‘Serendipity’ is a category used to describe discoveries in science that occur at the intersection of chance and wisdom. In this paper, I argue for understanding serendipity in science as an emergent property of scientific discovery, describing an oblique relationship between the outcome of a discovery process and the intentions that drove it forward. The recognition of serendipity is correlated with an acknowledgment of the limits of expectations about potential sources of knowledge. I provide an analysis of (...) serendipity in science as a defense of this definition and its implications, drawing from theoretical and empirical research on experiences of serendipity as they occur in science and elsewhere. I focus on three interrelated features of serendipity in science. First, there are variations of serendipity. The process of serendipitous discovery can be complex. Second, a valuable outcome must be obtained before reflection upon the significance of the unexpected observation or event in respect to that outcome can take place. Therefore, serendipity is retrospectively categorized. Third, the primacy of epistemic expectations is elucidated. Finally, I place this analysis within discussions in philosophy of science regarding the impact of interpersonal competition upon the number and significance of scientific discoveries. Thus, the analysis of serendipity offered in this paper contributes to discussions about the social-epistemological aspects of scientific discovery and has normative implications for the structure of epistemically effective scientific communities. (shrink)

This volume offers selected papers exploring issues arising from scientific discovery in the social sciences. It features a range of disciplines including behavioural sciences, computer science, finance, and statistics with an emphasis on philosophy. The first of the three parts examines methods of social scientific discovery. Chapters investigate the nature of causal analysis, philosophical issues around scale development in behavioural science research, imagination in social scientific practice, and relationships between paradigms of inquiry and scientific fraud. The next part (...) considers the practice of social science discovery. Chapters discuss the lack of genuine scientific discovery in finance where hypotheses concern the cheapness of securities, the logic of scientific discovery in macroeconomics, and the nature of that what discovery with the Solidarity movement as a case study. The final part covers formalising theories in social science. Chapters analyse the abstract model theory of institutions as a way of representing the structure of scientific theories, the semi-automatic generation of cognitive science theories, and computational process models in the social sciences. The volume offers a unique perspective on scientific discovery in the social sciences. It will engage scholars and students with a multidisciplinary interest in the philosophy of science and social science. (shrink)

What is the role of chance in scientific discovery? And, more to the point, if chance plays a key role in scientific discovery, what room is left for reason? These are grounding questions in the debates, for instance, over whether there is a distinction to be made between discovery and justification in science, and whether innate genius must play a role in discovery or if there exists some method that can be taught to anyone. While the role of chance (...) has been discussed throughout the history of science, it has resurfaced in recent debates over how science should be funded, and particularly in the field of biomedical research. The word serendipity, for example, has become increasingly... (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)

An important fact about human labor is that it can result not just in reproduction of what it started with, but in something new, a surplus product. When the latter is a means of production, it makes possible a mechanism of change consisting of reproduction by means of the expanded means of production. Each iteration of the labor process can differ from the preceding one insofar as it incorporates the surplus generated previously. Over the long-term, this cyclical process can lead (...) to the self-transformation of labor and, through it, of human societies and cultures. In this paper, I argue that this mechanism of change is also at work in the history of science. I argue that the form this mechanism takes in science is that of a feedback loop between discovery and instrument construction. This process requires the integration, and transformation into material form, of different kinds of knowledge. Based on this mechanism, I defend a concept of scientific progress as transcendence of the limitations of native human epistemic abilities. I also criticize narrowly biologistic approaches to the history of science for ignoring the role of surplus generation in transforming the labor process, and discuss some problems associated with viewing science as labor. (shrink)

This study compares Pairs of subjects with Single subjects in a task of discovering scientific laws with the aid of experiments. Subjects solved a molecular genetics task in a computer micro‐world (Dunbar, 1993). Pairs were more successful in discovery than Singles and participated more actively in explanatory activities (i.e., entertaining hypotheses and considering alternative ideas and justifications). Explanatory activities were effective for discovery only when the subjects also conducted crucial experiments. Explanatory activities were facilitated when paired subjects made requests of (...) each other for explanation and focused on them. The study extends from individual to collaborative discovery activities the importance to the discovery process of setting goals to find hypotheses and evidence (Dunbar, 1993) and to construct explanations of phenomena and processes encountered in examples (Chi, Bassok, Lewis, & Glaser, 1989). (shrink)

The scientific reasoning strategies used to discover a new concept in a scientific domain were investigated in two studies. An innovative task in which subjects discover new concepts in molecular biology was used. This task was based upon one set of experiments that Jacob and Monod used to discover how genes are controlled, and for which they were awarded the Nobel prize. In the two studies reported in this article, subjects were taught some basic facts and experimental techniques in molecular (...) biology, using a simulated molecular genetics laboratory on a computer. Following their initial training, they were then asked to discover how genes are controlled by other genes. In Study 1, subjects found no evidence that was consistent with their initial hypothesis. Subjects then set one of two goals for conducting experiments and evaluating data. One goal was to search for evidence consistent with the current hypothesis (and they did not attend to the features of discrepant findings); none of the subjects who only had this goal succeeded at discovering how the genes were controlled. Other subjects in Study 1 used a different goal: Upon noticing evidence inconsistent with their current hypothesis, these subjects set a new goal of attempting to explain the cause of the discrepant findings. Using this goal, a subset of these subjects discovered the correct solution to the problem. Study 2 was conducted to test the hypothesis that subjects' goals of finding evidence consistent with their current hypothesis blocks consideration of alternate hypotheses and generation of new goals, it was predicted that if subjects could achieve their initial goal of discovering evidence consistent with their current hypothesis, they would then attend to particular features of discrepant evidence and solve the problem. To test this prediction, an additional mechanism of genetic control that was consistent with subjects' initial goal was added to the genes. Here, subjects had to discover two mechanisms of control: one mechanism consistent with their current hypothesis, and one inconsistent with their hypothesis. Twice as many subjects reached the correct solution in Study 2 than in Study 1. The findings of the two studies indicate that goals provide a powerful constraint on the cognitive processes underlying scientific reasoning and that the types of goals that are represented determine many of the reasoning errors that subjects make. (shrink)

The idea of elegance in science is not necessarily a familiar one, but it is an important one. The use of the term is perhaps most clear-cut in mathematics - the elegant proof - and this is where Ian Glynn begins his exploration. Scientists often share a sense of admiration and excitement on hearing of an elegant solution to a problem, an elegant theory, or an elegant experiment. The idea of elegance may seem strange in a field of endeavour (...) that prides itself in its objectivity, but only if science is regarded as a dull, dry activity of counting and measuring. It is, of course, far more than that, and elegance is a fundamental aspect of the beauty and imagination involved in scientific activity. Ian Glynn, a distinguished scientist, selects historical examples from a range of sciences to draw out the principles of science, including Kepler's Laws, the experiments that demonstrated the nature of heat, and the action of nerves, and of course the several extraordinary episodes that led to Watson and Crick's discovery of the structure of DNA. With a highly readable selection of inspiring episodes highlighting the role of beauty and simplicity in the sciences, the book also relates to important philosophical issues of inference, and Glynn ends by warning us not to rely on beauty and simplicity alone - even the most elegant explanation can be wrong. (shrink)

The ArgumentScientific tools—measurement and calculation instruments, techniques of inference—straddle the line between the context of discovery and the context of justification. In discovery, new scientific tools suggest new theoretical metaphors and concepts; and in justification, these tool-derived theoretical metaphors and concepts are morelikely to be accepted by the scientific community if the tools are already entrenched in scientific practice.Techniques of statistical inference and hypothesis testing entered American psychology first as tools in the 1940s and 1950s and then as cognitive theories (...) in the 1960s and 1970s. Not only did psychologists resists statistical metaphors of mind prior to the institutionalization of inference techniques in their own practice; the cognitive theories they ultimately developed about “the mind as intuitive statistician” still bear the telltale marks of the practical laboratory context in which the tool was used. (shrink)

This article discusses three recent philosophers who speak in different ways about the retroactive construction of reality by human knowledge. Bruno Latour unapologetically claims that the Egyptian Pharaoh Ramses II could not have died of tuberculosis, as determined by a team of French doctors in 1976, since this disease was not discovered until three thousand years after his death. Slavoj Žižek often makes comparable arguments, though his version of retroactivity draws on both psychoanalysis and dialectics in a way that is (...) never the case for Latour. Yet in his 2012 book Less Than Nothing, Žižek takes the more prudent, realist-sounding line that changes in scientific theories do not change nature itself. The real novelty in retroactive theories is provided by Thomas Kuhn, who draws our attention to a grey temporal zone in scientific discovery in which it is impossible to pinpoint the exact date of any breakthrough. For Kuhn, this stems from a dualism found in reality itself: one between the fact “that” a thing exists and the determination of “what” its properties are. The tension between these two moments is responsible for much of the vagueness and drama surrounding any paradigm shift in the sciences and is closely related to at least one plausible theory of metaphor. In closing, three Hollywood films are cited as helpful examples for understanding the different ways in which a paradigm shift works its retroactive magic. (shrink)

All types of logic started with Aristotle and have been corrected as a traditional, formal, conditional, classical logic and even modern logic carry the main problems of Aristotelian logic. Despite their important differences, because of these core commonalities they are all called Classical Logic. The fundamental limitations of classical logic make it impossible to advance the knowledge necessary to solve growing human problems. All human knowledge, especially scientific knowledge is based on the logical principles that seem to hinder the knowledge (...) of reality rather than facilitate it; although in the beginning, this logic has helped mankind in acquiring knowledge. Fuzzy logic has been successful as an effective solution in science and in practice, but it lacks the necessary philosophical foundations so it has faced with several major problems and on important paradox in theorizing. First, the main challenges in classical logic are diseased in this article, then it is explained how to solve the problems and most important paradox to apply the fuzzy logic for scientific discoveries in a new approach. Finally, the new paradigm of Fuzziological Epistemology (fuzzy based epistemology) has been proposed in term of Dynamic Fuzzy Puzzle Theory. (shrink)

This paper analyzes features of the emergence of new fields in science by examining the cases of cytology and biochemistry. The first step in the emergence of these new fields was the discovery of a new entity. A subsequent claim was made that entities of this kind are found more generally; making this generalization constituted the construction of a new theory. As a line of research to test the theory began, a new domain was formed and the new field (...) emerged. In each case the theory proposed a new solution to an old problem in science. Some implications of this analysis for understanding the emergence of other fields are indicated. (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)

With In Search of Mechanisms, Carl F. Craver and Lindley Darden offer both a descriptive and an instructional account of how biologists discover mechanisms. Drawing on examples from across the life sciences and through the centuries, Craver and Darden compile an impressive toolbox of strategies that biologists have used and will use again to reveal the mechanisms that produce, underlie, or maintain the phenomena characteristic of living things. They discuss the questions that figure in the search for mechanisms, characterizing the (...) experimental, observational, and conceptual considerations used to answer them, all the while providing examples from the history of biology to highlight the kinds of evidence and reasoning strategies employed to assess mechanisms. At a deeper level, Craver and Darden pose a systematic view of what biology is, of how biology makes progress, of how biological discoveries are and might be made, and of why knowledge of biological mechanisms is important for the future of the human species. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Jewish Thought and Scientific Discovery in Early Modern EuropeNoah J. EfronAlmost a quarter-century ago Benjamin Nelson published his famous plea for what he called a “differential” and “comparative historical sociology of ‘science’ in civilizational perspective.” 1 Like Max Weber, Robert Merton, and Joseph Needham, Nelson believed that the growth of western science could be better understood when compared to the ways “science” fared in other cultures (...) with other intellectual and institutional and economic sensibilities and structures. A particularly propitious case study for such a differential and comparative historical study of science, as Hillel Levine observed in his 1983 essay about Jewish reactions to heliocentrism, are the Jews of early modern Europe, who constituted “a society geographically and culturally contiguous with those who framed and advanced occidental ‘science.’” 2Since about the time of Nelson’s plea, David B. Ruderman has been writing the history of Jewish attitudes towards, and engagements with, science during the period in which modern western science was constituting itself. It is no exaggeration to say that he established this as a field of study, producing a steady stream of historical studies, initially of Italian Jews who read and wrote about nature and its study, but continually expanding his compass. 3 The field [End Page 719] Ruderman established and the studies he produced have been “repercussive” (to borrow his own adjective) in many directions—shedding light on Jewish-Christian relations, on early-modern Jewish intellectual history, on the deployments of Kabbalah and magic in early modern times, and so on. One of Ruderman’s achievements—perhaps not the most important in his view (for he considers himself a historian of Jewish thought and culture and not a historian of science) but of great importance nonetheless—has been to begin to lay the groundwork for a comparative history of Jewish and Christian attitudes towards and participation in the “new sciences.”Ruderman’s newest book is a big step towards Nelson’s desideratum, using Jewish attitudes as the comparative case. It is a collection of twelve linked essays (five of which have appeared elsewhere in one form or another) framed by a synthetic introduction and epilogue. The essays are individual or group portraits of Jews who evinced interest in natural philosophy or medicine, in a variety of settings and for a variety of reasons, between the sixteenth and eighteenth centuries. Ruderman describes his subject as “three distinct but interrelated groups among early modern Jews”: (1) “converso physicians and other university-trained intellectuals who fled Spain and Portugal in the seventeenth century and settled in Holland, Italy, Germany, England, and even eastern Europe, serving as doctors and purveyors of scientific learning throughout the Jewish communities of Europe, while yielding considerable political and economic power,” (2) “certain circles of Jewish scholars in central and eastern Europe [who] pursued scientific learning, especially astronomy, in more informal settings as a desirable supplement to rabbinic study,” and (3) “the hundreds of Jews who attended Italian medical schools, primarily the University of Padua, from the late sixteenth through the eighteenth centuries.” 4In fact Ruderman covers even more ground than this. As background, he includes a brief essay on the attitudes of tenth- to fifteenth-century Jews towards nature and its study, surely the best survey of the sort available. Of the thirty or so early modern Jews that he describes in the remainder of the book, about twenty fit in at least one of the three camps upon which he focuses. 5 Nine [End Page 720] emerged from different circumstances (though these too were often highly influenced by one or more of the focus populations). This fact does nothing to impugn Ruderman’s typology—the groups he described were, in fact, of particular importance, and his identification of them as the principle populations contemplating and promulgating natural philosophy among Jews is in itself an advance of some moment. But the fact that a third of the cases Ruderman described do not fit into his own typology is testimony both to the complexity of his subject, and to his agility in addressing it.By anthologizing a dozen depictions of different thinkers in different milieus, Ruderman affords what might be called a “hawk... (shrink)

In this thesis I am going to explain the role of metaphor in articulation of new scientific theories, explicitly speaking, indeed, I have not a word about metaphorical thinking in theory invention, implicitly speaking. In fact, I talk about conceptual metaphor instead of linguistic metaphor. As another classification, this investigation belongs to “justification context”, rather than “discovery context”. Employing Boyd’ ideas on metaphor in science can lend a hand for acquiring this point. In Boyd’ set of beliefs; we need (...) another reference theory which has not the problems of kiripki-pautnam’s reference fixing theory, thus, Boyd proposes the “epistemic-access theory of reference”. With accepting “interacting view” of Block on metaphor, he demonstrates that in this theory of reference we are not encountering the problems such as referent shifting, lack of precise of metaphor which exist in kripki-pautnam’s reference fixing. On the other hand, by admitting “relativity”, Kuhn criticizes the Boyd’s attitude on metaphor in science. To conclude, I defend kripki-pautnam’s reference fixing theory; since, it seems to be implausible to accept Boyd’s criticism. (shrink)

Multiple simultaneous independent discoveries, so well enunciated by Robert K. Merton in the early 1960s but already discussed for several hundreds of years, is a classic concept in the sociology of science. In this paper, the concept of multiple simultaneous independent errors is proposed, analyzed, and discussed. The concept of Selective Pessimistic Induction is proposed and used to connect MIDs with MIEs. Five types of MIEs are discussed: multiple errors in the interpretation of experimental data or computational results; (...) multiple misjudgments of the value of another’s research results or conclusions; multiple cases of false anticipation of achieving a certain experimental result; multiples of ignoring or omitting relevant precedents; and multiple instances of failure due to a not-yet-conceived scientific concept or principle. Causal MIDs and MIEs are those that can be traced directly to antecedent knowledge. Acausal MIDs and MIEs are those involving a consequential and identifiable leap from antecedent knowledge. Examples of causal and acausal MIEs are provided, mostly but not exclusively from the discipline of chemistry. Comparisons are made between MIDs and MIEs. Topics for future research are discussed and implications of these concepts are proposed. (shrink)

The INBIOSA project brings together a group of experts across many disciplines who believe that science requires a revolutionary transformative step in order to address many of the vexing challenges presented by the world. It is INBIOSA’s purpose to enable the focused collaboration of an interdisciplinary community of original thinkers. This paper sets out the case for support for this effort. The focus of the transformative research program proposal is biology-centric. We admit that biology to date has been more (...) fact-oriented and less theoretical than physics. However, the key leverageable idea is that careful extension of the science of living systems can be more effectively applied to some of our most vexing modern problems than the prevailing scheme, derived from abstractions in physics. While these have some universal application and demonstrate computational advantages, they are not theoretically mandated for the living. A new set of mathematical abstractions derived from biology can now be similarly extended. This is made possible by leveraging new formal tools to understand abstraction and enable computability. [The latter has a much expanded meaning in our context from the one known and used in computer science and biology today, that is "by rote algorithmic means", since it is not known if a living system is computable in this sense (Mossio et al., 2009).] Two major challenges constitute the effort. The first challenge is to design an original general system of abstractions within the biological domain. The initial issue is descriptive leading to the explanatory. There has not yet been a serious formal examination of the abstractions of the biological domain. What is used today is an amalgam; much is inherited from physics (via the bridging abstractions of chemistry) and there are many new abstractions from advances in mathematics (incentivized by the need for more capable computational analyses). Interspersed are abstractions, concepts and underlying assumptions “native” to biology and distinct from the mechanical language of physics and computation as we know them. A pressing agenda should be to single out the most concrete and at the same time the most fundamental process-units in biology and to recruit them into the descriptive domain. Therefore, the first challenge is to build a coherent formal system of abstractions and operations that is truly native to living systems. Nothing will be thrown away, but many common methods will be philosophically recast, just as in physics relativity subsumed and reinterpreted Newtonian mechanics. -/- This step is required because we need a comprehensible, formal system to apply in many domains. Emphasis should be placed on the distinction between multi-perspective analysis and synthesis and on what could be the basic terms or tools needed. The second challenge is relatively simple: the actual application of this set of biology-centric ways and means to cross-disciplinary problems. In its early stages, this will seem to be a “new science”. This White Paper sets out the case of continuing support of Information and Communication Technology (ICT) for transformative research in biology and information processing centered on paradigm changes in the epistemological, ontological, mathematical and computational bases of the science of living systems. Today, curiously, living systems cannot be said to be anything more than dissipative structures organized internally by genetic information. There is not anything substantially different from abiotic systems other than the empirical nature of their robustness. We believe that there are other new and unique properties and patterns comprehensible at this bio-logical level. The report lays out a fundamental set of approaches to articulate these properties and patterns, and is composed as follows. -/- Sections 1 through 4 (preamble, introduction, motivation and major biomathematical problems) are incipient. Section 5 describes the issues affecting Integral Biomathics and Section 6 -- the aspects of the Grand Challenge we face with this project. Section 7 contemplates the effort to formalize a General Theory of Living Systems (GTLS) from what we have today. The goal is to have a formal system, equivalent to that which exists in the physics community. Here we define how to perceive the role of time in biology. Section 8 describes the initial efforts to apply this general theory of living systems in many domains, with special emphasis on crossdisciplinary problems and multiple domains spanning both “hard” and “soft” sciences. The expected result is a coherent collection of integrated mathematical techniques. Section 9 discusses the first two test cases, project proposals, of our approach. They are designed to demonstrate the ability of our approach to address “wicked problems” which span across physics, chemistry, biology, societies and societal dynamics. The solutions require integrated measurable results at multiple levels known as “grand challenges” to existing methods. Finally, Section 10 adheres to an appeal for action, advocating the necessity for further long-term support of the INBIOSA program. -/- The report is concluded with preliminary non-exclusive list of challenging research themes to address, as well as required administrative actions. The efforts described in the ten sections of this White Paper will proceed concurrently. Collectively, they describe a program that can be managed and measured as it progresses. (shrink)

Critical realism claims to bring a significant improvement to social science, especially in comparison with empiricist and interpretive approaches. So far, however, it has fallen short of the high expectations it raises. Critical realist arguments are convincing on the philosophical or meta-theoretical level but the contributions of critical realism to social science in terms of research activities at the field level are less clear. Nonetheless, there is no way back. Moving forward requires that the practice of doing social (...) scientific research be no longer perceived as limited to the justification of specific knowledge claims but must be seen as an integral part of the cycle of scientific discovery. (shrink)

Should scientists value simple theories? Is fruitfulness an important criterion to assess scientific theories? What role moral, social, and political values should have in the assessment of scientific theories? In recent years, there has been an increasing interest among philosophers of science in studying how cognitive and non-cognitive values influence and should influence the assessment and comparison of scientific theories. While cognitive values (such as simplicity and fruitfulness) are features of scientific theories that are indicative of the truth or (...) empirical adequacy of theories, non-cognitive values are moral, political, social, and economic values. Understanding the roles of values in science is a particularly urgent issue. Clarifying the importance of cognitive values is important in order to be able to make accurate comparisons of scientific theories. Understanding the influence of non-cognitive values on science is crucial because moral, social, and political values are involved in many stages of research, such as decisions on methodologies and allocation of funds. Since these decisions affect all the members of the society (scientists, non-experts, and political institutions), understanding the impact of non-cognitive values on these choices is of primary importance. Although a large body of literature has investigated the roles of cognitive and non-cognitive values in theory appraisal, several questions remain to be analysed. In this dissertation, I address four questions by using two main methods, namely the analysis of case studies from evolutionary psychology and the experimental method. First, while philosophers have clarified the importance and roles in theory appraisal of some cognitive values, little or no attention has been paid to other values. In this dissertation, I have started filling this gap by formulating a clear explication and a simple strategy to be employed in theory appraisal for one of the values that have attracted little attention, namely fruitfulness. I have explicated fruitfulness as the ability of programs to extend their content and suggested considering research questions and discovery heuristics to assess this ability. Moreover, I have used my account to assess the fruitfulness of evolutionary psychology. Second, some philosophers of science argue that cognitive values are desirable and relevant to the assessment of theories because they are indicative of the truth or empirical adequacy of theories. However, why is it so? In my dissertation, I develop a context-sensitive approach to values and I argue that in order to understand the ground for the desirability of cognitive values and make an accurate appraisal of theories, we have to consider specific factors of the context in which theories are assessed, such as the availability of methodologies and the way cognitive values are interrelated to each other in that context. Third, philosophers have traditionally argued that the influence of non-cognitive values on scientific reasoning threatens the epistemic authority of science. I have challenged this view and argued that some non-cognitive values can play a cognitive role in science, i.e., they can be epistemically beneficial to the assessment of scientific theories. On the basis of a case study (the account of human mating in evolutionary psychology), I have argued that feminist values have positively contributed to theory appraisal in various ways, such as by raising sensitivity to evidence that was neglected because of gender bias. Fourth, some philosophers have argued that non-cognitive values play a legitimate role in cases of inductive risk, namely cases in which scientists may wrongly assess scientific hypotheses (e.g. accepting a hypothesis that should be rejected) because of some uncertainty due to mixed results or disagreement on the reliability of methodologies. Mistakes can have consequences that can be morally or economically undesirable and non-cognitive values, some philosophers argue, provide the standards to evaluate and compare these possible consequences. However, little is known on how - specifically - non-cognitive values influence this evaluation. To address this issue, I have conducted an experimental study clarifying how personal features, political values, and specific aspects of a risk (e.g. the chance of incurring Type I vs. Type II errors) determine people’s reasoning about cases of inductive risk. On the basis of these results, I have discussed recent institutional calls for the need to align research agendas and technological development to citizens’ values, needs, and expectations. (shrink)

In addition to natural curiosity, science is characterized by a number of psychological processes and perceptions. Among the psychological features, scientific enquiry relates to uncovering—or discovering—aspects of a world perceived as hidden from humans. A speculative theoretical model is presented, suggesting the evolution of science reflects psychological repercussions of wearing clothes. Specifically, the natural world is perceived as hidden due to the presence of clothing. Three components of scientific enquiry may arise from clothing: detachment from sensual experience, a (...) perception that the world is veiled in mystery, and an intellectual desire to uncover the hidden structure of nature. Rather than beginning with the emergence of Homo sapiens, the proposed connection with clothing implies that psychological foundations for science began to develop during the last ice age, with the invention of complex clothes that fully covered the human body. After the end of the last ice age, elements of scientific thinking began to emerge in societies where clothing was worn routinely for psychosocial reasons, including modesty. Notably, a scientific attitude was essentially absent in hunter-gatherer communities where nakedness remained the norm. This novel perspective aims to advance the history and philosophy of science, revealing the emergence of science as a situated phenomenon contingent on humans being covered. (shrink)

"In preparing this remarkable book, Ernest Hook persuaded an eminent group of scientists, historians, sociologists and philosophers to focus on the problem: why are some discoveries rejected at a particular time but later seen to be valid? The interaction of these experts did not produce agreement on 'prematurity' in science but something more valuable: a collection of fascinating papers, many of them based on new research and analysis, which sometimes forced the author to revise a previously-held opinion. The (...) book should be enthusiastically welcomed by all readers who are interested in how science works."—Stephen G. Brush, co-author of Physics, The Human Adventure: From copernicus to Einstein and Beyond "Prematurity and Scientific Discovery contains interesting and insightful papers by numerous well-known scientists and scholars. It will be of wide interest, not only to science studies scholars but also to working scientists and to science-literate general readers."—Thomas Nickles, editor of Scientific Discovery, Logic, and Rationality. (shrink)

The article reports the results from the developmentof four data-driven discovery systems, operating inlinguistics. The first mimics the induction methods ofJohn Stuart Mill, the second performs componentialanalysis of kinship vocabularies, the third is ageneral multi-class discrimination program, and thefourth finds logical patterns in data. These systemsare briefly described and some arguments are offeredin favour of machine linguistic discovery. Thearguments refer to the strength of machines incomputationally complex tasks, the guaranteedconsistency of machine results, the portability ofmachine methods to new tasks and (...) domains, and thepotential machines provide for our gaining newinsights. (shrink)

The INBIOSA project brings together a group of experts across many disciplines who believe that science requires a revolutionary transformative step in order to address many of the vexing challenges presented by the world. It is INBIOSA’s purpose to enable the focused collaboration of an interdisciplinary community of original thinkers. This paper sets out the case for support for this effort. The focus of the transformative research program proposal is biology-centric. We admit that biology to date has been more (...) fact-oriented and less theoretical than physics. However, the key leverageable idea is that careful extension of the science of living systems can be more effectively applied to some of our most vexing modern problems than the prevailing scheme, derived from abstractions in physics. While these have some universal application and demonstrate computational advantages, they are not theoretically mandated for the living. A new set of mathematical abstractions derived from biology can now be similarly extended. This is made possible by leveraging new formal tools to understand abstraction and enable computability. [The latter has a much expanded meaning in our context from the one known and used in computer science and biology today, that is "by rote algorithmic means", since it is not known if a living system is computable in this sense (Mossio et al., 2009).] Two major challenges constitute the effort. The first challenge is to design an original general system of abstractions within the biological domain. The initial issue is descriptive leading to the explanatory. There has not yet been a serious formal examination of the abstractions of the biological domain. What is used today is an amalgam; much is inherited from physics (via the bridging abstractions of chemistry) and there are many new abstractions from advances in mathematics (incentivized by the need for more capable computational analyses). Interspersed are abstractions, concepts and underlying assumptions “native” to biology and distinct from the mechanical language of physics and computation as we know them. A pressing agenda should be to single out the most concrete and at the same time the most fundamental process-units in biology and to recruit them into the descriptive domain. Therefore, the first challenge is to build a coherent formal system of abstractions and operations that is truly native to living systems. Nothing will be thrown away, but many common methods will be philosophically recast, just as in physics relativity subsumed and reinterpreted Newtonian mechanics. -/- This step is required because we need a comprehensible, formal system to apply in many domains. Emphasis should be placed on the distinction between multi-perspective analysis and synthesis and on what could be the basic terms or tools needed. The second challenge is relatively simple: the actual application of this set of biology-centric ways and means to cross-disciplinary problems. In its early stages, this will seem to be a “new science”. This White Paper sets out the case of continuing support of Information and Communication Technology (ICT) for transformative research in biology and information processing centered on paradigm changes in the epistemological, ontological, mathematical and computational bases of the science of living systems. Today, curiously, living systems cannot be said to be anything more than dissipative structures organized internally by genetic information. There is not anything substantially different from abiotic systems other than the empirical nature of their robustness. We believe that there are other new and unique properties and patterns comprehensible at this bio-logical level. The report lays out a fundamental set of approaches to articulate these properties and patterns, and is composed as follows. -/- Sections 1 through 4 (preamble, introduction, motivation and major biomathematical problems) are incipient. Section 5 describes the issues affecting Integral Biomathics and Section 6 -- the aspects of the Grand Challenge we face with this project. Section 7 contemplates the effort to formalize a General Theory of Living Systems (GTLS) from what we have today. The goal is to have a formal system, equivalent to that which exists in the physics community. Here we define how to perceive the role of time in biology. Section 8 describes the initial efforts to apply this general theory of living systems in many domains, with special emphasis on crossdisciplinary problems and multiple domains spanning both “hard” and “soft” sciences. The expected result is a coherent collection of integrated mathematical techniques. Section 9 discusses the first two test cases, project proposals, of our approach. They are designed to demonstrate the ability of our approach to address “wicked problems” which span across physics, chemistry, biology, societies and societal dynamics. The solutions require integrated measurable results at multiple levels known as “grand challenges” to existing methods. Finally, Section 10 adheres to an appeal for action, advocating the necessity for further long-term support of the INBIOSA program. -/- The report is concluded with preliminary non-exclusive list of challenging research themes to address, as well as required administrative actions. The efforts described in the ten sections of this White Paper will proceed concurrently. Collectively, they describe a program that can be managed and measured as it progresses. (shrink)

Popper is well known for rejecting a logic of discovery, but he is only justified in rejecting the same type of logic of discovery that is denied by consequentialism. His own account of hypothesis generation, based on a natural selection analogy, involves an error-eliminative logic of discovery and the differences he admits between biological and conceptual evolution suggest an error-corrective logic of discovery. These types of logics of discovery are based on principles of plausibility that are used in the generation (...) as opposed to the preliminary evaluation of hypotheses. The normative relevance of these principles is grounded in the distinction between strategic and definitory rules. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Reviewed by:Against Method in Science and Religion: Recent Debates on Rationality and Theology by Josh ReevesWhitney A. BaumanAgainst Method in Science and Religion: Recent Debates on Rationality and Theology. Josh Reeves. London, UK: Routledge, 2019. 154 pp. $170.00 hard-cover; $54.95 paperback; $39.71 eBook.Josh Reeves has written a very accessible and well-argued book for those interested in the field known as “science and religion.” It is a (...) timely book that I would use in conversation with other works that are questioning the continued validity and usefulness of modern Western university disciplines. In a world that is marked by globalization and climate change, and one in which many histories, religions, cultures, and possible futures come into contact with and change one another, perhaps we need to rethink what we mean by both “science” and “religion.”The general argument of the book is that Western scholars of science and religion have, until very recently paid more attention to the philosophy of science rather than the history of science. As such, these scholars have participated in a form of “methodological fetishism” (9) and have leaned too heavily on the idea that the sciences participate in some sort of unified program. In particular, Reeves deals with three figures within theology and science (I think it is important to distinguish theology from religion more clearly than the author does), whose research programs seek to place the claims of theology on some type of equal footing with the claims of science.Nancey Murphy, for instance, applies Imre Lakatos’s idea of core and auxiliary hypotheses to theology (40). Murphy’s project is trying to show how theology can be scientific by using this methodology (49). Though recognizing that knowledge in both theology and science change over time, it is most often auxiliary hypotheses rather than the core hypotheses that need to be altered. In this way, scientific and theological programs can remain in continuity over time, rather than experiencing disjointed paradigm shifts.Alister McGrath opts, instead, for a type of “critical realism” (56). There is a real world pushing back against human ideas and concepts and science can give us valid information about that world, but we must critically analyze the data since no data is raw (59). Against some post-modern claims, McGrath still argues that ontology determines epistemology (61). Reeves argues that McGrath fails to analyze older, discarded theories in his reading of the development of various scientific discoveries, thereby paving over the historical knowledge from the sciences that we would now see as outdated. This serves [End Page 96] to support an illusion that there is some sort of “global realism” that connects all sciences in a common ground and narrative (68).Finally, J. Wentzel van Huyssteen starts from the idea that there is no global common ground and sets out to offer a post-foundational theology based upon post-foundational philosophies of science and epistemology (78). For van Huyssteen, rationality is intersubjective, embodied and emerges from eco-social contexts, and thus, he highlights the serious problem of projecting a unified, global rationality as a unified basis for the sciences (82). Instead, he constructs a trans-local rationality that takes into account the multiple perspectives making up what we think of as a unified understanding of reason (84). Reeves argues that while this may be a step along the way to a method for “theology and science,” it does not offer us a way to navigate differences between conflicting knowledge claims (93). I would suggest that this is precisely the point of a post-foundational project: there is no overarching value but rather common grounds must be gained through dialogues, conversations, and translations.After engaging with these three philosophical theologians, Reeves proceeds to the second part of the book, in which he more directly criticizes distinct concepts of “religion” and “science” historically. For instance, he describes the tendency of early historians of science and those in the field of “science and religion” to erase the religiosity of early figures such as Isaac Newton and Francis Bacon (107). These figures mixed theological ideas with what we might call magical ideas in order to further develop natural... (shrink)

The goals ofthis paper are to identify (in Section II) some general features of problem solving strategies in science, to discuss (in Section III) how Chomsky has employed two particularly popular discovery strategies in science, and to show (in Section IV) how these strategies inform Chomskyan linguistics. In Section IV I will discuss (1) how their employment in linguistics manifests features of scientific problem solving outlined in Section Il and (2) how an analysis in terms of those features (...) suggests a natural account for many controversial aspects 0fChomsky’s methods. I will specifically examine how this analysis bears on Chomsky’s claims concerning competence theories’ centrality in psychology and their psychological reality. Although no methodological considerations bar Chomsky from tinkering with our notion ofpsychology, competence theories mus! eventually offer some fruitful empirical connections with psycholinguistics and that part of mainstream cognitive psychology concerned with language study tojustify that tinkering. After twenty years of research such connections have proven rare enough to raise important doubts about thejustification ofChomsl·:y’s claims for the place of competence theory in cognitive psychology {and for the psychological reality of the mechanism it describes). Although I will argue (contra man) tf C}iom.rk_y’s critics) that his methods are unexceptionable, still [contra Chomsky) his theories have not proven sufficiently robust empirically to justify his strong claims concerning their position in cognitive psychology. (shrink)

It is widely acknowledged that metaphors are used in science. Great scientists, such as Darwin and Einstein, believed that the use of metaphors is vital to the development of scientific ideas. The history of science is full of examples of scientific metaphors as tools at the forefront of discoveries of new facts and new concepts.