Computational Philosophy

The prestige of an academic institution may be determined as a function of affiliations with other academic institutions. Using digital tools to data-scrape, data-mine, and perform network analysis on university websites, an approximation of numbers of academic affiliations may be measured. Especially observing the alma mater institutions of the faculty of employed institutions, these numbers show the relative employment of alumni and a proxy metric for the relative prestige of their degree-granting institutions. These affiliations can be charted and graphed to (...) determine the distributions of affiliations throughout an academic ecosystem from which we might draw conclusions about that system’s hierarchies and inequalities. Here we use anglophone PhD-granting philosophy departments as a case study for this methodology with tentative conclusions. (shrink)

Computers may help us to better understand (not just verify) arguments. In this article we defend this claim by showcasing the application of a new, computer-assisted interpretive method to an exemplary natural-language ar- gument with strong ties to metaphysics and religion: E. J. Lowe’s modern variant of St. Anselm’s ontological argument for the existence of God. Our new method, which we call computational hermeneutics, has been particularly conceived for use in interactive-automated proof assistants. It aims at shedding light on the (...) meanings of words and sentences by framing their inferential role in a given argument. By employing automated theorem reasoning technology within interactive proof assistants, we are able to drastically reduce (by several orders of magnitude) the time needed to test the logical validity of an argu- ment’s formalization. As a result, a new approach to logical analysis, inspired by Donald Davidson’s account of radical interpretation, has been enabled. In computational hermeneutics, the utilization of automated reasoning tools ef- fectively boosts our capacity to expose the assumptions we indirectly commit ourselves to every time we engage in rational argumentation and it fosters the explicitation and revision of our concepts and commitments. (shrink)

The Turing machine halting problem can be explained by several factors, including arithmetic logic irreversibility and memory erasure, which contribute to computational uncertainty due to information loss during computation. Essentially, this means that an algorithm can only preserve information about an input, rather than generate new information. This uncertainty arises from characteristics such as arithmetic logical irreversibility, Landauer's principle, and memory erasure, which ultimately lead to a loss of information and an increase in entropy. To measure this uncertainty and loss (...) of information, the concept of arithmetic logical entropy can be used. The Turing machine and its equivalent, general recursive functions can be understood through the λ calculus and the Turing/Church thesis. However, there are certain recursive functions that cannot be fully understood or predicted by other algorithms due to the loss of information during logical-arithmetic operations. In other words, the behaviour of these functions cannot be completely determined at every stage of the computation due to a lack of information in their definition. While there are some cases where the behaviour of recursive functions is highly predictable, the lack of information in most cases makes it impossible for algorithms to determine if a program will halt or not. This inability to predict the outcome of the computation is the essence of the halting problem of the Turing machine. Even in cases where more information is available about the program, it is still difficult to determine with certainty if the program will halt or not. This also highlights the importance of the Turing oracle machine, which introduces information from outside the computation to compensate for the lack of information and ultimately decide the result of the computation. (shrink)

Members of marginalized communities are often accused of being "too sensitive" when subjected to supposedly harmless acts of microaggression. This paper explores a simulated society consisting of marginalized and non-marginalized agents who interact and may, based on their individually held convictions, commit acts of microaggressions. Agents witnessing a microaggression might condone, ignore or condemn such microaggressions, thus potentially influencing a perpetrator's conviction. A prototype model has been implemented in NetLogo, and possible applications are briefly discussed.

Philosophers have long tried to understand scientific change in terms of a dynamics of revision within ‘theoretical frameworks,’ ‘disciplinary matrices,’ ‘scientific paradigms’ or ‘conceptual schemes.’ No-one, however, has made clear precisely how one might model such a conceptual scheme, nor what form change dynamics within such a structure could be expected to take. In this paper we take some first steps in applying network theory to the issue, modeling conceptual schemes as simple networks and the dynamics of change as cascades (...) on those networks. The results allow a new understanding of two traditional approaches—Popper and Kuhn—as well as introducing the intriguing prospect of viewing scientific change using the metaphor of selforganizing criticality. (shrink)

The transformative power of artificial intelligence (AI) is coming to philosophy—the only question is the degree to which philosophers will harness it. In this paper, we argue that the application of AI tools to philosophy could have an impact on the field comparable to the advent of writing, and that it is likely that philosophical progress will significantly increase as a consequence of AI. The role of philosophers in this story is not merely to use AI but also to help (...) develop it and theorize about it. In fact, we argue that philosophers have a prima facie obligation to spend significant effort in doing so, at least insofar as they should spend effort philosophizing. (shrink)

I address the worry that reflective equilibrium is too weak as an account of justification because it fails to let differing views converge. I take up informal aspects of convergence and operationalise them in a formal model of reflective equilibrium. This allows for exploration by the means of computer simulation. Findings show that the formal model does not yield unique outputs, but still boosts agreement. I conclude from this that reflective equilibrium is best seen as a pluralist account of justification (...) that cannot be accused of resulting in an “anything goes” relativism. (shrink)

I would like to thank Renia Gasparatou, Philip Goff, and Andreas Vrahimis for contributing to the book symposium on For and Against Scientism: Science, Methodology, and the Future of Philosophy (London: Rowman & Littlefield, 2022). I am grateful to James Collier for hosting this book symposium on the Social Epistemology Review and Reply Collective. In what follows, I will reply to Gasparatou and Vrahimis’s contributions to this book symposium.1 Before I do so, I will summarize what I take to be (...) their main arguments against my conception of scientism. Briefly, my conception of scientism runs along the weak and broad lines of epistemological scientism (Mizrahi 2022a, 12). More specifically, Weak Scientism is the view that scientific knowledge is the best knowledge (or some other epistemic good, such as justified belief) we have. Weak Scientism is a weaker version of epistemological scientism than Strong Scientism, which is the view that scientific knowledge is the only knowledge we have. According to Weak Scientism, while non-scientific disciplines do produce knowledge, scientific disciplines produce knowledge that is superior—both quantitatively (in terms of research output and research impact) and qualitatively (in terms of explanatory, predictive, and instrumental success)—to non-scientific knowledge (Mizrahi 2017, 354; 2022a, 6–7; 2023, 41). (shrink)

Mizrahi (2017a) advances an argument in support of Weak Scientism, which is the view that scientific knowledge is the best (but not the only) knowledge we have, according to which Weak Scientism follows from the premises that scientific knowledge is quantitatively and qualitatively better than non-scientific knowledge. In this paper, I develop a different argument for Weak Scientism. This latter argument for Weak Scientism proceeds from the premise that academic disciplines that make progress are superior to academic disciplines that do (...) not make progress. In other words, other things being equal, it is generally better for an academic discipline to make progress than to make little or no progress, given that an academic discipline that is making little or no progress is an academic discipline that is failing to achieve its epistemic goals. Now, if there is no question among academic philosophers that science makes progress, and significantly so, but there is an open question among academic philosophers as to whether academic philosophy makes progress (and if so, how much), then academic philosophers would have to agree that science is superior to academic philosophy in terms of making progress. I develop this argument in this paper and provide empirical evidence suggesting that the premises would be acceptable to academic philosophers. (shrink)

Drawing on the epistemology of logic literature on anti-exceptionalism about logic, we set out to investigate the following metaphilosophical questions empirically: Is philosophy special? Are its methods (dis)continuous with science? More specifically, we test the following metaphilosophical hypotheses empirically: philosophical deductivism, philosophical inductivism, and philosophical abductivism. Using indicator words to classify arguments by type (namely, deductive, inductive, and abductive arguments), we searched through a large corpus of philosophical texts mined from the JSTOR database (N = 435,703) to find patterns of (...) argumentation. The results of our quantitative, corpus-based study suggest that deductive arguments are significantly more common than abductive arguments and inductive arguments in philosophical texts overall, but they are gradually and steadily giving way to non-deductive (i.e. inductive and abductive) arguments in academic philosophy. (shrink)

Interactive theorem provers might seem particularly impractical in the history of philosophy. Journal articles in this discipline are generally not formalized. Interactive theorem provers involve a learning curve for which the payoffs might seem minimal. In this article I argue that interactive theorem provers have already demonstrated their potential as a useful tool for historians of philosophy; I do this by highlighting examples of work where this has already been done. Further, I argue that interactive theorem provers can continue to (...) be useful tools for historians of philosophy in the future; this claim is defended through a more conceptual analysis of what historians of philosophy do that identifies argument reconstruction as a core activity of such practitioners. It is then shown that interactive theorem provers can assist in this core practice by a description of what interactive theorem provers are and can do. If this is right, then computer verification for historians of philosophy is in the offing. (shrink)

With the powerful analyses and resources they enable, digital humanities tools have captivated researchers from many different fields who want to use them to study science. Digital tools, as well as funding agencies, research communities, and academic administrators, require researchers to think carefully about how they conceptualize, manage, and store data, and about what they plan to do with that data once a given project is over. The difficulties of developing strategies to address these problems can prevent new researchers from (...) sticking with digital tools and flummox even experienced researchers. To help overcome the data hurdle, we present five principles to help researchers, novice and experienced alike, conceptualize and plan for their data. We illustrate the use of those principles with two digital projects from the history of science, the Embryo Project and the Marine Biological Laboratory History Project, and their associated HPS Repository for data. The principles apply beyond the digital realm, so those who collect and manage data by more traditional means will also find them useful. (shrink)

Sallie McFague’s theological models construct a tensive relationship between conceptual structures and symbolic, metaphorical language to interpret the defining and elusive aspects of theological phenomena and loci. Computational models of language can extend and formalize the conceptual structures of theological models to develop computer-augmented interpretations of theological texts. Previously unclear is whether computational models can retain the tensive symbolism essential for theological investigation. I demonstrate affirmatively by constructing a computational topic model of the moral theology of Thomas Aquinas from Summa (...) Theologica (Second Part, in English translation) useful for interpreting not only the Thomistic text but also recent papal encyclicals. (shrink)

It is a common view among philosophers of science that theoretical virtues (also known as epistemic or cognitive values), such as simplicity and consistency, play an important role in scientific practice. In this article, I set out to study the role that theoretical virtues play in scientific practice empirically. I apply the methods of data science, such as text mining and corpus analysis, to study large corpora of scientific texts in order to uncover patterns of usage. These patterns of usage, (...) in turn, might shed some light on the role that theoretical virtues play in scientific practice. Overall, the results of this empirical study suggest that scientists invoke theoretical virtues explicitly, albeit rather infrequently, when they talk about models (less than 30%), theories (less than 20%), and hypotheses (less than 15%) in their published works. To the extent that they are mentioned in scientific publications, the results of this study suggest that accuracy, consistency, and simplicity are the theoretical virtues that scientists invoke more frequently than the other theoretical virtues tested in this study. Interestingly, however, depending on whether they talk about hypotheses, theories, or models, scientists may invoke one of those theoretical virtues more than the others. (shrink)

The term scientism is used in several ways. It is used to denote an epistemological thesis according to which science is the source of our knowledge about the world and ourselves. Relatedly, it is used to denote a methodological thesis according to which the methods of science are superior to the methods of non-scientific fields or areas of inquiry, or even used to put forward a metaphysical thesis that what exists is what science says exists. In recent decades, the term (...) scientism has acquired a derogatory meaning when it is used in defense of non-scientific ways of knowing. In particular, some philosophers level the charge of “scientism” against those (mostly scientists) who are dismissive of philosophy. Other philosophers, however, embrace scientism, or some variant thereof, and object to the pejorative use of the term scientism. This book critically examines the arguments for and against scientism of various kinds to answer the central question: does scientism pose an existential threat to philosophy, or should philosophy become more scientific? (shrink)

While the empirical evidence pointing to a gender gap in professional, academic philosophy in the English-speaking world is widely accepted, explanations of this gap are less so. In this paper, we aim to make a modest contribution to the literature on the gender gap in academic philosophy by taking a quantitative, corpus-based empirical approach. Since some philosophers have suggested that it may be the argumentative, “logic-chopping,” and “paradox-mongering” nature of academic philosophy that explains the underrepresentation of women in the discipline, (...) our research questions are the following: Do men and women philosophers make different types of arguments in their published works? If so, which ones and with what frequency? Using data mining and text analysis methods, we study a large corpus of philosophical texts mined from the JSTOR database in order to answer these questions empirically. Using indicator words to classify arguments by type, we search through our corpus to find patterns of argumentation. Overall, the results of our empirical study suggest that women philosophers make deductive, inductive, and abductive arguments in their published works just as much as male philosophers do, with no statistically significant differences in the proportions of those arguments relative to each philosopher’s body of work. (shrink)

In this paper, we set out to investigate the following question: if science relies heavily on induction, does philosophy of science rely heavily on induction as well? Using data mining and text analysis methods, we study a large corpus of philosophical texts mined from the JSTOR database (n = 14,199) in order to answer this question empirically. If philosophy of science relies heavily on induction, just as science supposedly does, then we would expect to find significantly more inductive arguments than (...) deductive arguments and abductive arguments in the published works of philosophers of science. Using indicator words to classify arguments by type (namely, deductive, inductive, and abductive arguments), we search through our corpus to find patterns of argumentation. Overall, the results of our study suggest that philosophers of science do rely on inductive inference. But induction may not be as foundational to philosophy of science as it is thought to be for science, given that philosophers of science make significantly more deductive arguments than inductive arguments. Interestingly, our results also suggest that philosophers of science do not rely on abductive arguments all that much, even though philosophers of science consider abduction to be a cornerstone of scientific methodology. (shrink)

This paper argues that to negate the ontological difference between the natural and the artificial, is not plausible; nor is the reduction of the natural to the artificial or vice versa possible. Except if one intends to empty the semantic content of the terms and notions: “natural” and “artificial.” Most philosophical discussions on Artificial Intelligence (AI) have always been in relation to the human person, especially as it relates to human intelligence, consciousness and/or mind in general. This paper, intends to (...) broaden the conversation, by discussing AI in relation to the notions of “nature” and the “artificial.” This intention is to more critically understand the artificiality in and of artificial intelligence. To achieve this, the notion of “nature” in Aristotle’s Philosophy of Nature, has been employed as an epistemological tool in interrogating the notion of the artificial and the objectives of the science and technology of Artificial Intelligence. (shrink)

-/- For all that digital methods—including network visualization, text analysis, and others—have begun to show extensive promise in philosophical contexts, a tension remains between two uses of those tools that have often been taken to be incompatible, or at least to engage in a kind of trade-off: the discovery of new hypotheses and the testing of already-formulated positions. This paper presents this basic distinction, then explores ways to resolve this tension with the help of two interdisciplinary case studies, taken from (...) preregistration in contemporary science and the debate over whig history in the history of science. These case studies, the paper argues, refocus our attention from a mutually exclusive testing/discovery binary to the relationship between our background data or philosophical views and the empirical generalizations that we might draw from the data. Finally, it develops a set of three challenges for philosophers and corresponding avenues for future work that will, it is hoped, allow us to better justify our use of these methods. (shrink)

(Editorial introduction to a special issue of Synthese.).

When people combine concepts these are often characterised as “hybrid”, “impossible”, or “humorous”. However, when simply considering them in terms of extensional logic, the novel concepts understood as a conjunctive concept will often lack meaning having an empty extension (consider “a tooth that is a chair”, “a pet flower”, etc.). Still, people use different strategies to produce new non-empty concepts: additive or integrative combination of features, alignment of features, instantiation, etc. All these strategies involve the ability to deal with conflicting (...) attributes and the creation of new (combinations of) properties. We here consider in particular the case where a Head concept has superior ‘asymmetric’ control over steering the resulting concept combination (or hybridisation) with a Modifier concept. Specifically, we propose a dialogical approach to concept combination and discuss an implementation based on axiom weakening, which models the cognitive and logical mechanics of this asymmetric form of hybridisation. (shrink)

This article created to address the current state of affairs, which has resulted in an insufficient progress and innovation system. The purpose of this overview article is to increase educate society's knowledge of how to use modern and innovative technologies based on need, cultural aspects, social context, and state context. As a result, I used secondary sources to assist readers understand how state actors and policies might best respond to society's aspirations to use and communicate through technology and information, as (...) well as innovation, in a fair and equitable approach. It might be either positive or negative. Modernization and innovation can primarily noticed constructively. It means that before bringing forward and totally researching [technology], we must analyse what we need, how we treat it, and why we use it. (shrink)

Symmetry in biological and physical systems is a product of self-organization driven by evolutionary processes, or mechanical systems under constraints. Symmetry-based feature extraction or representation by neural networks may unravel the most informative contents in large image databases. Despite significant achievements of artificial intelligence in recognition and classification of regular patterns, the problem of uncertainty remains a major challenge in ambiguous data. In this study, we present an artificial neural network that detects symmetry uncertainty states in human observers. To this (...) end, we exploit a neural network metric in the output of a biologically inspired Self- Organizing Map Quantization Error (SOM-QE). Shape pairs with perfect geometry mirror symmetry but a non-homogenous appearance, caused by local variations in hue, saturation, or lightness within and/or across the shapes in a given pair produce, as shown here, a longer choice response time (RT) for “yes” responses relative to symmetry. These data are consistently mirrored by the variations in the SOM-QE from unsupervised neural network analysis of the same stimulus images. The neural network metric is thus capable of detecting and scaling human symmetry uncertainty in response to patterns. Such capacity is tightly linked to the metric’s proven selectivity to local contrast and color variations in large and highly complex image data. (shrink)

The composition of a timeline depends on purpose, perspective, and scale – and of the very understanding of the word, the phenomenon referred to, and whether the focus is the idea or concept, an instance of an idea or a phenomenon, a process, or an event and so forth. The main function of timelines is to provide an overview over a long history, it is a kind of a mnemotechnic device or a particular kind of Knowledge Organization System (KOS).b The (...) entries in the timeline should be brief and indisputable. Therefore, timelines often identify the first occurrences rather than the most widespread or most qualified instances leaving the fuller and more complex, and possibly disputable story out. But even first occurrences are often difficult to establish. The first occurrence is most often only the first finding of an instance. Older instances may be found and competing definitions develop either within a field or in different fields. This is further complicated since the phenomena, their names, and their meanings may change over time. Former meanings may become redundant, or they must accommodate and coexist with new meanings. The time and place of the composition of the timeline are to be considered in interpreting the things listed. The following note will discuss these issues as they occur in the development of the notions of text, e-text and hypertext, and the origin of machine translation. (shrink)

Empirical philosophers of science aim to base their philosophical theories on observations of scientific practice. But since there is far too much science to observe it all, how can we form and test hypotheses about science that are sufficiently rigorous and broad in scope, while avoiding the pitfalls of bias and subjectivity in our methods? Part of the answer, we claim, lies in the computational tools of the digital humanities, which allow us to analyze large volumes of scientific literature. Here (...) we advocate for the use of these methods by addressing a number of large-scale, justificatory concerns—specifically, about the epistemic value of journal articles as evidence for what happens elsewhere in science, and about the ability of DH tools to extract this evidence. Far from ignoring the gap between scientific literature and the rest of scientific practice, effective use of DH tools requires critical reflection about these relationships. (shrink)

The aim of this paper is to contribute to the debate over the nature of scientific progress in philosophy of science by taking a quantitative, corpus-based approach. By employing the methods of data science and corpus linguistics, the following philosophical accounts of scientific progress are tested empirically: the semantic account of scientific progress, the epistemic account of scientific progress, and the noetic account of scientific progress. Overall, the results of this quantitative, corpus-based study lend some empirical support to the epistemic (...) and the noetic accounts over the semantic account of scientific progress, for they suggest that practicing scientists use the terms ‘knowledge’ and ‘understanding’ significantly more often than the term ‘truth’ when they talk about the aims or goals of scientific research in their published works. But the results do not favor the epistemic account over the noetic account, or vice versa, for they reveal no significant differences between the frequency with which practicing scientists use the terms ‘knowledge’ and ‘understanding’ when they talk about the aims or goals of scientific research in their published works. (shrink)

In a reply to Mizrahi (2019), Bryant (2020) raises several methodological concerns regarding my attempt to test hypotheses about the observation that academic philosophers tend to find “scientism” threatening empirically using quantitative, corpus based methods. Chief among her methodological concerns is that numbers of philosophical publications that mention “scientism” are a “poor proxy for scholarly sentiment” (Bryant 2020, 31). In reply, I conduct a sentiment analysis that is designed to find out whether academic philosophers have negative, positive, or neutral sentiments (...) toward “scientism.” The results of this analysis suggest that, for the most part, articles on “scientism” written by academic philosophers tend to contain mostly negative rather than positive (or neutral) sentiments about “scientism.”. (shrink)

Philosophy is often divided into two traditions: analytic and continental philosophy. Characterizing the analytic-continental divide, however, is no easy task. Some philosophers explain the divide in terms of the place of argument in these traditions. This raises the following questions: Is analytic philosophy rife with arguments while continental philosophy is devoid of arguments? Or can different types of arguments be found in analytic and continental philosophy? This paper presents the results of an empirical study of a large corpus of philosophical (...) texts mined from the JSTOR database (n = 53,260) designed to find patterns of argumentation by type. Overall, the results suggest that there are no significant differences between the types of arguments advanced in analytic and continental philosophy journal articles. The findings, therefore, provide no empirical support to the hypothesis that the divide between analytic and continental philosophy has to do with the place of argument in these traditions. (shrink)

Arguments for extended cognition and the extended mind are typically directed at human-centred forms of cognitive extension—forms of cognitive extension in which the cognitive/mental states/processes of a given human individual are subject to a form of extended or wide realization. The same is true of debates and discussions pertaining to the possibility of Web-extended minds and Internet-based forms of cognitive extension. In this case, the focus of attention concerns the extent to which the informational and technological elements of the online (...) environment form part of the machinery of the (individual) human mind. In this paper, we direct attention to a somewhat different form of cognitive extension. In particular, we suggest that the Web allows human individuals to be incorporated into the computational/cognitive routines of online systems. These forms of computational/cognitive extension highlight the potential of the Web and Internet to support bidirectional forms of computational/cognitive incorporation. The analysis of such bidirectional forms of incorporation broadens the scope of philosophical debates in this area, with potentially important implications for our understanding of the foundational notions of extended cognition and the extended mind. (shrink)

While scientific inquiry crucially relies on the extraction of patterns from data, we still have a far from perfect understanding of the metaphysics of patterns—and, in particular, of what makes a pattern real. In this paper we derive a criterion of real-patternhood from the notion of conditional Kolmogorov complexity. The resulting account belongs to the philosophical tradition, initiated by Dennett :27–51, 1991), that links real-patternhood to data compressibility, but is simpler and formally more perspicuous than other proposals previously defended in (...) the literature. It also successfully enforces a non-redundancy principle, suggested by Ladyman and Ross, that aims to exclude from real-patternhood those patterns that can be ignored without loss of information about the target dataset, and which their own account fails to enforce. (shrink)

This study shows firstly that it is necessary to characterize a computer simulation at a finer level than that of formal models: that of symbols and their various modes of reference. This is particularly true for those that integrate models and formalisms of a heterogeneous nature. This study then examines the ontological causes that, consequently, could explain their epistemic success. It is argued that they can be conveniently explained if one adopts a conception of nature that is both discontinuous and (...) finite. The latter thesis supports a naturalistic metaphysical position by invalidating, at its root, the argument made by speculative materialism against a scientific approach to the physical world that proceeds, like simulations, by finite representations and operations. (shrink)

This paper proposes a sender-receiver model to explain two large-scale patterns observed in natural languages: Zipf’s inverse power law relating the frequency of word use and word rank, and the negative correlation between the frequency of word use and rate of lexical change. Computer simulations show that the model recreates Zipf’s inverse power law and the negative correlation between signal frequency and rate of change, provided that agents balance the rates with which they invent new signals and forget old ones. (...) Results are robust across a wide range of parameter values and structural assumptions, such as different forgetting rules and forgetting rates. Analysis of the model further suggests that Zipf’s law relating word frequency and rank arises because of language-external factors and that frequent signals change less because frequent signals are less subject to drift than rare ones. The paper concludes with some brief considerations on model-based and data-driven approaches in philosophy. (shrink)

The principle of self-organization has acquired a fundamental significance in the newly emerging field of computational philosophy. Self-organizing systems have been described in various domains in science and philosophy including physics, neuroscience, biology and medicine, ecology, and sociology. While system architecture and their general purpose may depend on domain-specific concepts and definitions, there are (at least) seven key properties of self-organization clearly identified in brain systems: 1) modular connectivity, 2) unsupervised learning, 3) adaptive ability, 4) functional resiliency, 5) functional plasticity, (...) 6) from-local-to-global functional organization, and 7) dynamic system growth. These are defined here in the light of insight from neurobiology, cognitive neuroscience and Adaptive Resonance Theory (ART), and physics to show that self-organization achieves stability and functional plasticity while minimizing structural system complexity. A specific example informed by empirical research is discussed to illustrate how modularity, adaptive learning, and dynamic network growth enable stable yet plastic somatosensory representation for human grip force control. Implications for the design of “strong” artificial intelligence in robotics are brought forward. (shrink)

Epistemic justifications for democracy have been offered in terms of two different aspects of decision-making: voting and deliberation, or ‘votes’ and ‘talk.’ The Condorcet Jury Theorem is appealed to as a justification in terms votes, and the Hong-Page “Diversity Trumps Ability” result is appealed to as a justification in terms of deliberation. Both of these, however, are most plausibly construed as models of direct democracy, with full and direct participation across the population. In this paper, we explore how these results (...) hold up if we vary the model so as to reflect the more familiar democratic structure of a representative hierarchy. We first recount extant analytic work that shows that representation inevitably weakens the voting results of the Condorcet Jury Theorem, but we question the ability of that result to shine light on real representative systems. We then show that, when we move from votes to talk, as modeled in Hong-Page, representation holds its own and even has a slight edge. (shrink)

Discussions on the alleged methodological specificity of social knowledge are fueled to not the least extent by a kind of retarded position of the latter against technological advancements of natural and information science based on exact methods and formal or quantitative languages. It is more or less obvious that applicability of exact scientific methods to social disciplines is highly dependent on a chosen conception of social reality, i. e., on social ontology. In the article, the author critically approaches the ontological (...) views of Tony Lawson and proposes a computational view on social ontology that is supposed to eliminate some internal contradictions of Lawson's realist conception. (shrink)

In this paper, I propose that applying the methods of data science to “the problem of whether mathematical explanations occur within mathematics itself” (Mancosu 2018) might be a fruitful way to shed new light on the problem. By carefully selecting indicator words for explanation and justification, and then systematically searching for these indicators in databases of scholarly works in mathematics, we can get an idea of how mathematicians use these terms in mathematical practice and with what frequency. The results of (...) this empirical study suggest that mathematical explanations do occur in research articles published in mathematics journals, as indicated by the occurrence of explanation indicators. When compared with the use of justification indicators, however, the data suggest that justifications occur much more frequently than explanations in scholarly mathematical practice. The results also suggest that justificatory proofs occur much more frequently than explanatory proofs, thus suggesting that proof may be playing a larger justificatory role than an explanatory role in scholarly mathematical practice. (shrink)

It is generally accepted among philosophers of science that hypothesis testing is a key methodological feature of science. As far as philosophical theories of confirmation are con...

Turner argues that computer programs must have purposes, that implementation is not a kind of semantics, and that computers might need to understand what they do. I respectfully disagree: Computer programs need not have purposes, implementation is a kind of semantic interpretation, and neither human computers nor computing machines need to understand what they do.

This article aims to study the relationship between today’s canonical and noncanonical authors in the domain of early modern natural philosophy through the lens of social network analysis. By studying a massive corpus of letters (Electronic Enlightenment project), we examine the structural relationship between several of today’s canonical authors in natural philosophy and noncanonical women philosophers operating in the same network. We demonstrate the structure of this network and its effects on noncanonical authors. By modeling the case of women philosophers, (...) we show that our model can be used to identify further noncanonical authors who had similar profiles. (shrink)

How can we best reconstruct the origin of a notion, its development, and possible spread to multiple fields? We present a pilot study on the spread of the notion of conceptual scheme. Though the notion is philosophically important, its origin, development, and spread are unclear. Several purely qualitative and competing historical hypotheses have been offered, which rely on disconnected disciplinary traditions, and have never been tested all at once in a single comprehensive investigation fitting the scope of its subject matter. (...) As a step toward such an investigation, we trace the use of the bigram “conceptual scheme” in about 42,000 US journal articles in social sciences from 1888-1959 by using a novel method combining a quantitative procedure aided by basic computational techniques with qualitative elements informed by Betti and van den Berg (2014)’s ‘model approach to the history of ideas’. (shrink)

The quantization error in a fixed-size Self-Organizing Map (SOM) with unsupervised winner-take-all learning has previously been used successfully to detect, in minimal computation time, highly meaningful changes across images in medical time series and in time series of satellite images. Here, the functional properties of the quantization error in SOM are explored further to show that the metric is capable of reliably discriminating between the finest differences in local contrast intensities and contrast signs. While this capability of the QE is (...) akin to functional characteristics of a specific class of retinal ganglion cells (the so-called Y-cells) in the visual systems of the primate and the cat, the sensitivity of the QE surpasses the capacity limits of human visual detection. Here, the quantization error in the SOM is found to reliably signal changes in contrast or colour when contrast information is removed from or added to the image, but not when the amount and relative weight of contrast information is constant and only the local spatial position of contrast elements in the pattern changes. While the RGB Mean reflects coarser changes in colour or contrast well enough, the SOM-QE is shown to outperform the RGB Mean in the detection of single-pixel changes in images with up to five million pixels. This could have important implications in the context of unsupervised image learning and computational building block approaches to large sets of image data (big data). (shrink)

What structure of scientific communication and cooperation, between what kinds of investigators, is best positioned to lead us to the truth? Against an outline of standard philosophical characteristics and a recent turn to social epistemology, this paper surveys highlights within two strands of computational philosophy of science that attempt to work toward an answer to this question. Both strands emerge from abstract rational choice theory and the analytic tradition in philosophy of science rather than postmodern sociology of science. The first (...) strand of computational research models the effect of communicative networks within groups, with conclusions regarding the potential benefit of limited communication. The second strand models the potential benefits of cognitive diversity within groups. Examples from each strand of research are used in analyzing what makes modeling of this sort both promising and distinctly philosophical, but are also used to emphasize possibilities for failure and inherent limitations as well. (shrink)

The Hong and Page ‘diversity trumps ability’ result has been used to argue for the more general claim that a diverse set of agents is epistemically superior to a comparable group of experts. Here we extend Hong and Page’s model to landscapes of different degrees of randomness and demonstrate the sensitivity of the ‘diversity trumps ability’ result. This analysis offers a more nuanced picture of how diversity, ability, and expertise may relate. Although models of this sort can indeed be suggestive (...) for diversity policies, we advise against interpreting such results overly broadly. (shrink)

Computational neuroscience attributes coloured areas and other perceptual qualia to calculations that are realizable in multiple cellular forms. This faces serious issues in explaining how the various qualia arise and how they bind to form overall perceptions. Qualia may instead be neuroelectrical. Growing evidence indicates that perceptions correlate with neuroelectrical activity spotted by locally activated EEGs, the different qualia correlate with the different electrochemistries of unique detector cells, a unified neural-electromagnetic field binds this activity to form overall perceptions, and this (...) field interacts with sensory circuits to help attentively guide perception. The coloured areas in images may thus be seated in the electrochemistry of unique cells, while constancy mechanisms and other multiply realizable computations just help refine these images behind the scenes. This theory is ultimately testable. (shrink)

This article aims to describe the last 10 years of the collaborative scientific endeavors on polarization in particular and collective problem-solving in general by our multidisciplinary research team. We describe the team’s disciplinary composition—social psychology, political science, social philosophy/epistemology, and complex systems science— highlighting the shared and unique skill sets of our group members and how each discipline contributes to studying polarization and collective problem-solving. With an eye to the literature on team dynamics, we describe team logistics and processes that (...) we believe make our multidisciplinary team persistent and productive. We emphasize challenges and difficulties caused by disciplinary differences in terms of terminology, units/levels of analysis, methodology, and theoretical assumptions. We then explain how work disambiguating the concepts of polarization and developing an integrative theoretical and methodological framework with complex systems perspectives has helped us overcome these challenges. We summarize the major findings that our research has produced over the past decade, and describe our current research and future directions. Last, we discuss lessons we have learned, including difficulties in a “three models” project and how we addressed them, with suggestions for effective multidisciplinary team research. (shrink)

It is often said that ‘every logical truth is obvious’ (Quine 1970: 82), that the ‘axioms and rules of logic are true in an obvious way’ (Murawski 2014: 87), or that ‘logic is a theory of the obvious’ (Sher 1999: 207). In this chapter, I set out to test empirically how the idea that logic is obvious is reflected in the scholarly work of logicians and philosophers of logic. My approach is data-driven. That is to say, I propose that systematically (...) searching for patterns of usage in databases of scholarly works, such as JSTOR, can provide new insights into the ways in which the idea that logic is obvious is reflected in logical and philosophical practice, i.e., in the arguments that logicians and philosophers of logic actually make in their published work. (shrink)

We motivate a picture of social epistemology that sees forgetting as subject to epistemic evaluation. Using computer simulations of a simple agent-based model, we show that how agents forget can have as large an impact on group epistemic outcomes as how they share information. But, how we forget, unlike how we form beliefs, isn’t typically taken to be the sort of thing that can be epistemically rational or justified. We consider what we take to be the most promising argument for (...) this claim and find it lacking. We conclude that understanding how agents forget should be as central to social epistemology as understanding how agents form beliefs and share information with others. (shrink)