Models are the coin of the realm in current philosophy of science, as they are in science itself, having replaced laws and theories as the primary strategy. Logical Positivism tried to erase the older neo-Kantian distinction between ideal constructions and reality. It returns in the case of models. Nowak’s concept of idealization pro- vided an alternative account of this issue. It construed model application as concretizations of hypotheses which improve by accounting for exceptions. This appears to account (...) for physical law. But it raises the problem of uniqueness: is the result unique, as physical law should be? Neo-Kantianism failed this test. Its solutions were circular justifications for claims of uniqueness. Nowak inherited the problem without resolving it. (shrink)

Fundamental knowledge endures deep conceptual crisis manifested in total crisis of understanding, crisis of interpretation and representation, loss of certainty, troubles with physics, crisis of methodology. Crisis of understanding in fundamental science generates deep crisis of understanding in global society. What way should we choose for overcoming total crisis of understanding in fundamental science? It should be the way of metaphysical construction of new comprehensive model of ideality on the basis of the "modified ontology". Result of quarter-century wanderings: sum of (...) ideas, concepts and eidoses, new understanding of space, time, consciousness. (shrink)

Batterman and Rice ([2014]) argue that minimal models possess explanatory power that cannot be captured by what they call ‘common features’ approaches to explanation. Minimal models are explanatory, according to Batterman and Rice, not in virtue of accurately representing relevant features, but in virtue of answering three questions that provide a ‘story about why large classes of features are irrelevant to the explanandum phenomenon’ ([2014], p. 356). In this article, I argue, first, that a method (the renormalization group) (...) they propose to answer the three questions cannot answer them, at least not by itself. Second, I argue that answers to the three questions are unnecessary to account for the explanatoriness of their minimal models. Finally, I argue that a common features account, what I call the ‘generalized ontic conception of explanation’, can capture the explanatoriness of minimal models. (shrink)

Detailed examinations of scientific practice have revealed that the use of idealized models in the sciences is pervasive. These models play a central role in not only the investigation and prediction of phenomena, but in their received scientific explanations as well. This has led philosophers of science to begin revising the traditional philosophical accounts of scientific explanation in order to make sense of this practice. These new model-based accounts of scientific explanation, however, raise a number of key questions: (...) Can the fictions and falsehoods inherent in the modeling practice do real explanatory work? Do some highly abstract and mathematical models exhibit a noncausal form of scientific explanation? How can one distinguish an exploratory "how-possibly" model explanation from a genuine "how-actually" model explanation? Do modelers face tradeoffs such that a model that is optimized for yielding explanatory insight, for example, might fail to be the most predictively accurate, and vice versa? This chapter explores the various answers that have been given to these questions. (shrink)

The claim defended in the paper is that the mechanistic account of explanation can easily embrace idealization in big-scale brain simulations, and that only causally relevant detail should be present in explanatory models. The claim is illustrated with two methodologically different models: Blue Brain, used for particular simulations of the cortical column in hybrid models, and Eliasmith’s SPAUN model that is both biologically realistic and able to explain eight different tasks. By drawing on the mechanistic theory (...) of computational explanation, I argue that large-scale simulations require that the explanandum phenomenon is identified; otherwise, the explanatory value of such explanations is difficult to establish, and testing the model empirically by comparing its behavior with the explanandum remains practically impossible. The completeness of the explanation, and hence of the explanatory value of the explanatory model, is to be assessed vis-à-vis the explanandum phenomenon, which is not to be conflated with raw observational data and may be idealized. I argue that idealizations, which include building models of a single phenomenon displayed by multi-functional mechanisms, lumping together multiple factors in a single causal variable, simplifying the causal structure of the mechanisms, and multi-model integration, are indispensable for complex systems such as brains; otherwise, the model may be as complex as the explanandum phenomenon, which would make it prone to so-called Bonini paradox. I conclude by enumerating dimensions of empirical validation of explanatory models according to new mechanism, which are given in a form of a “checklist” for a modeler. (shrink)

Many have expected that understanding the evolution of norms should, in some way, bear on our first-order normative outlook: How norms evolve should shape which norms we accept. But recent philosophy has not done much to shore up this expectation. Most existing discussions of evolution and norms either jump headlong into the is/ought gap or else target meta-ethical issues, such as the objectivity of norms. My aim in this paper is to sketch a different way in which evolutionary considerations can (...) feed into normative thinking—focusing on stability. I will discuss two forms of argument that utilize information about social stability drawn from evolutionary models, and employs it to assess claims in political philosophy. One such argument treats stability as feature of social states that may be taken into account alongside other features. The other uses stability as a constraint on the realization of social ideals, via a version of the ought-implies-can maxim. These forms of argument are not new; indeed they have a history going back at least to early modern philosophy. But their marriage with evolutionary information is relatively recent, has a significantly novel character, and has received little attention in recent moral and political philosophy. (shrink)

Domain extension in mathematics occurs whenever a given mathematical domain is augmented so as to include new elements. Manders argues that the advantages of important cases of domain extension are captured by the model-theoretic notions of existential closure and model completion. In the specific case of domain extension via ideal elements, I argue, Manders’s proposed explanation does not suffice. I then develop and formalize a different approach to domain extension based on Dedekind’s Habilitationsrede, to which Manders’s account is compared. I (...) conclude with an examination of three possible stances towards extensions via ideal elements. (shrink)

In a recent special issue dedicated to Dani Rodrik’s (2015) influential monograph Economics Rules, Grüne-Yanoff and Marchionni (2018) raise a potentially damning problem for Rodrik’s suggestion that progress in economics should be understood and measured laterally, by a continuous expansion of new models. They argue that this could lead to an “embarrassment of riches”, i.e. the rapid expansion of our model library to such an extent that we become unable to choose between the available models, and thus needs (...) to be solved to make ‘model pluralism’ viable. Drawing on Veit’s (2019a) ‘model pluralism’ account, this paper argues that model pluralism as a thesis about the relationship between science and nature undermines the very idea of a general model selection framework for policy making. (shrink)

-/- This essay discusses the relation between ideal theory and two forms of political moralism identified by Bernard Williams, structural and enactment views. It argues that ideal theory, at least in the sense Rawls used that term, only makes sense for structural forms of moralism. These theories see their task as describing the constraints that properly apply to political agents and institutions. As a result, they are primarily concerned with norms that govern action. In contrast, many critiques of ideal theory (...) are structured and motivated by their commitment to an enactment model of political theorizing. This instead sees political agents and institutions as instruments for producing or promoting better states of affairs. Enactment models treat the evaluations that rank different states of affairs as justificatorily basic, rather than norms governing action on which structural models focus. This reveals an important feature of debates about ideal theory. Whether ideal theory is capable of appropriately guiding action will depend on what the criteria for appropriately guiding action are, about which different theorists have importantly different views. For example, some popular strategies for defending ideal theory fail, while it may be much less clear that some alternatives to ideal theory can provide action guidance than their advocates claim. (shrink)

Any computer can create a model of reality. The hypothesis that quantum computer can generate such a model designated as quantum, which coincides with the modeled reality, is discussed. Its reasons are the theorems about the absence of “hidden variables” in quantum mechanics. The quantum modeling requires the axiom of choice. The following conclusions are deduced from the hypothesis. A quantum model unlike a classical model can coincide with reality. Reality can be interpreted as a quantum computer. The physical processes (...) represent computations of the quantum computer. Quantum information is the real fundament of the world. The conception of quantum computer unifies physics and mathematics and thus the material and the ideal world. Quantum computer is a non-Turing machine in principle. Any quantum computing can be interpreted as an infinite classical computational process of a Turing machine. Quantum computer introduces the notion of “actually infinite computational process”. The discussed hypothesis is consistent with all quantum mechanics. The conclusions address a form of neo-Pythagoreanism: Unifying the mathematical and physical, quantum computer is situated in an intermediate domain of their mutual transformation. (shrink)

This paper is a review of Suarez, M. (ed.) Fictions in Science (Routledge).

Scientific models typically contain idealizations, or assumptions that are known not to be true. Philosophers have long questioned the nature of idealizations: Are they heuristic tools that will be abandoned? Or rather fictional representations of reality? And how can we reconcile them with realism about knowledge of nature? Immanuel Kant developed an account of scientific investigation that can inspire a new approach to the contemporary debate. Kant argued that scientific investigation is possible only if guided by ideal assumptions—what he (...) calls “regulative ideas”. These ideas are not true of objects of nature, and yet they are not heuristic tools or fictional represen- tations. They are necessary rules governing the construction and assessment of scientific explanations. In this paper, I suggest that some idealizations can be interpreted as having necessary regulative value and as being compatible with scientific realism. I first analyze the puzzle of the nature of idealization and present the main approaches to this topic in the literature. Second, I reconsider the puzzle vis-a-vis a restricted, Kantian definition of idealization and a novel characterization of the relation between idealization and truth. Finally, I discuss in detail an example of idealization (the Hardy-Weinberg equilibrium) along the suggested Kantian lines. (shrink)

This paper introduces and defends an account of model-based science that I dub model pluralism. I argue that despite a growing awareness in the philosophy of science literature of the multiplicity, diversity, and richness of models and modeling practices, more radical conclusions follow from this recognition than have previously been inferred. Going against the tendency within the literature to generalize from single models, I explicate and defend the following two core theses: any successful analysis of models must (...) target sets of models, their multiplicity of functions within science, and their scientific context and history and for almost any aspect x of phenomenon y, scientists require multiple models to achieve scientific goal z. (shrink)

Phylogenetic models traditionally represent the history of life as having a strictly-branching tree structure. However, it is becoming increasingly clear that the history of life is often not strictly-branching; lateral gene transfer, endosymbiosis, and hybridization, for example, can all produce lateral branching events. There is thus motivation to allow phylogenetic models to have a reticulate structure. One proposal involves the reconciliation of genealogical discordance. Briefly, this method uses patterns of disagreement – discordance – between trees of different genes (...) to add lateral branching events to phylogenetic trees of taxa, and to estimate the most likely cause of these events. I use this practice to argue for: (1) a need for expanded accounts of multiple-models idealization, (2) a distinction between automatic and manual de-idealization, and (3) recognition that idealization may serve the meso-level aims of science in a different way than hitherto acknowledged. (shrink)

The linear programming method is one of the important methods of operations research that has been used to address many practical issues and provided optimal solutions for many institutions and companies, which helped decision makers make ideal decisions through which companies and institutions achieved maximum profit, but these solutions remain ideal and appropriate in If the conditions surrounding the work environment are stable, because any change in the data provided will affect the optimal solution and to avoid losses and achieve (...) maximum profit, we have, in previous research, reformulated the linear models using the concepts of neutrosophic science, the science that takes into account the instability of conditions and fluctuations in the work environment and leaves nothing to chance. While taking data, neutrosophic values carry some indeterminacy, giving a margin of freedom to decision makers. In another research, we reformulated one of the most important methods used to solve linear models, which is the simplex method, using the concepts of this science, and as a continuation of what we did in the previous two researches, we will reformulate in this research. The graphical method for solving linear models using the concepts of neutrosophics. We will also shed light on a case that is rarely mentioned in most operations research references, which is that when the difference between the number of unknowns and the number of constraints is equal to one, two, or three, we can also find the optimal solution graphically for some linear models. This is done by taking advantage of the conditions of non-negativity that linear models have, and we will explain this through an example in which the difference is equal to two. Also, through examples, we will explain the difference between using classical values and neutrosophic values and the extent of this’s impact on the optimal solution. (shrink)

Recent methodological debates regarding the place of feasibility considerations in normative political theory are hindered for want of a rigorous model of the feasibility frontier. To address this shortfall, I present an analysis of feasibility that generalizes the economic concept of a production possibility frontier and then develop a rigorous model of the feasibility frontier using the familiar possible worlds technology. I then show that this model has significant methodological implications for political philosophy. On the Target View, a political ideal (...) presents a long-term goal for morally progressive reform efforts and, thus, serves as an important reference point for our specification of normative political principles. I use the model to show that we can- not reasonably expect that adopting political ideals as long-term reform objectives will guide us toward the realization of morally optimal feasible states of affairs. I conclude by proposing that political philosophers turn their attention to the analysis of actual social failures rather than political ideals. (shrink)

The majority of analyses investigating the professionalisation of scientific domains tend to assume the linear and general features of this transformation. These studies focus on the shift from a non-professionalised state to a professionalised state. This dual approach, however, crucially lacks some other aspects of the process of professionalisation. This issue is discussed within the context of the growth of prehistoric archaeology in France from the 1940s, by observing scientific societies, national research organisations and their social networks. Looking at the (...) scale of Georges Laplace’s career and that of his research group, which studied the typologie analytique method, this article demonstrates the benefits of a ternary model which also encompasses the modes of refusal of professionalisation. (shrink)

Ecological neutral theory has been controversial as an alternative to niche theory for explaining community structure. Neutral theory, which explains community structure in terms of ecological drift, is frequently charged with being unrealistic, but commentators have usually not provided an account of theory or model realism. In this paper, I propose a framework for comparing the “realism” or accuracy of alternative theories within a domain with respect to the extent to which the theories abstract and idealize. Using this framework I (...) argue, contrary to most previous commentators, that neutral and niche theories are similarly realistic. Realism cannot provide a basis for accepting or rejecting either type of theory; instead, community ecologists should continue working with a plurality of models. While theoretical unification may become possible, we should treat a plurality of complementary, partial models as the expected situation within community ecology. (shrink)

This article shows how the MISS account of models—as isolations and surrogate systems—accommodates and elaborates Sugden’s account of models as credible worlds and Hausman’s account of models as explorations. Theoretical models typically isolate by means of idealization, and they are representatives of some target system, which prompts issues of resemblance between the two to arise. Models as representations are constrained both ontologically (by their targets) and pragmatically (by the purposes and audiences of the modeller), (...) and these relations are coordinated by a model commentary. Surrogate models are often about single mechanisms. They are distinguishable from substitute models, which are examined without any concern about their connections with the target. Models as credible worlds are surrogate models that are believed to provide access to their targets on account of their credibility (of which a few senses are distinguished). (shrink)

In this paper we present a new framework of idealization in biology. We characterize idealizations as a network of counterfactual and hypothetical conditionals that can exhibit different “degrees of contingency”. We use this idea to say that, in departing more or less from the actual world, idealizations can serve numerous epistemic, methodological or heuristic purposes within scientific research. We defend that, in part, this structure explains why idealizations, despite being deformations of reality, are so successful in scientific practice. For (...) illustrative purposes, we provide an example from population genetics, the Wright-Fisher Model. (shrink)

The debate on ideal theory focuses mainly on whether it can provide a long-term target and a metric for assessing the justice of different institutional arrangements in non-ideal theory. Both critics and defenders of ideal theory typically overlook the role it plays in a model of fairness that can restrict the range of permissible arrangements under non-ideal conditions. In this paper, I explain ideal theory’s fairness role and its part in ensuring an institutional structure that benefits everyone in a society. (...) Critics of ideal theory therefore cannot reject it as simply useless. But I consider how they can question the attractiveness of an ideal-theory-based fairness constraint on non-ideal theory. (shrink)

Inferentialists about scientific representation hold that an apparatus’s representing a target system consists in the apparatus allowing “surrogative inferences” about the target. I argue that a serious problem for inferentialism arises from the fact that many scientific theories and models contain internal inconsistencies. Inferentialism, left unamended, implies that inconsistent scientific models have unlimited representational power, since an inconsistency permits any conclusion to be inferred. I consider a number of ways that inferentialists can respond to this challenge before suggesting (...) my own solution. I develop an analogy to exploitable glitches in a game. Even though inconsistent representational apparatuses may in some sense allow for contradictions to be generated within them, doing so violates the intended function of the apparatus’s parts and hence violates representational “gameplay.”. (shrink)

Maps and mapping raise questions about models and modeling and in science. This chapter archives map discourse in the founding generation of philosophers of science (e.g., Rudolf Carnap, Nelson Goodman, Thomas Kuhn, and Stephen Toulmin) and in the subsequent generation (e.g., Philip Kitcher, Helen Longino, and Bas van Fraassen). In focusing on these two original framing generations of philosophy of science, I intend to remove us from the heat of contemporary discussions of abstraction, representation, and practice of science and (...) thereby see in a more distant and neutral light the many productive ways in which maps can stand in analytically for scientific theories and models. The chapter concludes by complementing the map analogy – i.e., a scientific theory is a map of the world – with a model analogy, viz., a scientific model is a vehicle for understanding. (shrink)

Leibniz frequently argued that reasons are to be weighed against each other as in a pair of scales, as Professor Marcelo Dascal has shown in his article "The Balance of Reason." In this kind of weighing it is not necessary to reach demonstrative certainty – one need only judge whether the reasons weigh more on behalf of one or the other option However, a different kind of account about rational decision-making can be found in some of Leibniz's writings. In his (...) article "Was Leibniz's Deity an Akrates?" Professor Jaakko Hintikka has argued that Leibniz developed a new vectorial model for rational decisions which is better suited to complicated decisions, where values are complementary to each other. This model, related closely to his work in metaphysics and the philosophy of mind, is a heuristic device which helps in finding rational combinations - and in an ideal case an optimum - between plural inclinations to the good. I shall argue that Leibniz applies more or less implicitly both of these models in his practical rationality. In simple situations he applied the pair of scales model and in more complicated situations he applied the vectorial model. (shrink)

According to Steven Nadler's novel interpretation of Spinoza's much discussed ‘free man’, the free man is not an unattainable ideal. On this reading, the free man represents an ideal condition not because he is passionless, as has often been claimed, but because even though he experiences passions, he ‘never lets those passions determine his actions’. In this paper, I argue that Nadler's interpretation is incorrect in taking the model of the free man to be an attainable ideal within our reach. (...) Furthermore, I show that Spinoza's moral philosophy has room for another ideal yet attainable condition, which is represented by the wise man. On my reading, becoming a wise man consists not in surmounting human bondage, but in understanding ourselves as finite expressions of God's power and, thereby, coming to terms with the ineliminability of bondage for us due to our very human or modal condition in the Spinozistic universe. (shrink)

Knill, Kersten, & Mamassian (Chapter 6) provide an interesting discussion of how the Bayesian formulation can be used to help investigate human vision. In their view, computational theories can be based on an ideal observer that uses Bayesian inference to make optimal use of available information. Four factors are important here: the image information used, the output structures estimated, the priors assumed (i.e., knowledge about the structure of the world), and the likelihood function used (i.e., knowledge about the projection of (...) the world onto the sensors). Knill & Kersten argue that such a framework not only helps analyze a perceptual task, but can also help investigators to define it. Two examples are provided (the interpretation of surface contour and the perception of moving shadows) to show how this approach can be used in practice. As the authors admit, most (if not all) perceptual processes are ill-suited to a "strong" Bayesian approach based on a single consistent model of the world. Instead, they argue for a "weak" variant that assumes Bayesian inference to be carried out in modules of more limited scope. But how weak is "weak"? Are such approaches suitable for only a few relatively low-level tasks, or can they be applied more generally? Could a weak Bayesian approach, for example, explain how we would recognize the return of Elvis Presley? The formal modelling of human perception To help get a fix on things, it is useful to examine the fate of an earlier attempt to formalize human perception: the application of information theory. It was once hoped that this theory—a close cousin of the Bayesian formulation—would provide a way to uncover information-handling laws that were largely independent of physical implementation. In this approach, the human nervous system was assumed to have.. (shrink)

The human body has always been one of the most important subjects for European artists. But the way it is displayed in art has varied in different epochs. In ancient Greece, a canon was constituted that proclaimed an ideal vision of the body, derived from the rules governing the universe. This idealization of the human body, neglected in the Middle Ages, was re‑established in Renaissance and Classicist art. However, Renaissance artists also created another image of the human body by (...) borrowing from patterns mainly found in nature, and started to depict their models not in an ideal but rather in a more natural shape. The new non‑ideal forms of art that appeared in Mannerist art made the artists develop a much wider artistic language, which brought into being a variety of individually interpreted artistic representations of the human body. It preceded similar phenomena which became widespread in the twentieth century. Thus, the human body was not always displayed in art as strong, healthy and beautiful. On the contrary, the martyred bodies of Christ and the saints, as well as the depictions of aged, tired or ill people, also carried enormous artistic expression. A distinct problem has occurred with the ways in which corpses have been presented in art. The review concludes with a reference to the contemporary trend called Body‑Art that involves various artistic activities, such as happenings and performances, where the human body is itself used as a significant work of art. (shrink)

The focus in the literature on scientific explanation has shifted in recent years towards modelbased approaches. The idea that there are simple and true laws of nature has met with objections from philosophers such as Nancy Cartwright (1983) and Paul Teller (2001), and this has made a strictly Hempelian D-N style explanation largely irrelevant to the explanatory practices of science (Hempel & Oppenheim, 1948). Much of science does not involve subsuming particular events under laws of nature. It is increasingly recognized (...) that science across the disciplines is to some degree a patchwork of scientific models, with different methods, strategies, and with varying degrees of successful prediction and explanation. And so accounts of scientific explanation have reflected this change of perspective and model-based approaches have flourished in the explanation literature (Batterman, 2002b; Bokulich, 2008; Craver, 2006; Woodward, 2003). (shrink)

In a possible world framework, an agent can be said to know a proposition just in case the proposition is true at all worlds that are epistemically possible for the agent. Roughly, a world is epistemically possible for an agent just in case the world is not ruled out by anything the agent knows. If a proposition is true at some epistemically possible world for an agent, the proposition is epistemically possible for the agent. If a proposition is true at (...) all epistemically possible worlds for an agent, the proposition is epistemically necessary for the agent, and as such, the agent knows the proposition. -/- This framework presupposes an underlying space of worlds that we can call epistemic space. Traditionally, worlds in epistemic space are identified with possible worlds, where possible worlds are the kinds of entities that at least verify all logical truths. If so, given that epistemic space consists solely of possible worlds, it follows that any world that may remain epistemically possible for an agent verifies all logical truths. As a result, all logical truths are epistemically necessary for any agent, and the corresponding framework only allows us to model logically omniscient agents. This is a well-known consequence of the standard possible world framework, and it is generally taken to imply that the framework cannot be used to model non-ideal agents that fall short of logical omniscience. -/- A familiar attempt to model non-ideal agents within a broadly world involving framework centers around the use of impossible worlds where the truths of logic can be false. As we shall see, if we admit impossible worlds where “anything goes” in epistemic space, it is easy to avoid logical omniscience. If any logical falsehood is true at some impossible world, then any logical falsehood may remain epistemically possible for some agent. As a result, we can use an impossible world involving framework to model extremely non-ideal agents that do not know any logical truths. -/- A much harder, and considerably less investigated challenge is to ensure that the resulting epistemic space can also be used to model moderately ideal agents that are not logically omniscient but nevertheless logically competent. Intuitively, while such agents may fail to rule out impossible worlds that verify complex logical falsehoods, they are nevertheless able to rule out impossible worlds that verify obvious logical falsehoods. To model such agents, we need a construction of a non-trivial epistemic space that partly consists of impossible worlds where not "anything goes". This involves imposing substantive constraints on impossible worlds to eliminate from epistemic space, say, trivially impossible worlds that verify obvious logical falsehoods. -/- The central aim of this dissertation is to investigate the nature of such non-trivially impossible worlds and the corresponding epistemic spaces. To flag my conclusions, I argue that successful constructions of epistemic spaces that can safely navigate between the Charybdis of logical omniscience and the Scylla of of “anything goes” are hard, if not impossible to find. (shrink)

The underrepresentation of women, people of color, and especially women of color—and the corresponding overrepresentation of white men—is more pronounced in philosophy than in many of the sciences. I suggest that part of the explanation for this lies in the role played by the idealized rational self, a concept that is relatively influential in philosophy but rarely employed in the sciences. The idealized rational self models the mind as consistent, unified, rationally transcendent, and introspectively transparent. I hypothesize that acceptance (...) of the idealized rational self leads philosophers to underestimate the influence of implicit bias on their own judgments and prevents them from enacting the reforms necessary to minimize the effects of implicit bias on institutional decision-making procedures. I consider recent experiments in social psychology that suggest that an increased sense of one’s own objectivity leads to greater reliance on bias in hiring scenarios, and I hypothesize how these results might be applied to philosophers’ evaluative judgments. I discuss ways that the idealized rational self is susceptible to broader critiques of ideal theory, and I consider some of the ways that the picture functions as a tool of active ignorance and color-evasive racism. (shrink)

Non-epistemic values pervade climate modelling, as is now well documented and widely discussed in the philosophy of climate science. Recently, Parker and Winsberg have drawn attention to what can be termed “epistemic inequality”: this is the risk that climate models might more accurately represent the future climates of the geographical regions prioritised by the values of the modellers. In this paper, we promote value management as a way of overcoming epistemic inequality. We argue that value management can be seriously (...) considered as soon as the value-free ideal and inductive risk arguments commonly used to frame the discussions of value influence in climate science are replaced by alternative social accounts of objectivity. We consider objectivity in Longino's sense as well as strong objectivity in Harding's sense to be relevant options here, because they offer concrete proposals that can guide scientific practice in evaluating and designing so-called multi-model ensembles and, in fine, improve their capacity to quantify and express uncertainty in climate projections. (shrink)

This paper analyses the phenomenology and epistemology of chatbots such as ChatGPT and Bard. The computational architecture underpinning these chatbots are large language models (LLMs), which are generative artificial intelligence (AI) systems trained on a massive dataset of text extracted from the Web. We conceptualise these LLMs as multifunctional computational cognitive artifacts, used for various cognitive tasks such as translating, summarizing, answering questions, information-seeking, and much more. Phenomenologically, LLMs can be experienced as a “quasi-other”; when that happens, users anthropomorphise (...) them. For most users, current LLMs are black boxes, i.e., for the most part, they lack data transparency and algorithmic transparency. They can, however, be phenomenologically and informationally transparent, in which case there is an interactional flow. Anthropomorphising and interactional flow can, in some users, create an attitude of (unwarranted) trust towards the output LLMs generate. We conclude this paper by drawing on the epistemology of trust and testimony to examine the epistemic implications of these dimensions. Whilst LLMs generally generate accurate responses, we observe two epistemic pitfalls. Ideally, users should be able to match the level of trust that they place in LLMs to the degree that LLMs are trustworthy. However, both their data and algorithmic opacity and their phenomenological and informational transparency can make it difficult for users to calibrate their trust correctly. The effects of these limitations are twofold: users may adopt unwarranted attitudes of trust towards the outputs of LLMs (which is particularly problematic when LLMs hallucinate), and the trustworthiness of LLMs may be undermined. (shrink)

General Relativity’s Schwarzschild solution describes a spherically symmetric gravitational field as an utterly static thing. The Space Generation Model describes it as an absolutely moving thing. The light propagation time-delay experiment of Shapiro-Reasenberg [1] and the falling atomic clock experiment of Vessot-Levine [2] provide the ideal context for illustrating how, though the respective world views implied by these models are radically di fferent, they make nearly the same prediction for the results of these experiments.

Schaffner’s model of theory reduction has played an important role in philosophy of science and philosophy of biology. Here, the model is found to be problematic because of an internal tension. Indeed, standard antireductionist external criticisms concerning reduction functions and laws in biology do not provide a full picture of the limits of Schaffner’s model. However, despite the internal tension, his model usefully highlights the importance of regulative ideals associated with the search for derivational, and embedding, deductive relations among mathematical (...) structures in theoretical biology. A reconstructed Schaffnerian model could therefore shed light on mathematical theory development in the biological sciences and on the epistemology of mathematical practices more generally. *Received November 2006; revised March 2009. †To contact the author, please write to: Philosophy Department, University of California, Santa Cruz, 1156 High St., Santa Cruz, CA 95064; e‐mail: [email protected]. (shrink)

Among the many functions of models, explanation is central to the functioning and aims of science. However, the discussions surrounding modeling and explanation in philosophy have largely remained separate from each other. This chapter seeks to bridge the gap by focusing on the puzzle of model-based explanation, asking how different philosophical accounts answer the following question: if idealizations and fictions introduce falsehoods into models, how can idealized and fictional models provide true explanations? The chapter provides a selective (...) and critical overview of the available strategies for solving this puzzle, mainly focusing on idealized models and how they explain. (shrink)

G. W. Leibniz developed a new model for rational decision-making which is suited to complicated decisions, where goods do not rule each other out, but compete with each other. In such cases the deliberator has to consider all of the goods and pick the ones that contribute most to the desired goal which in Leibniz’s system is ultimately the advancement of universal perfection. The inclinations to particular goods can be seen as vectors leading to different directions much like forces in (...) Leibniz’s dynamics. The vectorial model of rational decision-making is related to Leibniz’s work with metaphysical physics and the calculus of variations and is a heuristic tool which helps in finding reasonable combinations – in ideal cases optimums - between competing goods. By applying the model, the decision-maker can map and compare outcomes of combinations of goods in question and practice a kind of pseudo-mechanical arithmetic of reasons. A central feature of the model is the possibility to employ geometrical figures to help the conceptualization. In this paper I present the vectorial model, examine its applications in practical cases from political theory, jurisprudence and ethics Leibniz presented, and compare the model to recent theories of acting under uncertainty, such as bounded rationality and optimizing under constraints. (shrink)

The terms “model” and “model-building” have been used to characterize the field of formal philosophy, to evaluate philosophy’s and philosophical logic’s progress and to define philosophical logic itself. A model is an idealization, in the sense of being a deliberate simplification of something relatively complex in which several important aspects are left aside, but also in the sense of being a view too perfect or excellent, not found in reality, of this thing. Paraconsistent logic is a branch of philosophical (...) logic. It is however not clear how paraconsistent logic can be seen as model-building. What exactly is modeled? In this paper I adopt the perspective of looking at a particular instance of paraconsistent logic—paranormal modal logic—which might be seen as a model of a specific kind of agent: inductive agents. After ntroducing what I call the highlevel and low-level models of inductive agents, I analyze the extent to which the above-mentioned idealizing features of model-building appear in paranormal modal logic and how they affect its philosophical significance. (shrink)

The article examines the collaborations between the pensionnaires of the Villa Medici in Rome and the members of the French School of Athens, shedding light on the complex relationships between architecture, art, and archeology. The second half of the 19th century was a period during which the exchanges and collaborations between archaeologists, artists, and architects acquired a reinvented role and a dominant place. Within such a context, Athens was the place par excellence, where the encounter between these three disciplines took (...) place. The main objective of the article is to render explicit how the revelations of archeology, actively disseminated by the members of the French School of Athens—the “Athéniens”—had an important impact on the approach of certain pensionnaires of the Villa Medici in Rome. Particular emphasis is placed on certain pensionnaires, who decided to devote their envois to ancient monuments of Greece. In parallel, the article intends to shed light on the methods that helped the pensionnaires-architects of the Villa Medici in Rome appropriate archaeological discoveries concerning Greek antiquities. The article takes, as a starting point, the following hypothesis: to better understand the figure of the architect-archaeologist, of whom Jacques Ignace Hittorff is an emblematic example, it is pivotal to bear in mind that before the second half of the 19th century neither the figure of Hellenic archeology nor the figure of the architect had yet acquired their autonomy. Taking into account that Johann Joachim Winckelmann, in the middle of the 18th century, forged an ideal Greek model, which was criticized during the second half of the 19th century, the article also sheds light on the fact that the revelations of archaeologists have called into question the Winckelmannian image of Greece. Another aspect that is explored in the article is Jacques Ignace Hittorff’s studies concerning the polychromy of ancient Greek monuments, paying special attention to his Restitution du temple d’Empédocle à Sélinonte ou l’Architecture polychrome chez les Grecs. The article also explores how the shifts of the status of philhellenism are related to the mutations of the meaning of travel to Greece. In parallel, it investigates the impact of Greek independence on the ideals of beauty and nature in arts, as well as how Greek independence is related to the intensification of the interest in the excavations of Greek antiquities. (shrink)

Simple idealized models seem to provide more understanding than opaque, complex, and hyper-realistic models. However, an increasing number of scientists are going in the opposite direction by utilizing opaque machine learning models to make predictions and draw inferences, suggesting that scientists are opting for models that have less potential for understanding. Are scientists trading understanding for some other epistemic or pragmatic good when they choose a machine learning model? Or are the assumptions behind why minimal (...) class='Hi'>models provide understanding misguided? In this paper, using the case of deep neural networks, I argue that it is not the complexity or black box nature of a model that limits how much understanding the model provides. Instead, it is a lack of scientific and empirical evidence supporting the link that connects a model to the target phenomenon that primarily prohibits understanding. (shrink)

In the natural and social sciences, it is common to use toy models—extremely simple and highly idealized representations—to understand complex phenomena. Some of the simple surrogate models used to understand opaque machine learning (ML) models, such as rule lists and sparse decision trees, bear some resemblance to scientific toy models. They allow non-experts to understand how an opaque ML model works globally via a much simpler model that highlights the most relevant features of the input space (...) and their effect on the output. The obvious difference is that the common target of a toy and a full-scale model in the sciences is some phenomenon in the world, while the target of a surrogate model is another model. This essential difference makes toy surrogate models (TSMs) a new object of study for theories of understanding, one that is not easily accommodated under current analyses. This paper provides an account of what it means to understand an opaque ML model globally with the aid of such simple models. (shrink)

Cancer biology features the ascription of normal functions to parts of cancers. At least some ascriptions of function in cancer biology track local normality of parts within the global abnormality of the aberration to which those parts belong. That is, cancer biologists identify as functions activities that, in some sense, parts of cancers are supposed to perform, despite cancers themselves having no purpose. The present paper provides a theory to accommodate these normal function ascriptions—I call it the Modeling Account of (...) Normal Function (MA). MA comprises two claims. First, normal functions are activities whose performance by the function-bearing part contributes to the self-maintenance of the whole system and, thereby, results in the continued presence of that part. Second, MA holds that models of system-level activities that are (partly) constitutive of self-maintenance are improved by including a representation of the relevant function-bearing part and by making reference to the activity/activities that part performs which contribute(s) to those system-level activities. I contrast MA with two other accounts that seek to explicate the ascription of normal functions in biology, namely, the organizational account and the selected effects account. Both struggle to extend to cancer biology. However, I offer ecumenical readings which allow them to recover some ascriptions of normal function to parts of cancers. So, though I contend that MA excels in this respect, the purpose of this paper is served if it provides materials for bridging the gap between cancer biology, philosophy of cancer, and the literature on function. (shrink)

I critically examine the assumption that the theoretical structure that varies under theoretical symmetries is redundant and should be eliminated from a metaphysical picture of the universe, following a ‘symmetry to reality’ inference. I do so by analysing the status of coordinate change symmetries taking a pragmatic approach. I argue that coordinate systems function as indexical devices, and play an important pragmatic role for representing concrete physical systems. I examine the implications of considering this pragmatic role seriously, taking what I (...) call a perspectivist stance. My conclusion is that under a perspectivist stance, all symmetries (including local gauge symmetries) potentially have a direct empirical status: they point to dynamical aspects that are invariant under changes of operationalisation, and they constitute a guide not to reality, but to nomology and kinship. (shrink)

Metaphors abound in both the arts and in science. Due to the traditional division between these enterprises as one concerned with aesthetic values and the other with epistemic values there has unfortunately been very little work on the relation between metaphors in the arts and sciences. In this paper, we aim to remedy this omission by defending a continuity thesis regarding the function of metaphor across both domains, that is, metaphors fulfill any of the same functions in science as they (...) do in the arts. Importantly, this involves the claim that metaphors in arts as well as science have both epistemic and aesthetic functions. (shrink)

Explainable AI (xAI) methods are important for establishing trust in using black-box models. However, recent criticism has mounted against current xAI methods that they disagree, are necessarily false, and can be manipulated, which has started to undermine the deployment of black-box models. Rudin (2019) goes so far as to say that we should stop using black-box models altogether in high-stakes cases because xAI explanations ‘must be wrong’. However, strict fidelity to the truth is historically not a desideratum (...) in science. Idealizations – the intentional distortions introduced to scientific theories and models – are commonplace in the natural sciences and are seen as a successful scientific tool. Thus, it is not falsehood qua falsehood that is the issue. In this paper, I outline the need for xAI research to engage in idealization evaluation. Drawing on the use of idealizations in the natural sciences and philosophy of science, I introduce a novel framework for evaluating whether xAI methods engage in successful idealizations or deceptive explanations (SIDEs). SIDEs evaluates whether the limitations of xAI methods, and the distortions that they introduce, can be part of a successful idealization or are indeed deceptive distortions as critics suggest. I discuss the role that existing research can play in idealization evaluation and where innovation is necessary. Through a qualitative analysis we find that leading feature importance methods and counterfactual explanations are subject to idealization failure and suggest remedies for ameliorating idealization failure. (shrink)

I argue that ML models used in science function as highly idealized toy models. If we treat ML models as a type of highly idealized toy model, then we can deploy standard representational and epistemic strategies from the toy model literature to explain why ML models can still provide epistemic success despite their lack of similarity to their targets.

The value-free ideal for science holds that values should not influence the core features of scientific reasoning. We defend the difference-to-inference model of value-permeation, which holds that value-permeation in science is problematic when values make a difference to the inferences made about a hypothesis. This view of value-permeation is superior to existing views, and it suggests a corresponding maxim—namely, that scientists should strive to eliminate differences to inference. This maxim is the basis of a novel value-free ideal for science. -/- (...) . (shrink)

Rawlsian ideal theory is meant to perform various roles in non-ideal theory. In this paper, I distinguish between three roles, and I consider the extent to which we can expect ideal theory to perform them. It is meant to serve as a target to guide non-ideal theorising in the long-term. It is also supposed to provide a way of comparing different injustices to tell us which is worst and therefore in most urgent need of a remedy. Finally, ideal theory is (...) the basis for a model of fairness that restricts the set of morally permissible measures in non-ideal theory. I show how the first two roles—the target and urgency roles—are less plausible than the fairness role. (shrink)

Economic theories of democratic legitimacy (discussed here as minimalist theories) have criticized deliberative accounts of democratic legitimacy on the grounds that they do not represent a practical possibility and that they create conditions that make actual democracies worse. It is not simply that they represent the wrong ideal. Rather, they are too idealistic – failing to show proper regard for the cognitive and moral limitations of persons and the depth of disagreement in democratic society. This article aims to show (1) (...) that the minimalist criterion of democratic legitimacy is self-defeating and (2) that even if there are minimal cognitive, moral, and social requirements for the possibility of practicable deliberative democracy, these limitations do not necessarily impose insuperable barriers for democratic deliberation as the normative basis of democratic legitimacy. Thus, the limiting facts do not dictate the structure of appropriate normative models of democracy in the way minimalists have supposed. (shrink)

From Plato to the present day, political theorists have used models of idealistic societies to think about politics. How can these idealistic models inform our thinking about political life in our non-ideal world? Not, as many political theorists have hoped, by providing normative guidance -- by showing us how things should be or where we should go. Even still, we can use these models to interpret the concepts we depend on to explain and evaluate political behavior and (...) institutions, thereby sharpening our explanations of how things work and our estimations of how to make things better. Seeing idealistic models in this light reveals a promising route to a form of political inquiry that integrates our explanatory aims and our normative aspirations. -/- (Updated: October 2024. The book is in production for publication by Oxford University Press, to appear in the Philosophy, Politics, and Economics series. I have uploaded the table of contents, chapter 1, and the bibliography.). (shrink)