Ioannis G. Ntagkas

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.

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.

Epistemologists often claim that in addition to belief and disbelief there is a third, neutral, doxastic attitude. Various terms are used: ‘suspending judgment’, ‘withholding’, ‘agnosticism’. It is also common to claim that the factors relevant to the justification of these attitudes are epistemic in the narrow sense of being factors that bear on the strength or weakness of one’s epistemic position with respect to the target proposition. This paper addresses two challenges to such traditionalism about doxastic attitudes. The first concerns the relevance of non-epistemic factors we might call "future-comparative" – e.g., that you’ll have more decisive evidence on whether p tomorrow – to the justification of suspending judgment. The second, from Jane Friedman, is to explain the point of the neutral attitude without appealing to inquiry and thus taking goal-related factors, which are not epistemic, such as the value of the goal or the prospects for finding means to achieve it, to bear on the justification of the neutral attitude. My defense of traditionalism relies on distinguishing three ways of being neutral on a question: agnosticism, inquiry and suspension of judgment. Traditionalism is saved because, of these, agnosticism alone is a genuine doxastic attitude.

Moderate epistemic akrasia is the state a subject is in when she believes that p and suspends judgment about whether her evidence supports p. In this article it is argued that, given a certain understanding of the attitude of suspension of judgment, moderate epistemic akrasia is doxastically irrational. The paper starts with a brief introduction that makes explicit some background notions and clarifies the dialectics of the debate. Second, the well-known distinction between propositional and doxastic rationality is introduced and some cases of improper basing are discussed. Third, two different cases are considered in which one might argue that moderate epistemic akrasia is doxastically rational, and it is argued that none is successful. Fourth, several objections are presented and answered. Finally, some conclusions are drawn.

There are many important dimensions of epistemic evaluation, one of which is justification. We don’t just evaluate beliefs for truth, reliability, accuracy, and knowledge, but also for justification. However, in the epistemological literature, there is much disagreement about the nature of justification and how it should be understood. One of the controversies that has separated the contemporary epistemological discourse into two opposing camps has to do with the internalism-externalism distinction. Whereas internalists defend certain core assumptions about justification from the pre-Gettier tradition, externalists generally think that the traditional conception is untenable and should be replaced. In this compilation thesis, I argue for, defend, and develop a particular brand of internalism, both in general and with respect to specific sources of justification. In papers 1 and 2, I defend a couple of well-known arguments for mentalism and accessibilism. Moreover, I also point out how prominent versions of these theses are vulnerable to serious problems (e.g., about over-intellectualization and vicious regresses). Part of my goal in the first couple of papers is to figure out what commitments the internalist should take on in order to avoid the externalist's objections, while at the same time receiving support from considerations that have motivated internalism in the past. In papers 3 and 4, I start from the assumption that mentalism is true and attempt to answer the following questions: 1) which non-factive mental states can play a justification-conferring role with respect to empirical belief? And 2) why does this set of states play the epistemic role it does? In response to question 1, I argue that all and only one's beliefs and perceptual experiences have justificatory relevance. In response to question 2, I argue that one's beliefs and perceptual experiences are one's strongly representational states, and that strongly representational states necessarily provide support to certain empirical propositions. Having done so, I then defend mentalism about scientific evidence from a couple of prominent objections in the recent literature. Lastly, in papers 5 and 6, I argue for a particular brand of internalism about testimonial and memorial justification and show how that position has a dialectical advantage over its main competitors.

The notion of belief appears frequently in cognitive science. Yet it has resisted definition of the sort that could clarify inquiry. How then might a cognitive science of belief proceed? Here we propose a form of pluralism about believing. According to this view, there are importantly different ways to "believe" an idea. These distinct psychological kinds occur within a multi-dimensional property space, with different property clusters within that space constituting distinct varieties of believing. We propose that discovering such property clusters is empirically tractable, and that this approach can help sidestep merely verbal disputes about what constitutes “belief.”

This paper is a partial defence of presentism against the argument from cross-time relations. It is argued, first, that the Aristotelian view of causation and persistence does not really depict these phenomena in terms of relations between entities existing at different times, and indeed excludes the possibility of such cross-time relations obtaining. Second, it is argued that to reject the existence of the past—and thereby be unable to ground the truth of claims about the past—does not lead to any absurd consequences.

ABSTRACTIn answering the circularity charge, Descartes consistently distinguished between truths whose demonstrations we currently perceive clearly and distinctly and truths whose demonstrations we merely remember having perceived clearly and distinctly. Descartes uses C-truths to prove God’s existence, thus validating R-truths. While avoiding one form of circularity, this introduces another circle, for Descartes believes that God’s existence validates R-truths even when itself an R-truth. I consider Newman and Nelson’s grounds enhancement strategy according to which this problem is solved when God’s existence is rendered axiomatic. I argue that since it is still possible to doubt axioms when not directly apprehending them, this strategy cannot work; having to reproduce the argument for God’s existence in face of sceptical doubt is unavoidable. Drawing both on Newman and Nelson’s notion of grounds enhancement and on repr...

This paper suggests that the appearance of circularity in descartes' arguments is due to a lack of precision in his statements of them, Rather than to any flaw in his reasoning. The clear and distinct perceptions presupposed in the demonstrations of the existence of God are not the same as those whose reliability depends upon the existence of god. He is presupposing the reliability only of those clear and distinct perceptions which are known through the light of nature and have metaphysical certainty in that they cannot be imagined false even on the demon hypothesis. And the only clear and distinct perceptions whose reliability he is demonstrating are those which are not known through the light of nature with metaphysical certainty but are subject to metaphysical doubt on the demon hypothesis, Even though they have moral or psychological certainty