Ioannis G. Ntagkas

Laws of nature are puzzling because they have a 'modal character'—they seem to be 'necessary-ish'—even though they also seem to be metaphysically contingent. And it is hard to understand how contingent truths could have such a modal character. Scientific essentialism is a doctrine that seems to dissolve this puzzle, by showing that laws of nature are actually metaphysically necessary. I argue that even if the metaphysics of natural kinds and properties offered by scientific essentialism is correct, there are still some metaphysically contingent truths that share the modal character of the laws of nature. I argue that these contingent truths should be considered laws of nature. So even if scientific essentialism is true, at least some laws of nature are metaphysically contingent

Descartes's claim that the eternal truths were freely created by God is fraught with interpretive difficulties. The main arguments in the literature are classified as concerning the ontological status or the modalities of possibility and necessity of the eternal truths. The views of the principal defenders of the Creation Doctrine – Robert Desgabets, Pierre Sylvain Régis, and Antoine Le Grand are contrasted with those of Nicolas Malebranche. In clarifying the theological, ontological, and logical terms of the debate we can see that what was at stake was the objectivity and certainty of the truths of mathematics and physics. I conclude by suggesting that this issue might fruitfully be used to clarify the disparate discussions in the contemporary literature.

Conventional wisdom has it that truth is always evaluated using our actual linguistic conventions, even when considering counterfactual scenarios in which different conventions are adopted. This principle has been invoked in a number of philosophical arguments, including Kripke’s defense of the necessity of identity and Lewy’s objection to modal conventionalism. But it is false. It fails in the presence of what Einheuser (2006) calls c-monsters, or convention-shifting expressions (on analogy with Kaplan’s monsters, or context-shifting expressions). We show that c-monsters naturally arise in contexts, such as metalinguistic negotiations, where speakers entertain alternative conventions. We develop an expressivist theory—inspired by Barker (2002) and MacFarlane (2016) on vague predications and Einheuser (2006) on counterconventionals—to model these shifts in convention. Using this framework, we reassess the philosophical arguments that invoked the conventional wisdom.

Although true in some aspects, the suggested characterization of today’s science as a dichotomy between traditional science and data-driven science misses some of the nuance, complexity, and possibility that exists between the two positions. Part of the problem is the claim that Data Science works without theories. There are many theories behind the data that are used in science. However, for data science, the only theories that matter are those in mathematics, statistics, and computer science. In this conceptual paper, we add two other philosophy of science tenets, experiments and data, to the discussion to create a more nuanced view of how data science uses theories. Following Ihde’s concept of technoscience and the incessant quest for more precision, magnification, and resolution, we argue that technology-driven science created a need for more technology-driven science, culminating in data science. Further, we adapt Hacking and Galison’s views on physics to argue that data science is also an experimental science, which uses data objects in experiments. Drawing from Heelan, we called these objects “data-objects-for-knowing”. Finally, we conclude that data science is a science to study artificially created phenomena—a science to study the data manipulated by the equations and operations of AI. It disregards the connections between data and the real world that were carefully built by the theories from other sciences. In the experiments of data science, data are the world itself. The knowledge created by data science is purposely disconnected from any theory from other sciences; it is a knowledge for the sake of itself.

This paper defends a theory of hope according to which hopes are composed of a desire and a belief that the object of the desire is possible. Although belief plus desire theories of hope are now widely rejected, this is due to important oversights. One is a failure to recognize the relation that hope-constituting desires and beliefs must stand in to constitute a hope. A second is an oversimplification of the explanatory power of hope-constituting desires. The final portion of the paper uses an enhanced understanding of the psychology of hope to make progress on normative questions about hoping well.

The epistemological problem of the external world asks: (1) “How is knowledge of the external world possible given certain obstacles which make it look impossible?” This is a “how-possible?” question: it asks how something is possible given certain obstacles which make it look impossible (cf. Cassam 2007; Nozick 1981; Stroud 1984). Now consider the following question, which asks: (2) “How is a philosophically satisfying answer to (1) possible?” Skepticism is the thesis that knowledge of the external world is impossible. It therefore represents a negative answer to the first question. Meta-epistemological skepticism is the thesis that a satisfying philosophical explanation of how our knowledge of the external world is possible is itself impossible. It therefore represents a negative answer to the second question. In this thesis, I explore the prospects of meta-epistemological skepticism. In particular, I structure the thesis around two master arguments from for meta-epistemological skepticism. The first argument is that skepticism represents a kind of paradox which requires dispensing with a plausible principle or belief, or even 'platitude', which means that there's no philosophically satisfying response to the paradox (see, e.g., Stroud 1984), and the second argument is “Stroud’s dilemma” (cf. Cassam 2009), that either we explain how external world knowledge is possible by reference to what external world knowledge we have, thereby failing to answer the philosophical question adequately, or else we don't, but then we succumb to first-order skepticism. I argue that the first argument fails to provide adequate support for meta-epistemological skepticism. However, the second argument, Stroud’s dilemma, is plausible and withstands serious objections (e.g., from Sosa 1994, Williams 1996, and Cassam 2009). In short, while the worry emerging out of the 'skeptical paradox' view fails to adequately support meta-epistemological skepticism, Stroud’s dilemma succeeds. Fortunately, it doesn't show that we lack external world knowledge; we rather just can't explain, philosophically, how it's possible. We may have first-order knowledge without understanding how it's possible. This thesis therefore represents a partial defense of meta-epistemological skepticism. Meta-epistemological skepticism is a live option in epistemology.

Aristotle’s account of epistēmē is foundationalist. In contrast, the web of dialectical argumentation that constitutes justification for scientific principles is coherentist. Aristotle’s account of explanation is structurally parallel to the argument for a foundationalist account of justification. He accepts the first argument but his coherentist accounts of justification indicate that he would not accept the second. Where is the disanalogy? For Aristotle, the intelligibility of a demonstrative premise is the cause of the intelligibility of a demonstrated conclusion and causation is asymmetric. Within the Posterior Analytics itself, Aristotle does not account for this, but elsewhere he develops the resources for doing so: the cause is what acts on a substrate to actualize a potential in that substrate, resulting in the effect. On the other hand, it may well happen that two propositions entail each other, in which case one may as well justify the one on the basis of the other as vice versa.

The hoary philosophical tradition of hedonism – the view that pleasure is the basic ethical or normative value – suggests that it is at least reasonably and roughly intuitive. But philosophers no longer treat hedonism that way. For the most part, they think that they know it to be obviously false on intuitive grounds, much more obviously false on such grounds than familiar competitors. I argue that this consensus is wrong. I defend the intuitive cogency of hedonism relative to the dominant desire-based and objectivist conceptions of well-being and the good. I argue that hedonism is still a contender, and indeed that our current understanding of commonsense intuition on balance supports it.

Epistemic relativism has the contemporary academy in its grip. Not merely in the United States, but seemingly everywhere, most scholars working in the humanities and the social sciences seem to subscribe to some form of it. Even where the label is repudiated, the view is embraced. Sometimes the relativism in question concerns truth, sometimes justification. The core impulse appears to be a relativism about knowledge. The suspicion is widespread that what counts as knowledge in one cultural, or broadly ideological, setting need not count as knowledge in another.

There is considerable agreement among epistemologists that certain abilities are constitutive of understanding-why. These abilities include: constructing explanations, drawing conclusions, and answering questions. This agreement has led epistemologists to conclude that understanding is a kind of know-how. However, in this paper, I argue that the abilities constitutive of understanding are the same kind of cognitive abilities that we find in ordinary cases of knowledge-that and not the kind of practical abilities associated with know-how. I argue for this by disambiguating between different senses of abilities that are too often lumped together. As a consequence, non-reductionists about understanding—those that claim that understanding-why is not reducible to knowledge-that—need to find another way to motivate the view. In the end, the fact that abilities are constitutive of understanding-why does not give us reason to conclude that understanding is a kind of know-how.

Recently, many have argued that there are certain kinds of abstract mathematical explanations that are noncausal. In particular, the irrelevancy approach suggests that abstracting away irrelevant causal details can leave us with a noncausal explanation. In this paper, I argue that the common example of Renormalization Group explanations of universality used to motivate the irrelevancy approach deserves more critical attention. I argue that the reasons given by those who hold up RG as noncausal do not stand up to critical scrutiny. As a result, the irrelevancy approach and the line between casual and noncausal explanation deserves more scrutiny.

In this chapter, we address the roles that exemplars might play in a comprehensive response to epistemic injustice. Fricker defines epistemic injustices as harms people suffer specifically in their capacity as (potential) knowers. We focus on testimonial epistemic injustice, which occurs when someone’s assertoric speech acts are systematically met with either too little or too much credence by a biased audience. Fricker recommends a virtue­theoretic response: people who do not suffer from biases should try to maintain their disposition towards naive testimonial justice, and those who find themselves already biased should cultivate corrective testimonial justice by systematically adjusting their credence in testimony up or down depending on whether they are hearing from someone whom they may be biased against or in favor of. We doubt that the prominent admiration­emulation model of exemplarism will be much use in this connection, so we propose two ways of learning from negative exemplars to better conduct one’s epistemic affairs. In the admiration­emulation model, both the identification of what a virtue is and the cultivation of virtues identified thusly proceed through the admiration of virtuous exemplars. We show that this model has serious flaws and argue for two alternatives: the envy­agonism model and the ambivalence­avoidance model.

Epistemologists have addressed a variety of modal epistemic standings, such as sensitivity, safety, risk, and epistemic virtue. These concepts mark out the ways that beliefs can fail to track the truth, articulate the conditions needed for knowledge, and indicate ways to become a better epistemic agent. However, it is our contention that current ways of carving up epistemic modality ignore the complexities that emerge when individuals are embedded within a community and listening to a variety of sources, some of whom are intentionally engaged in deception or bullshit. In this context we want our beliefs to be secure. In this paper we translate the epistemic modal standing of safety into a framework appropriate for social epistemology and argue for the importance of epistemic network-security and belief-security to be added to this framework. We discuss the virtues that are salient for promoting network-security and the vices that undermine it. In particular, we highlight monitoring, adjusting, and restructuring virtues and vices. Importantly, each of these vices can be other-regarding or self-regarding. For example, one tempting way of dealing with insecurity within a network is to completely cut oneself off from biased sources. However, we argue that this is a self-regarding restructuring vice because it closes oneself off from opportunities for epistemic growth. By contrast, an other-regarding restructuring vice would be to cut off others from hearing from sources of information that would make their network more secure.

Social epistemologists should be well-equipped to explain and evaluate the growing vulnerabilities associated with filter bubbles, echo chambers, and group polarization in social media. However, almost all social epistemology has been built for social contexts that involve merely a speaker-hearer dyad. Filter bubbles, echo chambers, and group polarization all presuppose much larger and more complex network structures. In this paper, we lay the groundwork for a properly social epistemology that gives the role and structure of networks their due. In particular, we formally define epistemic constructs that quantify the structural epistemic position of each node within an interconnected network. We argue for the epistemic value of a structure that we call the (m,k)-observer. We then present empirical evidence that (m,k)-observers are rare in social media discussions of controversial topics, which suggests that people suffer from serious problems of epistemic vulnerability. We conclude by arguing that social epistemologists and computer scientists should work together to develop minimal interventions that improve the structure of epistemic networks.

Recent work by Kahan et al. (2017) on the psychology of motivated numeracy in the context of intracultural disagreement suggests that people are less likely to employ their capabilities when the evidence runs contrary to their political ideology. This research has so far been carried out primarily in the USA regarding the liberal–conservative divide over gun control regulation. In this paper, we present the results of a modified replication that included an active reasoning intervention with Western European participants regarding both the hierarchy–egalitarianism and individualism–collectivism divides over immigration policy (n = 746; considerably less than the preregistration sample size). We reproduce the motivated numeracy effect, though we do not find evidence of increased polarization of high-numeracy participants.

Scientists appeal to models when explaining phenomena. Such explanations are often dubbed model explanations or model-based explanations. But what are the precise conditions for ME? Are ME special explanations? In our paper, we first rebut two definitions of ME and specify a more promising one. Based on this analysis, we single out a related conception that is concerned with explanations that are induced from working with a model. We call them ‘model-induced explanations’. Second, we study three paradigmatic cases of alleged ME. We argue that all of them are MIE, upon closer examination. Third, we argue that this undermines the building consensus that model explanations are special explanations that, e.g., challenge the factivity of explanation. Instead, it suggests that what is special about models in science is the epistemology behind how models induce explanations.

In this paper, we explain and showcase the promising methodology of testimonial network analysis and visualization for experimental epistemology, arguing that it can be used to gain insights and answer philosophical questions in social epistemology. Our use case is the epistemic community that discusses vaccine safety primarily in English on Twitter. In two studies, we show, using both statistical analysis and exploratory data visualization, that there is almost no neutral or ambivalent discussion of vaccine safety on Twitter. Roughly half the accounts engaging with this topic are pro-vaccine, while the other half are con-vaccine. We also show that these two camps rarely engage with one another, and that the con-vaccine camp has greater epistemic reach and receptivity than the pro-vaccine camp. In light of these findings, we question whether testimonial networks as they are currently constituted on popular fora such as Twitter are living up to their promise of delivering the wisdom of crowds. We conclude by pointing to directions for further research in digital social epistemology.

Knowledge is power. Knowledge about human psychology is increasingly being produced using natural language processing (NLP) and related techniques. The power that accompanies and harnesses this knowledge should be subject to ethical controls and oversight. In this chapter, we address the ethical pitfalls that are likely to be encountered in the context of such research. These pitfalls occur at various stages of the NLP pipeline, including data acquisition, enrichment, analysis, storage, and sharing. We also address secondary uses of the results and tools developed through psychometric NLP, such as profit-driven targeted advertising, political campaigns, and domestic and international psyops. Along the way, we reflect on potential ethical guidelines and considerations that may help researchers navigate these pitfalls.

What do humility, intellectual humility, and open-mindedness mean in the context of inter-group conflict? We spend most of our time with ingroup members, such as family, friends, and colleagues. Yet our biggest disagreements —— about practical, moral, and epistemic matters —— are likely to be with those who do not belong to our ingroup. An attitude of humility towards the former might be difficult to integrate with a corresponding attitude of humility towards the latter, leading to smug tribalism that masquerades as genuine virtue. These potentially conflicting priorities have recently come to the fore because “tribal epistemology” has so thoroughly infected political and social discourse. Most research on these dispositions focuses on individual traits and dyadic peer-disagreement, with little attention to group membership or inter-group conflict. In this chapter, we dilate the social scale to address this pressing philosophical and social problem.

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 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.

How should we respond to evidence when our evidence indicates that we are rationally impaired? I will defend a novel answer based on the analogy between self-doubt and memory loss. To believe that one is now impaired and previously was not is to believe that one’s epistemic position has deteriorated. Memory loss is also a form of epistemic deterioration. I argue that agents who suffer from epistemic deterioration should return to the priors they had at an earlier time. I develop this argument regarding memory loss then extend it to cases of self-doubt.

The problem of the Cartesian circle, as it is called, has sparked ongoing debate, which intersects several important themes of the Meditations. Discussions of the circle must address questions about the force and scope of the famous method of doubt introduced in Meditation I, and they must examine the intricate arguments for the existence of God and the avoidance of error in Meditations III to V. These discussions raise questions about the possibility of overturning skepticism, once a skeptical doubt has been introduced. More generally, the problem of the circle resonates with recent questions about the foundations of knowledge: Must we be able to validate our methods of reasoning or of knowing before using them? If we must, wouldn't we be forever stuck at the beginning, unable to use our methods of reasoning or of knowing in their own validation? The problem of the Cartesian circle raises general questions about the validation of reason and the possibility of knowledge. This chapter examines the Cartesian circle in the context of Descartes' central project in the Meditations, to secure the foundations of metaphysics. In carrying out this project, Descartes felt the need, or adopted the strategy, of examining the possibility of human knowledge more generally. Such an examination can be interpreted in various ways. Depending on the interpretation given, the roles assigned to the method of doubt and the proofs about God may differ, thereby altering how we see the problem of the circle. We therefore need first to consider Descartes' metaphysical project along with the methods and strategies he adopted in carrying it out. Subsequently, I explain and evaluate several main approaches to the problem of the circle. The chapter concludes with some reflections on the relation of Descartes' metaphysics of knowledge to other prominent positions in the history of philosophy.