Assuming that votes are independent, the epistemically optimal procedure in a binary collective choice problem is known to be a weighted supermajority rule with weights given by personal log-likelihood-ratios. It is shown here that an analogous result holds in a much more general model. Firstly, the result follows from a more basic principle than expected-utility maximisation, namely from an axiom (Epistemic Monotonicity) which requires neither utilities nor prior probabilities of the ‘correctness’ of alternatives. Secondly, a person’s input need not (...) be a vote for an alternative, it may be any type of input, for instance a subjective degree of belief or probability of the correctness of one of the alternatives. The case of a profile of subjective degrees of belief is particularly appealing, since here no parameters such as competence parameters need to be known. (shrink)

This article examines two questions about scientists’ search for knowledge. First, which search strategies generate discoveries effectively? Second, is it advantageous to diversify search strategies? We argue pace Weisberg and Muldoon, “Epistemic Landscapes and the Division of Cognitive Labor”, that, on the first question, a search strategy that deliberately seeks novel research approaches need not be optimal. On the second question, we argue they have not shown epistemic reasons exist for the division of cognitive labor, identifying the errors (...) that led to their conclusions. Furthermore, we generalize the epistemic landscape model, showing that one should be skeptical about the benefits of social learning in epistemically complex environments. (shrink)

The value of optimality modeling has long been a source of contention amongst population biologists. Here I present a view of the optimality approach as at once playing a crucial explanatory role and yet also depending on external sources of confirmation. Optimality models are not alone in facing this tension between their explanatory value and their dependence on other approaches; I suspect that the scenario is quite common in science. This investigation of the optimality approach thus (...) serves as a case study, on the basis of which I suggest that there is a widely felt tension in science between explanatory independence and broad epistemic interdependence, and that this tension influences scientific methodology. (shrink)

Epistemic trust is crucial for science. This article aims to identify the kinds of assumptions that are involved in epistemic trust as it is required for the successful operation of science as a collective epistemic enterprise. The relevant kind of reliance should involve working from the assumption that the epistemic endeavors of others are appropriately geared towards the truth, but the exact content of this assumption is more difficult to analyze than it might appear. The root (...) of the problem is that methodological decisions in science typically involve a complex trade-off between the reliability of positive results, the reliability of negative results, and the investigation's power. Which balance between these is the ‘correct’ one can only be determined in light of an evaluation of the consequences of all the different possible outcomes of the inquiry. What it means for the investigation to be ‘appropriately geared towards the truth’ thus depends on certain value judgments. I conclude that in the optimal case, trusting someone in her capacity as an information provider also involves a reliance on her having the right attitude towards the possible consequences of her epistemic work. 1 Introduction2 Epistemic Reliance within the Sciences3 Methodological Conventionalism4 Trust in Science5 Conclusions. (shrink)

The background of this paper (section 1) consists in a new account to foundation‐theoretic epistemology characterized by two features: (i) All beliefs are to be justified by deductive, inductive or abductive inferences from a minimalistic class of unproblematic (introspective or analytic) basic beliefs. (ii) Higher‐order justifications for these inferences are given by means of the novel method of optimality justifications. Optimality justifications are a new tool for epistemology (section 2). An optimality justification does not attempt todemonstratethat a (...) cognitive method is reliable (which is impossible), but pursues the more modest goal of demonstrating that the method isoptimalamong all accessible alternative methods for the given epistemic goal. The reasoning from the established optimality of a method to the acceptability of a particular belief generated by the method is accomplished by so‐called optimality principles. In sections 3–5, the method of optimality justifications is carried out in detail for three fundamental problems: justifying induction, logic, and theory‐generating abduction. (shrink)

There are several proposals to resolve the problem of epistemic peer disagreement which concentrate on the question of how to incorporate evidence of such a disagreement. The main positions in this field are the equal weight view, the steadfast view, and the total evidence view. In this paper we present a new argument in favour of the equal weight view. As we will show, this view results from a general approach of forming epistemic attitudes in an optimal way. (...) By this, the argument for equal weighting can be massively strengthened from reasoning via epistemic indifference to reasoning from optimality. (shrink)

‘Epistemic’ arguments for conservatism typically claim that given the limits of human reason, we are better off accepting some particular social practice or institution rather than trying to consciously improve it. I critically examine and defend here one such argument, claiming that there are some domains of social life in which, given the limits of our knowledge and the complexity of the social world, we ought to defer to those institutions that have robustly endured in a wide variety of (...) circumstances in the past while not being correlated with intolerable outcomes. These are domains of social life in which our ignorance of optimal institutions is radical, and there is uncertainty about the costs of error. This is an argument for the preservation of particular institutions, not particular policies or outcomes, and it specifically identifies these with the institutions that John Rawls called ‘the basic structure of society.’ The argument further implies that to the extent that there is any reason to change these institutions, changes should be calculated as far as possible to increase their ‘epistemic power.’. (shrink)

A necessary condition for a group being taken as a rational agent is that its choices and judgements are ‘logically contestable’, but this can lead to problems of aggregation, as Arrow impossibility theorem or the discursive dilemma. This paper proposes a contractarian or constitutional approach: the relevant thing is what aggregation mechanisms would be preferred by the members of the group. Two distinctions need to be made: first, judgement aggregation is not aggregation of decisions, and judgement aggregation needs be distinguished (...) from the aggregation of information: we assume that every member of the group has already taken into account the opinions of the other members, by means of a process of public deliberation, but they may end having different opinions; we also assume that the members are rational, so that they have no reasons to accept further changes in their individual opinions. So, from the epistemic point of view, the collective judgment is not a 'better' opinion than those of the individual members. The collective judgement is better seen as a kind of compromise, the outcome of a ‘bargain’, so to say. Basically, we assume that individuals will have an interest in choosing a specific aggregation function by taking into account how are they affected by the collective actions carried out by the group, and grounded on the chosen collective judgement. (shrink)

The constitution of a collective judgment is analyzed from a contractarian point of view. The optimal collective judgment is defined as the one that maximizes the sum of the utility each member gets from the collective adoption of that judgment. It is argued that judgment aggregation is a different process from the aggregation of information and public deliberation. This entails that the adoption of a collective judgment should not make any rational member of the group change her individual opinion, and (...) so the collective judgment can not have any kind of epistemic superiority over the individual ones. ‡The author acknowledges Spanish Government's research projects HUM2005–01686/FISO and HUM2005-25447-E, as well as the grant PR2006-0108 which allowed a three months stay at the Helsinki Collegium for Advanced Studies, in which a big part of this paper was written. †To contact the author, please write to: Universidad Nacional de Educación a Distancia, Dpto. de Lógica, Historia y F. de la ciencia, Humanidades, Paseo de Senda del rey 7, 28040 Madrid, Spain; e-mail: [email protected]. (shrink)

A new approach to Hume's problem of induction that justifies the optimality of induction at the level of meta-induction. Hume's problem of justifying induction has been among epistemology's greatest challenges for centuries. In this book, Gerhard Schurz proposes a new approach to Hume's problem. Acknowledging the force of Hume's arguments against the possibility of a noncircular justification of the reliability of induction, Schurz demonstrates instead the possibility of a noncircular justification of the optimality of induction, or, more precisely, (...) of meta-induction (the application of induction to competing prediction models). Drawing on discoveries in computational learning theory, Schurz demonstrates that a regret-based learning strategy, attractivity-weighted meta-induction, is predictively optimal in all possible worlds among all prediction methods accessible to the epistemic agent. Moreover, the a priori justification of meta-induction generates a noncircular a posteriori justification of object induction. Taken together, these two results provide a noncircular solution to Hume's problem. Schurz discusses the philosophical debate on the problem of induction, addressing all major attempts at a solution to Hume's problem and describing their shortcomings; presents a series of theorems, accompanied by a description of computer simulations illustrating the content of these theorems (with proofs presented in a mathematical appendix); and defends, refines, and applies core insights regarding the optimality of meta-induction, explaining applications in neighboring disciplines including forecasting sciences, cognitive science, social epistemology, and generalized evolution theory. Finally, Schurz generalizes the method of optimality-based justification to a new strategy of justification in epistemology, arguing that optimality justifications can avoid the problems of justificatory circularity and regress. (shrink)

The optimal balance between decidability and expressiveness is a big problem of logical systems, in particular, of quantified epistemic logics (QELs). On the one hand, decidability is a very significant characteristic of logics that allows us to use such logics in the framework of artificial intelligence. On the other hand, QELs have important expressive capabilities that should not be lost when we construct decidable fragments of these logics. QELs are known to be much more expressive than first-order logics. One (...) important example of their extra expressive power is that they allow us to distinguish between de dicto and de re readings of epistemic sentences. It is clear that such capabilities should be preserved as much as possible in decidable fragments. In this paper, we consider extensions of QELs that include quantification over modalities. Denote this extensions by $$\hbox {Q}_{\Box }$$ Ls. $$\hbox {Q}_{\Box }$$ Ls allows us to make more subtle distinctions between de dicto and de re readings of epistemic sentences, and we also should keep these new features as much as possible in decidable fragments. It is known that there are not much interesting decidable QELs. The situation with $$\hbox {Q}_{\Box }$$ Ls is the same. But in recent years (after 2018), we have obtained a variety of decidable $$\hbox {Q}_{\Box }$$ Ls constructed in different ways. We distinguish between (1) the approach in which for every undecidable $$\hbox {Q}_{\Box }$$ L and for every variant of its decidable fragment, a specific proof is constructed, and (2) the approach in which a class of decidable $$\hbox {Q}_{\Box }$$ Ls is obtained using general tools and a uniform method for all $$\hbox {Q}_{\Box }$$ Ls of this class. In this paper, we compare the results of these approaches. (shrink)

Journals regulate a significant portion of the communication between scientists. This paper devises an agent-based model of scientific practice and uses it to compare various strategies for selecting publications by journals. Surprisingly, it appears that the best selection method for journals is to publish relatively few papers and to select those papers it publishes at random from the available “above threshold” papers it receives. This strategy is most effective at maintaining an appropriate type of diversity that is needed to solve (...) a particular type of scientific problem. This problem and the limitation of the model is discussed in detail. (shrink)

Game-theoretic solution concepts describe sets of strategy profiles that are optimal for all players in some plausible sense. Such sets are often found by recursive algorithms like iterated removal of strictly dominated strategies in strategic games, or backward induction in extensive games. Standard logical analyses of solution sets use assumptions about players in fixed epistemic models for a given game, such as mutual knowledge of rationality. In this paper, we propose a different perspective, analyzing solution algorithms as processes of (...) learning which change game models. Thus, strategic equilibrium gets linked to fixed-points of operations of repeated announcement of suitable epistemic statements. This dynamic stance provides a new look at the current interface of games, logic, and computation. (shrink)

Weisberg and Muldoon’s epistemic landscape model (ELM) has been one of the most significant contributions to the use of agent-based models in philosophy. The model provides an innovative approach to establishing the optimal distribution of cognitive labor in scientific communities, using an epistemic landscape. In the paper, we provide a critical examination of ELM. First, we show that the computing mechanism for ELM is correct insofar as we are able to replicate the results using another programming language. Second, (...) we show that small changes in the rules that determine the behavior of individual agents can lead to important changes in simulation results. Accordingly, we claim that ELM results are robust with respect to the computing mechanism, but not necessarily across parameter space. We conclude by reflecting on the possible lessons to be gained from ELM as a class of simulations or cluster of models. (shrink)

This paper examines the concept of coherence and its role in legal reasoning. First, it identifies some problem areas confronting coherence theories of legal reasoning about both disputed questions of fact and disputed questions of law. Second, with a view to solving these problems, it proposes a coherence model of legal reasoning. The main tenet of this coherence model is that a belief about the law and the facts under dispute is justified if it is “optimally coherent,” that is, if (...) it is such that an epistemically responsible legal decision-maker would have accepted it as justified by virtue of its coherence in like circumstances. Last, looking beyond the coherence theory, the paper explores the implications of the version of legal coherentism proposed for a general theory of legal reasoning and rationality. (shrink)

Recent neo-Humean theories of laws of nature have placed substantial emphasis on the characteristic epistemic roles played by laws in scientific practice. In particular, these theories seek to understand laws in terms of their optimal predictive utility to creatures in our epistemic situation. In contrast to other approaches, this view has the distinct advantage that it is able to account for a number of pervasive features possessed by putative actual laws of nature. However, it also faces some unique (...) challenges. First, since the view tries to characterize the laws in terms of their predictive utility, any respects in which putative actual laws are sub-optimally predictively useful are inherently problematic. Such "predictive infelicities" can easily be found among our best physical theories. Second, in tying the laws to our epistemic situation, neo-Humeanism raises the possibility that by changing our epistemic situation, we can change the laws themselves, though it is hard to believe that we have such influence over the laws. This paper aims to address both of these challenges, first by presenting a variety of strategies for explaining away predictive infelicities, and then by developing a version of Lewis's "rigidification" strategy to preclude the possibility of our changing the laws. (shrink)

The aim of the article is to develop precise epistemic rules for good public political arguments, by which political measures in the broad sense are justified. By means of a theory of deliberative democracy, it is substantiated that the justification of a political measure consists in showing argumentatively that this measure most promotes the common good or is morally optimal. It is then discussed which argumentation-theoretical approaches are suitable for providing epistemically sound rules for arguments for such theses and (...) for the associated premises, rules whose compliance implies the truth or acceptability of the thesis. Finally, on the basis of the most suitable approach, namely the epistemological one, such systems of rules for the required types of arguments are presented that fulfil the conditions mentioned. (shrink)

A number of authors have defended permissivism by appealing to rational supererogation, the thought that some doxastic states might be rationally permissible even though there are other, more rational beliefs available. If this is correct, then there are situations that allow for multiple rational doxastic responses, even if some of those responses are rationally suboptimal. In this paper, I will argue that this is the wrong approach to defending permissivism—there are no doxastic states that are rationally supererogatory. By the lights (...) of contemporary linguistics, ‘rational’ is an absolute gradable adjective, and as such, can only be applied to things that satisfy the top of the scale of rationality. For this reason, it is not possible to believe what is rational while also failing to believe what is rationally optimal. (shrink)

The strength of many arguments for Classical Liberalism is often challenged on the grounds that these arguments appeal to controversial metaphysical structures or moral principles. To avoid these challenges, I appeal to a set of epistemic considerations to show that, in order to structure a society that affords optimal opportunity for citizens to obtain their interests, we have a rational obligation to protect individuals’ freedom to pursue those interests. In this paper, I defend the second premise of a larger (...) argument for Classical Liberalism and, ultimately, for negative natural rights. I conclude that each individual has a prima facie reason to regard every other individual as having an epistemic advantage with respect to evidence regarding their interests and how to obtain them. (shrink)

Indicators of the reliability of informants are essential for social learning in a society that is initially dominated by ignorance or superstition. Such reliability indicators should be based on meta-induction over records of truth-success. This is the major claim of this paper, and it is supported in two steps. One needs a non-circular justification of the method of meta-induction, as compared to other learning methods. An approach to this problem has been developed in earlier papers and is reported in section (...) 2. It is based on the predictive optimality of meta-inductive learning, under the assumption that objective success records are globally available. The rest of the paper develops an extension of this approach, so-called local meta-induction. Here individuals can access only success records of individuals in their immediate epistemic neighborhood. It is shown that local meta-inductive learning can spread reliable information over the entire population, and has clear advantages compared to success-independent social learning methods such as peer-imitation and authority-imitation.Send article to KindleTo send this article to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle. Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply. Find out more about the Kindle Personal Document Service.META-INDUCTION IN EPISTEMIC NETWORKS AND THE SOCIAL SPREAD OF KNOWLEDGEVolume 9, Issue 2Gerhard SchurzDOI: https://doi.org/10.1017/epi.2012.6Your Kindle email address Please provide your Kindle [email protected]@kindle.com Available formats PDF Please select a format to send. By using this service, you agree that you will only keep articles for personal use, and will not openly distribute them via Dropbox, Google Drive or other file sharing services. Please confirm that you accept the terms of use. Cancel Send ×Send article to Dropbox To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about sending content to Dropbox. META-INDUCTION IN EPISTEMIC NETWORKS AND THE SOCIAL SPREAD OF KNOWLEDGEVolume 9, Issue 2Gerhard SchurzDOI: https://doi.org/10.1017/epi.2012.6Available formats PDF Please select a format to send. By using this service, you agree that you will only keep articles for personal use, and will not openly distribute them via Dropbox, Google Drive or other file sharing services. Please confirm that you accept the terms of use. Cancel Send ×Send article to Google Drive To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about sending content to Google Drive. META-INDUCTION IN EPISTEMIC NETWORKS AND THE SOCIAL SPREAD OF KNOWLEDGEVolume 9, Issue 2Gerhard SchurzDOI: https://doi.org/10.1017/epi.2012.6Available formats PDF Please select a format to send. By using this service, you agree that you will only keep articles for personal use, and will not openly distribute them via Dropbox, Google Drive or other file sharing services. Please confirm that you accept the terms of use. Cancel Send ×Export citation Request permission. (shrink)

Since its inception in the early 1990s, evidence-based medicine (EBM) has become the dominant epistemic framework for Western medical practice. However, in light of powerful criticisms against EBM, alternatives such as casuistic medicine have been gaining support in both the medical and philosophical community. In the absence of empirical evidence in support of the claim that EBM improves patient outcomes, and in light of considerations that it is unlikely that such evidence will be forthcoming, another standard is needed to (...) assess EBM against its alternatives. In this paper, I propose a set of criteria for this purpose based on Helen Longino's criteria for assessing the objectivity of a knowledge productive community. I then apply these criteria to assess EBM against a casuistic framework for medical knowledge. I argue that EBM's strict adherence to a hierarchical organization of knowledge can reasonably be expected to block it from fulfilling a high level of objectivity. A casuistic framework, on the other hand, because it emphasizes critical evaluation in conjunction with the flexibility of a case-based approach, could be expected to better facilitate a more optimal epistemic community. (shrink)

Abstract:In this article, I argue that the cognitive value of narrative arts is an epistemic understanding of a complex set of facts. My argument is the following: because we are epistemically limited agents (in a sense of our cognitive capacity and motivation), engagement with narrative arts is the optimal way to familiarize ourselves with complex phenomena in the world, such as social injustice, institutional racism, and financial crises. Exemplary narrative works of art possess epistemic features that other (...) class='Hi'>epistemic sources, such as scientific articles and newspaper reports, lack. These features are narrative compression, simplified language, engagement with fictional characters, and artistic features. These features make exemplary narrative works of art an optimal way for an average agent to learn about the complex world around them. The article consists of three parts: Knowledge and Understanding, Narrative Arts as Epistemic Sources, and Understanding the Financial Crisis of 2007–8 with The Big Short (2015). In the first part, I introduce concepts of knowledge and understanding and explain why they are important for my claim. In the second part, I present my claim and offer arguments for it. In the third part, I illustrate my claim with the movie The Big Short (2015). (shrink)

When conversing and collaborating in everyday situations, people naturally and interactively align their behaviors with each other across various communication channels, including speech, gesture, posture, and gaze. Having access to a partner's referential gaze behavior has been shown to be particularly important in achieving collaborative outcomes, but the process in which people's gaze behaviors unfold over the course of an interaction and become tightly coordinated is not well understood. In this paper, we present work to develop a deeper and more (...) nuanced understanding of coordinated referential gaze in collaborating dyads. We recruited 13 dyads to participate in a collaborative sandwich-making task and used dual mobile eye tracking to synchronously record each participant's gaze behavior. We used a relatively new analysis technique—epistemic network analysis—to jointly model the gaze behaviors of both conversational participants. In this analysis, network nodes represent gaze targets for each participant, and edge strengths convey the likelihood of simultaneous gaze to the connected target nodes during a given time-slice. We divided collaborative task sequences into discrete phases to examine how the networks of shared gaze evolved over longer time windows. We conducted three separate analyses of the data to reveal (1) properties and patterns of how gaze coordination unfolds throughout an interaction sequence, (2) optimal time lags of gaze alignment within a dyad at different phases of the interaction, and (3) differences in gaze coordination patterns for interaction sequences that lead to breakdowns and repairs. In addition to contributing to the growing body of knowledge on the coordination of gaze behaviors in joint activities, this work has implications for the design of future technologies that engage in situated interactions with human users. (shrink)

I was in manufacturing for over thirty years and a manager for nearly twenty-five. During that time it never occurred to me that the consequentialist, utilitarian framework I used was inadequate as a conceptual framework for making decisions to ensure organisational viability and success.1 The framework gave three criteria which enabled me to construct a rational approach to issues associated with my role as a manager: To show that this framework is adequate as a basis for managerial decision making I (...) want to spell out the logical implications of the three criteria and show that they are necessary and jointly sufficient to provide an epistemically sound framework for managerial decisions. I will argue that we can look to managerial practice for examples which can serve as paradigms for constructing a pragmatic approach to management decision making, one that — when employed correctly — will result in the best moral outcome for all those affected by a decision.2 This approach is derived from, and ultimately justified by, the primary role responsibility of a manager to create and implement a healthy work environment. This is one designed to be viable so that the organisation can compete successfully in the marketplace and meet the morally minimal standard that we ought not to cause unnecessary and avoidable harm to innocent people. Because the approach is goal directed, it is teleological and consequential in nature. I maintain that a workplace, or organisation, is healthy when all the components that constitute it are working coherently together to achieve legitimate organisational goals designed to ensure the best chances of being viable and competitive. Such an organisation is what I term optimally functional.3. (shrink)

ABSTRACT The rise of social media has correlated with an increase in political polarization, which many perceive as a threat to public discourse and democratic governance. This paper presents a framework, drawing on social epistemology and the economic theory of public goods, to explain how social media can contribute to polarization, making us collectively poorer, even while it provides a preferable media experience for individual consumers. Collective knowledge and consensus is best served by having richly connected networks that are epistemically (...) integrated: individuals with diverse levels of expertise should be relatively well connected to each other. In epistemically segregated networks, by contrast, we have reason to predict collective epistemic failures. Expert knowledge will be isolated from the majority, leading average opinion to be less informed than is socially optimal, and entrenching disagreements. Because social media enables users to very easily adopt homophilous network connections – connections to those with similar opinions, education levels, and social backgrounds – it is likely to have increased epistemic segregation compared to older media platforms. The paper explains the theoretical foundations of these predictions, and sketches regulatory measures – such as taxes – that might be employed to preserve the public good of a well integrated social media network. (shrink)

The prelims comprise: Adequacy Conditions Dretske and the Flow of Information Epistemic Optimality Teleology Asymmetric Dependence Conclusion Glossary of Key Technical Terms.

Guidelines orient best practices in medicine, yet, in health care, many real world constraints limit their optimal realization. Since guideline implementation problems are not systematically anticipated, they will be discovered only post facto, in a learning curve period, while the already implemented guideline is tweaked, debugged and adapted. This learning process comes with costs to human health and quality of life. Despite such predictable hazard, the study and modeling of medical guideline implementation is still seldom pursued. In this article we (...) argue that to systematically identify, predict and prevent medical guideline implementation errors is both an epistemic responsibility and an ethical imperative in health care, in order to properly provide beneficence, minimize or avoid harm, show respect for persons, and administer justice. Furthermore, we suggest that implementation knowledge is best achieved technically by providing simulation modeling studies to anticipate the realization of medical guidelines, in multiple contexts, with system and scenario analysis, in its alignment with the emerging field of implementation science and in recognition of learning health systems. It follows from both claims that it is an ethical imperative and an epistemic responsibility to simulate medical guidelines in context to minimize harm in health care, before guideline implementation. (shrink)

This paper starts with an examination of the major problems of foundation-oriented epistemology in Sect. 2. Then, in Sects. 3–4, it is argued that the externalistic re-definition of knowledge deprives this concept from useful applications to human’s epistemic practice. From the viewpoint of cultural evolution, the condition of justification is the most important ingredient of knowledge. An alternative foundation-oriented conception of knowledge called third-person internalism is developed in Sect. 2 and Sect. 5. It combines insights of externalism with the (...) requirement of second-order justification. The application of third-person internalism to contextualistic positions leads to an important constraint on contextualism (Sect. 6). The final section (Sect. 7) sketches new prospects for a foundation-oriented epistemology which are based on epistemic optimality arguments. (shrink)

An evidentialist can be extreme about epistemic requirements in a couple of different ways. At the reductionist end of the spectrum are those who think our epistemic obligations are fully satisfied by the mere having of evidential fit—where having implies nothing about doing. Your beliefs ought to align with your evidence, in other words, but there’s nothing you’re obligated to do in order to get yourself into the epistemically optimal position. At the expansionist end of the spectrum are (...) those who think we ought to do more—epistemically-speaking—than just bring about a state of evidential fit. We ought to get more evidence, for instance, if it’s somehow relevant to our beliefs. Rather leery of extremists, we prefer a moderate account of epistemic obligation. It’s a conjunction of three theses: (1) We never have an epistemic duty to believe any particular proposition; (2) We’re epistemically obligated to reflect on our evidence in order to produce a state of evidential fit; (3) We’re never epistemically obligated to acquire any additional evidence. Our aim is to make these plausible. (shrink)

Emotion theory is beset by category disputes. Examining the nature and function of scientific classification can make some of these more tractable. The aim of classification is to group particulars into <<natural>> classes - classes whose members share a rich cluster of properties in addition to those used to place them in the class. Classification is inextricably linked to theories of the causal processes that explain why certain particulars resemble one another and so are usefully regarded as <<of the same (...) kind>>. The need to base categories on underlying causal processes explains why mere careful definition (including operational definition) need not produce categories that are productive objects of scientific study. Because different causal processes produce different patterns of similarity there is unlikely to be a single classification that is optimal for addressing all scientific questions. Cultural categories should not be contrasted to natural categories, but should be treated as natural classes generated by underlying social processes. Our capacity to introduce epistemically optimal categories is often restricted because categories play a role in social and political, as well as epistemic, projects. This account of classification has many implications for emotion theory. (shrink)

Information we use to structure our lives is increasingly stored digitally, rather than in biomemory. (Just think: if your online calendar went down, would you know where you are supposed be and at what time next week?) Likewise, with breakthroughs such as those from Google DeepMind and OpenAI, discoveries at the frontiers of knowledge are increasingly due to machine learning (often, applied to massive datasets, extracted from a fast-growing datasphere) rather than to brainbound cognition. It’s hard to deny that knowledge (...) retention and production is becoming increasingly – in various ways – digitised. -/- Digital Knowledge: A Philosophical Investigation is the first book to squarely and rigorously investigate digital knowledge: what it is, how to make sense of it in connection with received theories of knowledge, and where it is going. Key questions J Adam Carter examines along the way are the following: -/- How is mere digital information converted into reliable digital knowledge? To what extent can digital knowledge be vindicated against sceptical challenges, and in what ways might digital knowledge stand distinctively subject to defeat? What is the epistemically optimal way for us to decide which tasks to outsource entirely to intelligent machines, and to what extent is further outsourcing appropriate (or not) to verify the results of that same outsourced cognition? Are there any ways in which the expansion of the datasphere threatens to make knowledge more, rather than easy, to come by? If so, are there any promising ways to safeguard, epistemically, against such threats? Using fascinating examples throughout, such as the recent chess match between Stockfish and Google’s AlphaZero, smartphones and personalisation, Digital Knowledge: A Philosophical Investigation is an ideal for researchers investigating this fascinating area of research at the intersection of traditional mainstream epistemology, the philosophy of cognitive science, the philosophy of technology, and computer science. (shrink)

This paper discusses the conditions for legitimate expert arrangements within a democratic order and from a deliberative systems approach. It is argued that standard objections against the political role of experts are flawed or ill-conceived. The problem that confronts us instead is primarily one of truth-sensitive institutional design: Which mechanisms can contribute to ensuring that experts are really experts and that they use their competencies in the right way? The paper outlines a set of such mechanisms. However, the challenge exceeds (...) that of producing epistemically optimal expert deliberations because a deliberative political system must also fulfil the ethical and democratic requirements of respect and inclusion. Yet, epistemic concerns justify expertise arrangements in the first place, and measures taken to make the use of expertise compatible with these requirements have to balance the potential rewards from expertise against potential deliberative costs. In the final part of the paper, the regulatory framework of a best practice expert advice system is tentatively analysed to illustrate the applicability and critical potential of our approach. (shrink)

A puzzle is generated by two intuitions about artworks: 1. There is no prima facie reason to take artworks to be mind-independent objects; 2. Aesthetic judgments are objective. These intuitions seem to be in tension, for if artworks or their aesthetic properties are mind-dependent, how can aesthetic judgments be objective? The common solution to the puzzle lies in rejecting or revising one of the two intuitions. Typically, realists reject 1, and many antirealists reject 2. I develop an antirealist aesthetic theory (...) that accommodates both intuitions, focusing on critical disagreement between epistemically optimal judges, realist difficulties with supervenience and response-dependence, the role of imagination in the experience of artworks, and the metaphorical quality of aesthetic discourse. The hallmark of realism, namely the mind-independence of aesthetic qualities, is an untenable commitment that yields an impoverished view of artworks. A cognitivist anti-realism is available which preserves the objectivity of aesthetic discourse and yields a richer conception of artworks and our interaction with them. (shrink)

Optimal decision-making requires us to accurately pinpoint the basis of our thoughts, e.g. whether they originate from our memory or our imagination. This paper argues that the phenomenal qualities of our subjective experience provide permissible evidence to revise beliefs, particularly as it pertains to memory. I look to the source monitoring literature to reconcile circumstances where mnemic beliefs and mnemic qualia conflict. By separating the experience of remembering from biological facts of memory, unusual cases make sense, such as memory qualia (...) without memory or a failure to have memory qualia with memory. I argue that a pragmatic, probabilistic approach to belief revision is a way to rationally incorporate information from conscious experience, whilst acknowledging its inherent difficulties as an epistemic source. I conclude with a Bayesian defense of source monitoring based on C.I. Lewis’ coherence argument for memorial knowledge. (shrink)

All epistemic agents physically consist of parts that must somehow comprise an integrated cognitive self. Biological individuals consist of subunits (organs, cells, molecular networks) that are themselves complex and competent in their own context. How do coherent biological Individuals result from the activity of smaller sub-agents? To understand the evolution and function of metazoan bodies and minds, it is essential to conceptually explore the origin of multicellularity and the scaling of the basal cognition of individual cells into a coherent (...) larger organism. In this paper I synthesize ideas in cognitive science, evolutionary biology, and developmental physiology toward a hypothesis about the origin of Individuality: “Scale-Free Cognition”. I propose a fundamental definition of an Individual based on the ability to pursue goals at an appropriate level of scale and organization, and suggest a formalism for defining and comparing the cognitive capacities of highly diverse types of agents. Any Self is demarcated by a computational surface – the spatio-temporal boundary of events that it can measure, model, and try to affect. This surface sets a functional boundary - a cognitive “light cone” which defines the scale and limits of its cognition. I hypothesize that higher-level goal-directed activity and agency, resulting in larger cognitive boundaries, evolve from the primal homeostatic drive of living things to reduce stress – the difference between current conditions and life-optimal conditions. The mechanisms of developmental bioelectricity - the ability of all cells to form electrical networks that process information - suggests a plausible set of gradual evolutionary steps that naturally lead from physiological homeostasis in single cells to memory, prediction, and ultimately complex cognitive agents, via scale-up of the drive of infotaxis. Recent data on the molecular mechanisms of pre-neural bioelectricity suggest a model of how increasingly sophisticated cognitive functions emerge smoothly from cell-cell communication used to guide embryogenesis and regeneration. This set of hypotheses provides a novel perspective on numerous phenomena, such as cancer, and makes several unique, testable predictions for interdisciplinary research that have implications not only for evolutionary developmental biology but also for biomedicine and perhaps artificial intelligence and exobiology. (shrink)

Within a formal epistemic model for simultaneous-move games, we present the following conditions: belief in the opponents’ rationality, stating that a player believes that every opponent chooses an optimal strategy, self-referential beliefs, stating that a player believes that his opponents hold correct beliefs about his own beliefs, projective beliefs, stating that i believes that j’s belief about k’s choice is the same as i’s belief about k’s choice, and conditionally independent beliefs, stating that a player believes that opponents’ types (...) choose their strategies independently. We show that, if a player satisfies BOR, SRB and CIB, and believes that every opponent satisfies BOR, SRB, PB and CIB, then he will choose a Nash strategy. We thus provide a sufficient collection of one-person conditions for Nash strategy choice. We also show that none of these seven conditions can be dropped. (shrink)

Identifying optimal ways of organizing exploration in particle physics mega-labs is a challenging task that requires a combination of case-based and formal epistemic approaches. Data-driven studies suggest that projects pursued by smaller master-teams are substantially more efficient than larger ones across sciences, including experimental particle physics. Smaller teams also seem to make better project choices than larger, centralized teams. Yet the epistemic requirement of small, decentralized, and diverse teams contradicts the often emphasized and allegedly inescapable logic of discovery (...) that forces physicists pursuing the fundamental levels of the physical world to perform centralized experiments in mega-labs at high energies. We explain, however, that this epistemic requirement could be met, since the nature of theoretical and physical constraints in high energy physics and the technological obstacles stemming from them turn out to be surprisingly open-ended. (shrink)

This article discusses Sven Ove Hansson’s corpus model for the influence of values (in particular, non-epistemic ones) in the hypothesis acceptance/rejection phase of scientific inquiry. This corpus model is based on Hansson’s concepts of scientific corpus and science ‘in the large sense’. I first present Hansson’s corpus model of value influence with some introductory comments about its origins, a detailed presentation of the model with a new terminology, an analysis of its limits, and an appreciation of its handling of (...) controversial non-epistemic values. I conclude that it is a very good candidate for managing value influence, because contrary to other models in the literature it is fairly simple, it provides a universal and systematic procedure for dealing with values, and it syste- matically preserves the epistemic integrity of science. I then study some difficulties associated with the model’s central feature of taking the maximum level of evidence required by the applications of a claim in order for the latter to enter the scientific corpus: the difficulty to identify this maximum requirement; the non-optimality of this requirement with respect to other less demanding requirements; the potentially detrimental consequences of the preference for false negatives over false positives on which it relies; and the issue of whether there can nevertheless be requirements higher than this maximum. I show that these issues may potentially challenge the corpus model. Finally, I call for empirical work (in particular, an investigation of scientists’ and engineers’ own normative views) in order to better assess these issues. (shrink)

Knowledge is widely regarded as being incompatible with epistemic luck, but according to several philosophers, the same does not hold for understanding. This paper examines to what extent understanding is vulnerable to epistemic luck. After discussing the weaknesses of some of the cases that have been offered to support the conclusion that understanding tolerates environmental epistemic luck, I turn to a more recent one offered in favour of the opposite conclusion. I argue that this case does not (...) manage to establish that understanding is vulnerable to environmental luck; this even if the fact that understanding comes in degrees is taken into account. Finally, I examine the vulnerability of understanding to intervening luck – the type of luck present in classical Gettier cases – and conclude that when such luck is present, one's understanding is necessarily sub-optimal; a conclusion that does not hold, according to what I argue, when it comes to environmental luck. (shrink)

There is a long history of using facts about disagreement to argue that many of our most precious beliefs are false in a way that can make a difference in our lives. In this essay I go over a series of such arguments, arguing that the best arguments target beliefs that meet two conditions: (i) they have been investigated and debated for a very long time by a great many very smart people who are your epistemic superiors on the (...) matter and have worked very hard under optimal circumstances to figure out if the belief is true, and (ii) as far as you know these people have not come to any significant agreement on the belief and as far as you know those who agree with you are not, as a group, in a better position to judge the belief than those who disagree with you. (shrink)

In pure science, the standard approach to non-epistemic values is to exclude them as far as possible from scientific deliberations. When science is applied to practical decisions, non-epistemic values cannot be excluded. Instead, they have to be combined with scientific information in a way that leads to practically optimal decisions. A normative model is proposed for the processing of information in both pure and applied science. A general-purpose corpus of scientific knowledge, with high entry requirements, has a central (...) role in this model. Due to its high entry requirements, the information that it contains is sufficiently reliable for the vast majority of practical purposes. However, for some purposes, the corpus needs to be supplemented with additional information, such as scientific indications of danger that do not satisfy the entry requirements for the corpus. The role of non-epistemic values in the evaluation of scientific information should, as far as possible, be limited to determining the level of evidence required for various types of practical decisions. (shrink)

The received view about depression in the philosophical literature is that it is defined, in part, by epistemic irrationality. This status is undeserved. The received view does not fully reflect current clinical thinking and is motivated by an overly simplistic, if not false, account of depression’s phenomenal character. Equally attractive, if not more so, is a view that says depression can be instantiated either rationally or irrationally. This rival view faces challenges of its own: it appears to entail that (...) there are situations when not being depressed is rationally sub-optimal and that resilience to, and healthy coping strategies for avoiding, depression can be rationally remiss. I criticise an existing reply to these challenges before motivating a better one from the perspective of epistemic consequentialism. (shrink)

By Parallel Reasoning is the first comprehensive philosophical examination of analogical reasoning in more than forty years designed to formulate and justify standards for the critical evaluation of analogical arguments. It proposes a normative theory with special focus on the use of analogies in mathematics and science. In recent decades, research on analogy has been dominated by computational theories whose objective has been to model analogical reasoning as a psychological process. These theories have devoted little attention to normative questions. In (...) this book Bartha proposes that a good analogical argument must articulate a clear relationship that is capable of generalization. This idea leads to a set of distinct models for the critical analysis of prominent forms of analogical argument. The same core principle makes it possible to relate analogical reasoning to norms and values of scientific practice. Reasoning by analogy is justified because it strikes an optimal balance between conservative values, such as simplicity and coherence, and progressive values, such as fruitfulness and theoretical unification. Analogical arguments are also justified by appeal to symmetry--like cases are to be treated alike. In elaborating the connection between analogy and these broad epistemic principles, By Parallel Reasoning offers a novel contribution to explaining how analogies can play an important role in the confirmation of scientific hypotheses. (shrink)

The objective of this paper is to apply the general idea of contextualism, as a theory of knowledge attribution, to the very specific case of testimony and trust characterized as being the procedure of the attribution of knowledge (and sincerity) to the informant. In the first part, I argue in favor of evidentialism, a viewpoint that takes epistemically responsible trust as a matter of evidence. In the second part, I consider the question of how strong an evidential basis has to (...) be for epistemically responsible trust. I have briefly registered two main tendencies in contemporary debates regarding trust and testimony: (i) the non-unitary character of our trust; (ii) and the requirement for a refinement of evidential standards. In short, I argue in favor of the stance that any ‘undiscriminatory generalization’ (both Redian or anti-reductivist and Humean or reductivist) concerning epistemically responsible trust is a kind of inappropriate theoretical idealization, and that a certain theoretical reconciliation has to be offered. Finally, in the third part, I propose trust-contextualism as the viewpoint that optimally harmonizes both our intuitive and theoretical requirements about epistemically responsible trust. (shrink)

The universal optimality theorem for metainduction works for epistemic agents faced with a choice among finitely many prediction methods. Eckhart Arnold and Tom Sterkenburg objected that it breaks...

Science is a social epistemic enterprise. The complexity of research requires the division of cognitive labor. As a consequence, scientists have to present results and incorporate the results of others into their body of knowledge. This creates the possibility of strategic behavior, leading to phenomena such as publication bias. To analyze the dynamics of strategic behavior in epistemic communities, agent-based modeling suggests itself as a method. The phenomena generated by the developed agent-based simulation model reveal a diverse set (...) of possible dynamics in strategically heterogeneous groups and support the claim that there is a trade-off between a behavioral rule’s efficacy to generate accurate beliefs under optimal conditions and its robustness to variation in the composition of the epistemic environment. (shrink)

As our epistemic ambitions grow, the common and scientific endeavours are becoming increasingly dependent on Machine Learning (ML). The field rests on a single experimental paradigm, which consists of splitting the available data into a training and testing set and using the latter to measure how well the trained ML model generalises to unseen samples. If the model reaches acceptable accuracy, an a posteriori contract comes into effect between humans and the model, supposedly allowing its deployment to target environments. (...) Yet the latter part of the contract depends on human inductive predictions or generalisations, which infer a uniformity between the trained ML model and the targets. The paper asks how we justify the contract between human and machine learning. It is argued that the justification becomes a pressing issue when we use ML to reach ‘elsewheres’ in space and time or deploy ML models in non-benign environments. The paper argues that the only viable version of the contract can be based on optimality (instead of on reliability which cannot be justified without circularity) and aligns this position with Schurz’s optimality justification. It is shown that when dealing with inaccessible/unstable ground-truths (‘elsewheres’ and non-benign targets), the optimality justification undergoes a slight change, which should reflect critically on our epistemic ambitions. Therefore, the study of ML robustness should involve not only heuristics that lead to acceptable accuracies on testing sets. The justification of human inductive predictions or generalisations about the uniformity between ML models and targets should be included as well. Without it, the assumptions about inductive risk minimisation in ML are not addressed in full. (shrink)

The purpose of this paper is to present a formal model of social net- works suitable for studying questions in social epistemology. We show how to use this model, in conjunction with a computer program for simulating groups of inquirers, to draw conclusions about the epistemological prop- erties of different social practices. This furnishes us with the beginnings of a systematic research program in social epistemology, from which to approach problems pertaining to epistemic value, optimal organization, and the dynamics (...) of multi-agent inquiry. (shrink)

Vision often dominates other perceptual modalities both at the level of experience and at the level of judgment. In the well-known McGurk effect, for example, one’s auditory experience is consistent with the visual stimuli but not the auditory stimuli, and naïve subjects’ judgments follow their experience. Structurally similar effects occur for other modalities (e.g. rubber hand illusions). Given the robustness of this visual dominance, one might not be surprised that visual imagery often dominates imagery in other modalities. One might be (...) surprised, however, that visual imagery often dominates perception in other modalities. This more controversial claim is motivated both by empirical data and by introspection. Some think of perception-perception visual dominance as epistemically good, holding that cases in which visual dominance misleads us (e.g. McGurk and rubber hand illusions) are cases in which the perceptual system resolves conflicts according to principles that are generally reliable. Here, we explore support for the more controversial claim that imagery-perception visual dominance is epistemically good. We suggest that, when the task is richly spatial, requiring for optimal performance the all-at-once identification of macro-spatial and allocentric properties (e.g. identifying the shape or location of a felt or heard object), the visual, whether perception or imagination, should dominate other modalities. Put another way, when identifying objects, one should go and look or, short of that, visually imagine candidate objects, and then follow the visual, even against conflicting perceptions from other modalities. For this broadly-typed category of of cognitive-perceptual task, vision does dominate and it should. (shrink)