surprising when results can conflict with epistemic expectations, those expectations pertain to a wide set of subjects. I argue that there are two sources of such surprise in science. One source, often identified with experiments, involves bringing our theoretical ideas in contact with new empirical observations. Another, often identified with simulations, (...) involves articulating and bringing together different parts of our knowledge. Both experiments and simulations, then, can surprise. (shrink)

Experimental archaeology is often understood both as testing hypotheses about processes shaping the archaeological record and as generating tacit knowledge. Considering lithic technologies, I examine the relationship between these conceptions. Experimental archaeology is usefully understood via “maker’s knowledge”: archaeological experiments generate embodied know-how enabling archaeological hypotheses to be grasped and challenged, and further, well-positioning archaeologists to generate integrated interpretations. Finally, experimental archaeology involves “material speculation”: the constraints and affordances of archaeologists and their materials shape productive exploration of the capacities of (...) objects and human skill in ways relevant to archaeological questions. (shrink)

To explain their role in discovery and contrast them with theory-driven research, philosophers of science have characterized exploratory experiments in terms of what they lack: namely, that they lack direction from what have been called “local theories” of the target system or object under investigation. I argue that this is incorrect: it’s not whether or not there is direction from a local theory that matters, but instead how such a theory is used to direct an experiment that matters. Appealing to (...) contemporary exploratory experiments that involve the use of experimental techniques—specifically, examples where scientists explore the interaction of neural activity and human behavior by magnetically stimulating brains—I argue that local theories of a target system can inform auxiliary hypotheses in exploratory experiments, which direct these experiments. These examples illustrate how local theories can direct the exploration of target systems where researchers do not aim to evaluate these theories. (shrink)

The aim of this work is to elucidate John F. W. Herschel’s distinctive contribution to nineteenth-century British inductivism by exploring his understanding of experimental methods. Drawing on both his explicit discussion of experiment in his Preliminary Discourse on Natural Philosophy and his published account of experiments he conducted in the domain of electromagnetism, I argue that the most basic principle underlying Herschel’s epistemology of experiment is that experiment enables a particular kind of lower-level experimental understanding of phenomena. Experimental practices provide (...) knowledge of a particular phenomenon as a genuine effect produced under precise material conditions whose connections with other phenomena can be traced by variations in experimental parameters. The orienting concern of experimental inquiry seems to be the production of a secure understanding of phenomena even if it has no direct theoretical significance. Insofar as one can generate this lower-level understanding, it can function both as a fertile source for explanatory principles about phenomena and as a body of evidence against which one can test the adequacy of an explanatory hypothesis. This project provides evidence of Herschel’s inductivism not merely as a philosophical approach to understanding the sciences but as a methodological commitment in scientific practice. (shrink)

This chapter offers a review of standard views about the requirements for natural selection to shape evolution and for the sorts of ‘units’ on which selection might operate. It then summarizes traditional arguments for genic selectionism, i.e., the view that selection operates primarily on genes (e.g., those of G. C. Williams, Richard Dawkins, and David Hull) and traditional counterarguments (e.g., those of William Wimsatt, Richard Lewontin, and Elliott Sober, and a diffuse group based on life history strategies). It then offers (...) a series of responses to the arguments, based on more contemporary considerations from molecular genetics, offered by Carmen Sapienza. A key issue raised by Sapienza concerns the degree to which a small number of genes might be able to control much of the variation relevant to selection operating on such selectively critical organs as hearts. The response to these arguments suggests that selection acts on many levels at once and that sporadic selection, acting with strong effects, can act successively on different key traits (and genes) while maintaining a balance among many potentially conflicting demands faced by organisms within an evolving lineage. (shrink)

Deep neural networks have become increasingly successful in applications from biology to cosmology to social science. Trained DNNs, moreover, correspond to models that ideally allow the prediction of new phenomena. Building in part on the literature on ‘eXplainable AI’, I here argue that these models are instrumental in a sense that makes them non-explanatory, and that their automated generation is opaque in a unique way. This combination implies the possibility of an unprecedented gap between discovery and explanation: When unsupervised models (...) are successfully used in exploratory contexts, scientists face a whole new challenge in forming the concepts required for understanding underlying mechanisms. (shrink)

Signature-based model-independent searches for new physics form an explorative component of High Energy Physics experiments that aims at avoiding biases toward beyond-the-standard-model theo...

The experimental practice in contemporary molecular biology oscillates between the creativity of the researcher in tinkering with the experimental system, and the necessity of standardization of methods of inquiry. Experimental procedures, when standardized in lab protocols, might definitely be seen as actual recipes. Considering these protocols as recipes can help us understand some epistemological characteristics of current practice in molecular biology. On the one hand, protocols represent a common ground, i.e. the possibility of reproducibility, which constitutes one of the essential (...) properties for contemporary science to define an actual discovery. At the same time, however, protocols are flexible enough to be adapted by the individual researcher (within a space of maneuver given by the experimental system and by the practices that each individual discipline gives to itself) to his/her specific needs. These variations, just like the recipes, remind us that the legitimacy of an experimental practice, involves both objective and subjective constraints and it is articulated on a fuzzy background rather than a rigid and clear context. Moreover, looking at experiments according to this perspective can provide a key to understanding how different forms of science (which adopt different methodologies but which investigate the same phenomena), such as computational biology, are precisely different in the use of a different “cookbook”.Indeed, given the procedural/operational realism of biologists towards phenomena, the clash of different procedures has opened a discussion also about the nature and the meaning of the obtained results. Thus, according to the recipe-perspective that, the methodological struggle over the nature of biological phenomena (and their ways of discovery) among scientists, might be seen as a not always explicit, epistemological debate, however coming from the practice of science itself. (shrink)

Thought experiments (TEs) are important tools in science, used to both undermine and support theories, and communicate and explain complex phenomena. Their interest within philosophy of science has been dominated by a narrow question: How do TEs increase knowledge? My aim is to push beyond this to consider their broader value in scientific practice. I do this through an investigation into the scientific imagination. Part one explores questions regarding TEs as “experiments in the imagination” via a debate concerning the epistemic (...) status of computer simulations in science. I outline how, against Hacking, TEs also have “a life of their own” and I argue against accounts that privilege experiments over simulations (and by extension TEs) in light of their capacity to surprise in a productive way. Part two develops a pluralist account of the nature of the imagination in science. At its core, my view is that when we attend to a number of examples of TEs and consider the context in which they are used, we see that TEs engage a variety of our imaginative capacities. Existing monistic views fail to recognise the richness of the imagination and its potential in science. Part three looks to the “beauty” of TEs which is currently overlooked in the aesthetics of science literature. I put forward a new account that demonstrates the epistemic value of aesthetic features in science by showing how an appropriate fit between form and content enhances the usability of a TE, and its effectiveness as a prompt for our imagination. This also enables a more nuanced take on the proposed similarities between TEs and literary fictions. In the concluding chapter, I outline ways in which the core features of my account can be extended beyond TEs to illuminate the significance of the imagination and aesthetic values in other areas of science. (shrink)