The last couple of decades have witnessed a renewed interest in the notion of inductive risk among philosophers of science. However, while it is possible to find a number of suggestions about the mitigation of inductive risk in the literature, so far these suggestions have been mostly relegated to vague marginal remarks. This paper aims to lay the groundwork for a more systematic discussion of the mitigation of inductive risk. In particular, I consider two (...) approaches to the mitigation of inductive risk—the individualistic approach, which maintains that individual scientists are primarily responsible for the mitigation of inductive risk, and the socialized approach, according to which the responsibility for the mitigation of inductive risk should be more broadly distributed across the scientific community or, even more broadly, across society. I review some of the argument for and against the two approaches and introduce two new problems for the individualistic approach, which I call the problem of precautionary cascades and the problem of exogenous inductive risk, and I argue that a socialized approach might alleviate each of these problems. (shrink)

From what norms does the ethics of belief derive its oughts, its attributions of virtues and vices, responsibilities and irresponsibilities, its permissioning and censuring? Since my inductive risk account is inspired by pragmatism, and this method understands epistemology as the theory of inquiry, the paper will try to explain what the aims and tasks are for an ethics of belief, or project of guidance, which best fits with this understanding of epistemology. More specifically, this chapter approaches the ethics (...) of belief from a focus on responsible risk management, where doxastic responsibility is understood in terms of the degree of riskiness of agents’ doxastic strategies, a riskiness which is in turn most objectively measured through accordance or violation of inductive norms. Doxastic responsibility is attributable to agents on the basis of how epistemically risky was the process or strategy of inquiry salient in the etiology of their belief or in their maintenance of what one believes or accepts. (shrink)

Under what conditions does machine learning (ML) model opacity inhibit the possibility of explaining and understanding phenomena? In this article, I argue that nonepistemic values give shape to the ML opacity problem even if we keep researcher interests fixed. Treating ML models as an instance of doing model-based science to explain and understand phenomena reveals that there is (i) an external opacity problem, where the presence of inductive risk imposes higher standards on externally validating models, and (ii) an (...) internal opacity problem, where greater inductive risk demands a higher level of transparency regarding the inferences the model makes. (shrink)

The Argument from Inductive Risk (AIR) is taken to show that values are inevitably involved in making judgements or forming beliefs. After reviewing this conclusion, I pose cases which are prima facie counterexamples: the unreflective application of conventions, use of black-boxed instruments, reliance on opaque algorithms, and unskilled observation reports. These cases are counterexamples to the AIR posed in ethical terms as a matter of personal values. Nevertheless, it need not be understood in those terms. The values which (...) load a theory choice may be those of institutions or past actors. This means that the challenge of responsibly handling inductive risk is not merely an ethical issue, but is also social, political, and historical. (shrink)

Drug regulation is fraught with inductive risk. Regulators must make a prediction about whether or not an experimental pharmaceutical will be effective and relatively safe when used by typical patients, and such predictions are based on a complex, indeterminate, and incomplete evidential basis. Such inductive risk has important practical consequences. If regulators reject an experimental drug when it in fact has a favourable benefit/harm profile, then a valuable intervention is denied to the public and a company’s (...) material interests are needlessly thwarted. Conversely, if regulators approve an experimental drug when it in fact has an unfavourable benefit/harm profile, then resources are wasted, people are needlessly harmed, and other potentially more effective treatments are underutilized. Given that such regulatory decisions have these practical consequences, non-epistemic values about the relative importance of these consequences impact the way such regulatory decisions are made (similar to the analysis of laboratory studies on the toxic effects of dioxins presented in Douglas [2000]). To balance the competing demands of the pertinent non-epistemic values, regulators must perform what I call an “inductive risk calculus.” At least in the American context this inductive risk calculus is not well-managed. (shrink)

Some patients, following brain injury, do not outwardly respond to spoken commands, yet show patterns of brain activity that indicate responsiveness. This is “cognitive-motor dissociation” (CMD). Recent research has used machine learning to diagnose CMD from electroencephalogram (EEG) recordings. These techniques have high false discovery rates, raising a serious problem of inductive risk. It is no solution to communicate the false discovery rates directly to the patient’s family, because this information may confuse, alarm and mislead. Instead, we need (...) a procedure for generating case-specific probabilistic assessments that can be communicated clearly. This article constructs a possible procedure with three key elements: (1) a shift from categorical “responding or not” assessments to degrees of evidence; (2) the use of patient-centred priors to convert degrees of evidence to probabilistic assessments; and (3) the use of standardized probability yardsticks to convey those assessments as clearly as possible. (shrink)

In this paper I shall defend the idea that there is an abstract and general core meaning of objectivity, and what is seen as a variety of concepts or conceptions of objectivity are in fact criteria of, or means to achieve, objectivity. I shall then discuss the ideal of value-free science and its relation to the objectivity of science; its status can be at best a criterion of, or means for, objectivity. Given this analysis, we can then turn to the (...) problem of inductive risk. Do the value judgements regarding inductive risk really pose a threat to the objectivity of science? I claim that this is not the case because they do not lower the thresholds scientifically postulated for objectivity. I shall conclude the paper with a discussion of under-appreciated influences of values on science, which indeed pose a serious threat to the objectivity of some scientific disciplines. (shrink)

Havstad (2022) argues that the argument from inductive risk for the claim that non-epistemic values have a legitimate role to play in the internal stages of science is deductively valid. She also defends its premises and thus soundness. This is, as far as we are aware, the best reconstruction of the argument from inductive risk in the existing literature. However, there is a small flaw in this reconstruction of the argument from inductive risk which (...) appears to render the argument invalid. This flaw is superficial, and a small amendment to it rescues the claim of validity. (shrink)

To clarify the proper role of values in science, focusing on controversial expert responses to Covid-19, this article examines the status of (in)convenient hypotheses. Polarizing cases like health experts downplaying mask efficacy to save resources for healthcare workers, or scientists dismissing “accidental lab leak” hypotheses in view of potential xenophobia, plausibly involve modifying evidential standards for (in)convenient claims. Societies could accept that scientists handle (in)convenient claims just like nonscientists, and give experts less political power. Or societies could hold scientists to (...) a higher bar, by expecting them not to modify evidential standards to avoid costs only incidentally tied to error. (shrink)

This paper discusses ethical issues surrounding Integrated Assessment Models (IAMs) of the economic effects of climate change, and how climate economists acting as policy advisors ought to represent the uncertain possibility of catastrophe. Some climate economists, especially Martin Weitzman, have argued for a precautionary approach where avoiding catastrophe should structure climate economists’ welfare analysis. This paper details ethical arguments that justify this approach, showing how Weitzman’s “fat tail” probabilities of climate catastrophe pose ethical problems for widely used IAMs. The main (...) claim is that economists who ignore or downplay catastrophic risks in their representations of uncertainty likely fall afoul of ethical constraints on scientists acting as policy advisors. Such scientists have duties to honestly articulate uncertainties and manage (some) inductive risks, or the risks of being wrong in different ways. (shrink)

This article develops a constructive criticism of methodological conventionalism. Methodological conventionalism asserts that standards of inductive risk ought to be justified in virtue of their ability to facilitate coordination in a research community. On that view, industry bias occurs when conventional methodological standards are violated to foster industry preferences. The underlying account of scientific conventionality, however, is problematically incomplete. Conventions may be justified in virtue of their coordinative functions, but often qualify for posterior empirical criticism as research advances. (...) Accordingly, industry bias does not only threaten existing conventions but may impede their empirically warranted improvement if they align with industry preferences. My empiricist account of standards of inductive risk avoids such a problem by asserting that conventional justification can be pragmatically warranted but has, in principle, only a provisional status. Methodological conventions, therefore, should not only be defended from preference-based infringements on their coordinative function but ought to be subjected to empirical criticism. (shrink)

English abstract: Feminist philosophers of science have argued that various biases can and do influence the results of scientific investigations. Two kinds of arguments have been most influential: On the one hand, it has been argued that biased assumptions frequently bridge the gap between observation and theory associated with ‘the underdetermination thesis’. On the other hand, it has been argued that biased value judgments determine when the evidence in favor of a particular theory is considered sufficiently strong for the theory (...) to be accepted as true. This paper argues that bias can influence the results of scientific investigations via a third route. Briefly, biases can and do influence which theories are seriously proposed and considered in scientific communities, which in turn leads to otherwise promising theories being ignored when scientists are choosing between such theories. In the final section, I suggest that this result speaks in favor of taking a quite radical approach to eliminating unwanted biases in science. (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)

William James’ argument against William Clifford in The Will to Believe is often understood in terms of doxastic efficacy, the power of belief to influence an outcome. Although that is one strand of James’ argument, there is another which is driven by ampliative risk. The second strand of James’ argument, when applied to scientific cases, is tantamount to what is now called the Argument from Inductive Risk. Either strand of James’ argument is sufficient to rebut Clifford's strong (...) evidentialism and show that it is sometimes permissible to believe in the absence of compelling evidence. However, the two considerations have different scope and force. Doxastic efficacy applies in only some cases but allows any values to play a role in determining belief; risk applies in all cases but only allows particular conditional values to play a role. (shrink)

It has been common wisdom for centuries that scientific inference cannot be deductive; if it is inference at all, it must be a distinctive kind of inductive inference. According to demonstrative theories of induction, however, important scientific inferences are not inductive in the sense of requiring ampliative inference rules at all. Rather, they are deductive inferences with sufficiently strong premises. General considerations about inferences suffice to show that there is no difference in justification between an inference construed demonstratively (...) or ampliatively. The inductive risk may be shouldered by premises or rules, but it cannot be shirked. Demonstrative theories of induction might, nevertheless, better describe scientific practice. And there may be good methodological reasons for constructing our inferences one way rather than the other. By exploring the limits of these possible advantages, I argue that scientific inference is neither of essence deductive nor of essence inductive. (shrink)

The setting of evidential standards is a core practice of scientific assessment for policy. Persuaded by considerations of inductive risk, philosophers generally agree that the justification of evidential standards must appeal to non-epistemic values but debate whether the balance of non-epistemic reasons favours varying evidential standards versus maintaining fixed high evidential standards in assessment, as both sets of standards promote different and important political virtues of advisory institutions. In this paper, I adjudicate the evidential standards debate by developing (...) a novel argument from justice, drawing on the IPCC’s assessment of climate impacts as a case study. I argue that in assessments marked by background evidential inequality, maintaining fixed high evidential standards results in an unequal distribution of ‘epistemic power’ among stakeholders, producing a ‘powerful assessment’ for the data-rich (a high rate of findings) and a ‘weak assessment’ for the data-poor (a low rate of findings). Where such inequalities of epistemic power disadvantage those in data-poor regions with respect to fundamental interests, such as basic human rights, we have decisive reasons of justice to vary evidential standards. (shrink)

Utility discounting in intertemporal economic modelling has been viewed as problematic, both for descriptive and normative reasons. However, positive utility discount rates can be defended normatively; in particular, it is rational for future utility to be discounted to take into account model-independent outcomes when decision-making under risk. The resultant values will tend to be smaller than descriptive rates under most probability assignments. This also allows us to address some objections that intertemporal considerations will be overdemanding. A principle for utility (...) discount rates is suggested which is rooted in probability discounting. Utility discounting is defended against objections from Parfit (1984) and Broome (2005); Broome (2012). A sample utility discount rate is estimated. [Open access]. (shrink)

What makes science trustworthy to the public? This chapter examines one proposed answer: the trustworthiness of science is based at least in part on its independence from the idiosyncratic values, interests, and ideas of individual scientists. That is, science is trustworthy to the extent that following the scientific process would result in the same conclusions, regardless of the particular scientists involved. We analyze this "idiosyncrasy-free ideal" for science by looking at philosophical debates about inductive risk, focusing on two (...) recent proposals which offer different methods of avoiding idiosyncrasy: the high epistemic standards proposal and the democratic values proposal. (shrink)

Normatively inappropriate scientific dissent prevents warranted closure of scientific controversies and confuses the public about the state of policy-relevant science, such as anthropogenic climate change. Against recent criticism by de Melo-Martín and Intemann of the viability of any conception of normatively inappropriate dissent, I identify three conditions for normatively inappropriate dissent: its generation process is politically illegitimate, it imposes an unjust distribution of inductive risks, and it adopts evidential thresholds outside an accepted range. I supplement these conditions with an (...) inference-to-the-best-explanation account of knowledge-based consensus and dissent to allow policy makers to reliably identify unreliable scientific dissent. (shrink)

Animal welfare scientists face an acute version of the problem of inductive risk, since they must choose whether to affirm attributions of mental states to animals in advisory contexts, knowing their decisions hold consequences for animal welfare. In such contexts, the burden of proof should be sensitive to the consequences of error, but a framework for setting appropriate burdens of proof is lacking. Through reflection on two cases—pain and cognitive enrichment—I arrive at a tentative framework based on the (...) principle of expected welfare maximization. I then discuss the limitations of this framework and the questions it leaves open. (shrink)

Measures of inductive risk and of safety-principle violation help us to operationalize concerns about theological assertions or a sort which, as we saw in Part I, aggravate or intensify problems of religious luck. Our overall focus in Part II will remain on a) responses to religious multiplicity, and b) sharply asymmetrical religious trait-ascriptions to religious insiders and outsiders. But in Part II formal markers of inductive norm violation will supply an empirically-based manner of distinguishing strong from moderate (...) fideism. As we develop these markers we will elaborate their more specific connections with comparative study of religious fundamentalisms (chapters 3 and 4), with exclusivist responses to religious multiplicity (chapter 5), and with working hypotheses in cognitive science of religion (chapter 6). In Chapters 3 the special focus is on the need for comparative fundamentalism (hereafter CF), and on how a better inductive risk ‘toolkit’ can empower its development. The “Enemy in the Mirror” is a metaphor which researchers of CF have sometimes used to describe a phenomena of special concern. This allows that religious fundamentalism per se need not be morally or socially problem, and that the terms such as “fundamentalism” and “fideism should not be over-used by scholars. But the enemy-in-the-mirror phenomena, which gives rise to what I term “bias-mirroring” attributions of good/bad traits to religious insiders and outsiders, carries enormous moral risks. I argue that this is something researchers would do well to study. On the view to be developed, the enemy in the mirror phenomenon is a direct consequent of counter-inductive thinking when applied to a multiplicity of narrative testimonial traditions. (shrink)

A growing number of philosophers are concerned with the epistemic status of culturally nurtured beliefs, beliefs found especially in domains of morals, politics, philosophy, and religion. Plausibly, worries about the deep impact of cultural contingencies on beliefs in these domains of controversial views is a question about well-foundedness: Does it defeat well-foundedness if the agent is rationally convinced that she would take her own reasons for belief as insufficiently well-founded, or would take her own belief as biased, had she been (...) nurtured in a different psychographic community? This chapter will examine the proper scope and force of this epistemic location problem. It sketches an account of well and ill-founded nurtured belief based upon the many markers of doxastic strategies exhibiting low to high degrees of inductive risk: the moral and epistemic risk of ‘getting it wrong’ in an inductive context of inquiry. (shrink)

This chapter explores properties that bind individuals, knowledge, and communities, together. Section ‎‎1 introduces Hardwig’s argument from trust in others’ testimonies as entailing that trust is the glue ‎that binds individuals into communities. Section 2 asks “what grounds trust?” by exploring assessment ‎of collaborators’ explanatory responsiveness, formal indicators such as affiliation and credibility, ‎appreciation of peers’ tacit knowledge, game-theoretical considerations, and the role moral character ‎of peers, social biases, and social values play in grounding trust. Section 3 deals with establishing (...) ‎reliability standards for formation and breaching of trust. Different epistemic considerations and their ‎underpinning of inductive risks are examined through various communication routes within a ‎discipline, between disciplines, and to the public. Section 4 examines whether a collective entity can ‎be trusted over and above trust that is given to its individual members. Section 5 deals with the roles ‎technological artifacts play in distributed research and collective knowledge. It presents the common ‎view in which genuine trust cannot, in principle, be accorded to artifacts, so as an opposite view. We ‎show that what counts as a genuine object of trust is relevant to debates about the boundaries of ‎collective agency and as a criterion for extended cognitive systems.‎. (shrink)

Tough anti-terrorism policies are often defended by focusing on a fixed minority of the population who prefer violent outcomes, and arguing that toughness reduces the risk of terrorism from this group. This reasoning implicitly assumes that tough policies do not increase the group of 'potential terrorists', i.e., of people with violent preferences. Preferences and their level of violence are treated as stable, exogenously fixed features. To avoid this unrealis- tic assumption, I formulate a model in which policies can 'brutalise' (...) or 'appease' someone's personality, i.e., his preferences. This follows the endogenous prefer- ences approach, popular elsewhere in political science and economics. I formally decompose the effect of toughness into a (desirable) deterrence effect and an (un- desirable) provocation effect. Whether toughness is overall effi cient depends on which effect overweighs. I show that neglecting provocation typically leads to toughness exaggeration. This suggests that some tough anti-terrorism policies observable in the present and past can be explained by a neglect of provocation. (shrink)

This book has argued that problems of religious luck, especially when operationalized into concerns about doxastic risk and responsibility, can be of shared interest to theologians, philosophers, and psychologists. We have pointed out counter-inductive thinking as a key feature of fideistic models of faith, and examined the implications of this point both for the social scientific study of fundamentalism, and for philosophers’ and theologians’ normative concerns with the reasonableness of a) exclusivist attitudes to religious multiplicity, and b) theologically-cast (...) but bias-mirroring trait-ascriptions to religious insiders and outsiders. It is important to keep the descriptive/explanatory and normative concerns properly separated, but philosophy of luck and risk are relevant to both. More specifically, inductive risky theological strategies,we have argued, are a relevant concern both descriptively and normatively. The descriptive/explanatory relevance of measures of high inductive risk connects it with cognitive and social psychology of religion, while its normative relevance connects with critical concerns with epistemology of testimony, the epistemology of disagreement, and the ethics of belief. A research program to examine fideistic orientation and its relation to epistemically risky doxastic strategies is one of potentially numerous research programs on which philosophers and psychologists might work collaboratively. So this concluding chapter of our study culminates with the outline of a proposed research program at the intersection of shared concerns. I term this research program CICI, because it examines what lies at the intersection of CSR’s standing interest in the appeal of counter-intuitive ideas, and our own study’s focus on the fideistic penchant for counter-inductive thinking. Religious Studies scholars typically focus on particular traditions and teachings, while CSR scholars tend to eschew such content-focused approaches in favor of a study of evolutionary and hence generic or trans-religious functions and processes. I argue that CICI has the added benefit of effectively mediating this generic-specific contrast between CSR and Religious Studies, allowing CSR research to be more closely connected with and relevant to comparative fundamentalism. (shrink)

This paper presents a Least Square Monte Carlo approach for accurately calculating credit value adjustment (CVA). In contrast to previous studies, the model relies on the probability distribution of a default time/jump rather than the default time itself, as the default time is usually inaccessible. As such, the model can achieve a high order of accuracy with a relatively easy implementation. We find that the valuation of a defaultable derivative is normally determined via backward induction when their payoffs could be (...) positive or negative. Moreover, the model can naturally capture wrong or right way risk. (shrink)

In the first half of the 20 th century, philosophers of science used to sustain that the correct theory acceptance in science derived from their conforming to certain rules. However, from the historicist and practical turn in the philosophy of science, the theory acceptance started to be analyzed based on values rather than on a priori established rules. In this article, I will present four paradigmatic positions on the role of values in science. The first position, articulated by Hugh Lacey, (...) defends a regulative ideal of 'impartiality' in the acceptance of scientific theories as established. The other positions convey arguments that seem to conflict with this ideal. I characterize them as 'blind spot argument', 'inductive risk argument' and 'trust-based acceptance argument'. Based on this analysis, I will defend two main theses. My first thesis is that the ideal of impartiality is compatible with the arguments just mentioned. My second thesis is that the defense of impartiality has the advantage of providing a support for the epistemic authority of properly established scientific knowledge. Following Lacey, I will argue that theories can only be accepted as established under specified domains of phenomena. However, theories are accepted for other purposes, for example, when they are adopted to develop research or when they are endorsed to inform the legitimacy of an action. In such cases of theory acceptance, impartiality is neither possible nor desirable, which requires the support of other ideals. (shrink)

This article presents a generic model for pricing financial derivatives subject to counterparty credit risk. Both unilateral and bilateral types of credit risks are considered. Our study shows that credit risk should be modeled as American style options in most cases, which require a backward induction valuation. To correct a common mistake in the literature, we emphasize that the market value of a defaultable derivative is actually a risky value rather than a risk-free value. Credit value adjustment (...) (CVA) is also elaborated. A practical framework is developed for pricing defaultable derivatives and calculating their CVAs at a portfolio level. (shrink)

Built-in decision thresholds for AI diagnostics are ethically problematic, as patients may differ in their attitudes about the risk of false-positive and false-negative results, which will require that clinicians assess patient values.

Maps provide us with an easily recognizable version of the new demarcation problem: On the one hand, we are all familiar with graphics and maps that unacceptably distort our perceptions without being technically inaccurate or fictive; indeed there are whole websites groups devoted to curating such images for fun. On the other hand, there are multiple unavoidably value-laden choices that must be made in the production of any map. Producing a map requires choosing everything from the colors and thicknesses of (...) the lines, the scale, the projection system, the categories and parameters represented, and much more. There is no neutral default for any of these choices, and all of them shape what information the map communicates. All the visual choices involved in producing a map enable some information to be conveyed at the cost of hiding or distorting other information, as map makers themselves routinely acknowledge and discuss. Hence there are no straightforward answers to questions about the line between distortion and legitimate representational choices. I explore three distinctive kinds of epistemic risks in map-making that generate special versions of the demarcation problem, which I dub aesthetic risk, categorization risk, and simplification risk. I argue that in each case, even good maps – maps that are accurate and epistemically valuable – have the potential to mislead us. I end by looking at maps that offer special epistemic benefits by making clear their own lack of value-neutrality while still being accurate and epistemically fecund. (shrink)

My paper builds on the conceptual tools from three interrelated philosophical debates that—as I believe—may help structure important if chaotic discussions about surrogates for living human brains and resolve some practical issues related to regulatory matters. In particular, I refer to the discussions about the “moral precautionary principle” in research ethics (Koplin and Wilkinson 2019); about normative uncertainty in ethics (MacAskill, Bykvist, and Ord 2020), and about the inductive risk problem for animal welfare scientists (Birch 2018). I elucidate (...) upon the possible meanings of the phrase “a too good human brain surrogate” used by Henry T. Greely (2021), and I demonstrate that the evaluation of the practical and regulatory implications of the “goodness” of such surrogates created for research purposes should be sensitive to the possible consequences of two types of errors: the under-attribution and over-attribution of moral status to such beings. Many authors writing about this topic (including Greely 2021, but see also, e.g., Koplin and Savulescu 2019) concentrate only on the first type of error, neglecting the negative consequences of the second type, i.e., over-attribution. (shrink)

Consider a set of shuffled observations drawn from a fixed probability distribution over some instance domain. What enables learning of inductive generalizations which proceed from such a set of observations? The scenario is worthwhile because it epistemically characterizes most of machine learning. This kind of learning from observations is also inverse and ill-posed. What reduces the non-uniqueness of its result and, thus, its problematic epistemic justification, which stems from a one-to-many relation between the observations and many learnable generalizations? The (...) paper argues that this role belongs to any complexity regularization which satisfies Norton’s Material Theory of Induction (MTI) by localizing the inductive risk to facts in the given domain. A prime example of the localization is the Lottery Ticket Hypothesis (LTH) about overparameterized neural networks. The explanation of MTI’s role in complexity regularization of neural networks is provided by analyzing the stability of Empirical Risk Minimization (ERM), an inductive rule that controls the learning process and leads to an inductive generalization on the given set of observations. In cases where ERM might become asymptotically unstable, making the justification of the generalization by uniform convergence unavailable, LTH and MTI can be used to define a local stability. A priori, overparameterized neural networks are such cases and the combination of LTH and MTI can block ERM’s trivialization caused by equalizing the strengths of its inductive support for risk minimization. We bring closer the investigation of generalization in artificial neural networks and the study of inductive inference and show the division of labor between MTI and the optimality justifications (developed by Gerhard Schurz) in machine learning. (shrink)

To speak of being religious lucky certainly sounds odd. But then, so does “My faith holds value in God’s plan, while yours does not.” This book argues that these two concerns — with the concept of religious luck and with asymmetric or sharply differential ascriptions of religious value — are inextricably connected. It argues that religious luck attributions can profitably be studied from a number of directions, not just theological, but also social scientific and philosophical. There is a strong tendency (...) among adherents of different faith traditions to invoke asymmetric explanations of the religious value or salvific status of the home religion vis-à-vis all others. Attributions of good/bad religious luck and exclusivist dismissal of the significance of religious disagreement are the central phenomena that the book studies. Part I lays out a taxonomy of kinds of religious luck, a taxonomy that draws upon but extends work on moral and epistemic luck. It asks: What is going on when persons, theologies, or purported revelations ascribe various kinds of religiously-relevant traits to insiders and outsiders of a faith tradition in sharply asymmetric fashion? “I am saved but you are lost”; “My religion is holy but yours is idolatrous”; “My faith tradition is true, and valued by God, but yours is false and valueless.” Part II further develops the theory introduced in Part I, pushing forward both the descriptive/explanatory and normative sides of what the author terms his inductive risk account. Firstly, the concept of inductive risk is shown to contribute to the needed field of comparative fundamentalism by suggesting new psychological markers of fundamentalist orientation. The second side of what is termed an inductive risk account is concerned with the epistemology of religious belief, but more especially with an account of the limits of reasonable religious disagreement. Problems of inductively risky modes of belief-formation problematize claims to religion-specific knowledge. But the inductive risk account does not aim to set religion apart, or to challenge the reasonableness of religious belief tout court. Rather the burden of the argument is to challenge the reasonableness of attitudes of religious exclusivism, and to demotivate the “polemical apologetics” that exclusivists practice and hope to normalize. Lexington Books Pages: 290 978-1-4985-5017-8 • Hardback • December 2018 • $95.00 • (£65.00) 978-1-4985-5018-5 • eBook • December 2018 • $90.00 • (£60.00) ISBN 978-1-4985-5018-5 (pbk: alk. paper) (coming 2020) [Download the 30% personal use Discount Order Form I uploaded for hardcover or e-book, and please ask your library to purchase a copy for their collection.]. (shrink)

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

The main thesis of this paper is that when we trust the results of scientific research, that trust is inevitably directed at least in part at collective bodies rather than at single researchers, and that accordingly, reasonable assessments of epistemic trustworthiness in science must attend to these collective bodies. In order to support this claim, I start by invoking the collaborative nature of most of today’s scientific research. I argue that the trustworthiness of a collaborative research group does not supervene (...) on the trustworthiness of its individual members and point out some specific problems for the assessment of epistemic trustworthiness that arise from the specific nature of today’s collaborative research. Next, I argue that the social diffusion of trustworthiness goes even further; we always also need an assessment of the trustworthiness of the respective research community as a whole. Communities, I claim, play an essential role in the epistemic quality management of science. To see why this role is indispensible, we have to appreciate the full complexity of determining what is desirable in a method of inquiry. The relevant features of a method include three different dimensions: the reliability of positive results, the reliability of negative results, and the method’s power. Every methodological choice involves a trade-off between these three dimensions. The right balance between them (the “distribution of inductive risks”, or DIR) depends on value judgments about the costs of false results and the benefits of correct ones. Conventional methodological standards of research communities impose constraints on admissible DIR and thereby harmonize the implicit value judgments. Trusting that the research community has set the limitations on DIR in a suitable way is thus always part of placing our trust in a scientific result. (shrink)

As inductive decision-making procedures, the inferences made by machine learning programs are subject to underdetermination by evidence and bear inductive risk. One strategy for overcoming these challenges is guided by a presumption in philosophy of science that inductive inferences can and should be value-free. Applied to machine learning programs, the strategy assumes that the influence of values is restricted to data and decision outcomes, thereby omitting internal value-laden design choice points. In this paper, I apply arguments (...) from feminist philosophy of science to machine learning programs to make the case that the resources required to respond to these inductive challenges render critical aspects of their design constitutively value-laden. I demonstrate these points specifically in the case of recidivism algorithms, arguing that contemporary debates concerning fairness in criminal justice risk-assessment programs are best understood as iterations of traditional arguments from inductive risk and demarcation, and thereby establish the value-laden nature of automated decision-making programs. Finally, in light of these points, I address opportunities for relocating the value-free ideal in machine learning and the limitations that accompany them. (shrink)

This chapter sharpens the book’s criticism of exclusivist responsible to religious multiplicity, firstly through close critical attention to arguments which religious exclusivists provide, and secondly through the introduction of several new, formal arguments / dilemmas. Self-described ‘post-liberals’ like Paul Griffiths bid philosophers to accept exclusivist attitudes and beliefs as just one among other aspects of religious identity. They bid us to normalize the discourse Griffiths refers to as “polemical apologetics,” and to view its acceptance as the only viable form of (...) pluralism. This reasoning may seem initially plausible, but on closer examination his and other’s defence of the reasonableness of exclusivist responses to religious multiplicity fall apart. Informed by our study of luck-leaning theological explanations of religious difference and the counter-inductive thinking they exemplify, I argue that exclusivist responses to religious multiplicity are best explained by personal and group bias, and that a discourse between exclusivist authors or sects is beyond the pale of reasonable disagreement. Our study of descriptive (psychological) and prescriptive (religious) fideism in the first sections of Chapter Five suggests that we turn back to formal features of doxastic methods (i.e., of how people process), features that may be straightforwardly tested for in studies utilizing scales of religious orientation. These formal features allow us to better recognize not only the multiplicity of models of faith that religious adherents adhere to, but also that the relationship between forms of fideism is scalar: there is a spectrum of views running from rationalism to fideism, and at the fideistic end from moderate to strong forms of religious fideism. I further explain why developing tests and markers for a high degree of fideistic orientation is important to all those who study religion. The second half of the chapter turns to criticism or censure of exclusivist attitudes to religious multiplicity, in contrast to apologetic defenses of exclusivism. While we have examined the close connections between fideism and fundamentalism, and again between fundamentalism and exclusivism in earlier chapters, a sharper focus reveals an important but little-recognized distinction reflected in the literature: the distinction between religion-specific (or particularist) and mutualist exclusivism. The mutualist doesn’t talk just about the right of adherents of one specific religion to assert exclusivism, but the adherents of any and all “home” religions. I argue that some previously unrecognized problems for the reasonableness of exclusivist responses to religious multiplicity are brought to light when we make the distinction between the two basic ways to understand the claim that exclusivists are making. I put particularist (Barth, Lindbeck, Plantinga) and mutualist (Griffiths, Gellman, Margalit, D’Costa) defenses of exclusivism on the horns of a dilemma, and argue that despite the popularity it presently enjoys among post-liberal theologians, a close examination reveals that the very conceptual coherence of mutualist exclusivism is in serious doubt. (shrink)

In this peer commentary on L. Syd M. Johnson’s “Inference and Inductive Risk in Disorders of Consciousness,” I argue for the necessity of disability education as an integral component of decision-making processes concerning patients with DOC and, mutatis mutandis, all patients with disabilities. The sole qualification Johnson places on such decision-making is that stakeholders are educated about and “understand the uncertainties of diagnosis and prognosis.” Drawing upon research in philosophy of disability, social epistemology, and health psychology, I argue (...) that this educational qualification is insufficient to address systemic ableism and other forms of epistemic bias in quality of life judgments. (shrink)

Kevin Elliott and others separate two common arguments for the legitimacy of societal values in scientific reasoning as the gap and the error arguments. This article poses two questions: How are these two arguments related, and what can we learn from their interrelation? I contend that we can better understand the error argument as nested within the gap because the error is a limited case of the gap with narrower features. Furthermore, this nestedness provides philosophers with conceptual tools for analyzing (...) more robustly how values pervade science. (shrink)

This paper continues my development of philosophy of religion as multi-disciplinary comparative research. An earlier paper, “Wittgenstein and Contemporary Belief-Credence Dualism” compared Wittgensteinian reflections on religious discourse and praxis with B-C dualism as articulated by its leading proponents. While some strong commonalities were elaborated that might help to bridge Continental and Analytic approaches in philosophy of religion, Wittgenstein was found to be a corrective to B-C dualism especially as regards how the psychology and philosophy of epistemic luck/risk applies to (...) doxastic faith ventures. This paper aims to further elaborate a basis for improved dialogue between philosophers, theologians, and scholars in special sciences which study religion. I call this basis the Triangulated model the ABC’s of religious epistemics in order to contrast it with the B-C dualist proposal. (shrink)

As we have seen in the transition form Part I to Part II of this book, the inductive riskiness of doxastic methods applied in testimonial uptake or prescribed as exemplary of religious faith, helpfully operationalizes the broader social scientific, philosophical, moral, and theological interest that people may have with problems of religious luck. Accordingly, we will now speak less about luck, but more about the manner in which highly risky cognitive strategies are correlated with psychological studies of bias studies (...) and human cognitive ecology. Chapter Four is concerned with connections between psychological study of biases and heuristics, and the comparative study of fundamentalism. The first section looks at work by psychologists and philosophers on our bias blind spot. Later sections ask, ‘In what ways might biases and heuristics play a special role in aiding our understanding of, and response to, fundamentalist orientation?’. The judgments we make in ignorance of our own biases Montaigne calls our importunate presumptions, and he suggests a host of practical factors that make them appealing. Montaigne, as I discuss in the first section, associates many of our errors with one or another kind of presumption, often about our similarity or differences from others, or from God. Our obvious psychographic diversity, and the polemical ground dynamics involved in our ‘culture wars’ are compounded on the agential side by the invisibility of our biases to ourselves. A number of person and social biases are described that plausibly affect all of our beliefs in domains of controversial views, religious views included. The second section continues to study of how etiological symmetry (similar patterns of belief-uptake) gives rise to religious contrariety (diverse narratives and theologies) in testimonial faith traditions, and what the implications of this are for philosophy of religion, generally, and for an improved comparative study of fundamentalism, in particular. Utilizing the work of philosophers such as Rachel Fraser and psychologists such as Emily Pronin and her co-authors, I offer a four-step genealogical account for how etiological symmetry so easily gives rise to religious contrariety. This account begins with the narrative nature of testimony in the Abrahamic family of religions, and how narrative content confounds our “source monitoring.” My genealogy also introduces what I term biased-closure inferences (BCI) as one of the key enablers of religious exclusivism and absolutism. These are the seemingly ‘logical’ but actually very self-serving inferences people often make, inferences from their own belief being true, to any belief contrary to it being false. Those who claim unique truth, epistemic access, and/or virtue and religious value for the home religion are no exception to the broad pertinence of bias studies across domains of controversial view. The proximate causes of belief are all that we can study, and in these there may be significant etiological symmetries. Yet those groups themselves, especially to the extent that they are exclusivist, are tunnel-visioned on claims of doctrinal uniqueness: on content differences of a theological sort. Comparative philosophy is met with the puzzlement that symmetric or essentially similar doxastic strategies should give rise not just to cognitive diversity, but to what we can call polarized or polemical contrariety, contrariety of a kind where each view adamantly rejects all others. Arguably, the more that theologies offer explanations of a counter-inductive sort, or profess counter-inductive thinking as exemplary of faith, the better evidential ground there for inferring that bias involved in the acquisition or maintenance of beliefs. This provides more substance to the question of when censure, and etiological challenges to faith-based beliefs are philosophically well-motivated. (shrink)

Publics trust experts for personal and pro-social reasons. Scientists are among the experts publics trust most, and so, epistemic trust is routinely afforded to them. The call for epistemic trust to be more socially situated in order to account for the impact of science on society and public welfare is at the forefront of enhanced epistemic trust. I argue that the value-free ideal for science challenges establishing enhanced epistemic trust by preventing the inclusion of non-epistemic values throughout the evaluation of (...) evidence and communication of these values. By selectively silencing non-epistemic values, the ideal cannot take into account publics’ social and moral responses to inductive risk, which are instrumental for defining and determining public welfare. Furthermore, by emphasising epistemic values almost exclusively in science education and communication, the value-free ideal is presented to publics in such a way that it becomes a social indicator of trust. I show this through examination of the importance of values in decisions to trust, and conclude that values (and restrictions on them) can be used by lay publics to help decide which experts to trust. (shrink)

This chapter presents the reception of Leo Strauss by analytic philosophers after Strauss’s emigration to the United States. It gives a brief survey of the polemics against Strauss and his school by analytic philosophers, which aided in the self-constitution of analytic philosophy as a rival school of thought in philosophy. But most of the chapter is devoted to recovering the significance and influence of a criticism of Strauss by Ernest Nagel. The chapter argues that this response is of intrinsic interest (...) because it involves the relationship between science and values. Nagel’s response was foundational to Felix Oppenheim’s political philosophy or what Oppenheim called his project of ‘conceptual reconstruction.’ Lurking in Oppenheim’s response to Strauss are questions about the role of the principle of sufficient reason in philosophy. Rge chapter argues that an opportunity was missed to clarify questions pertaining to the inductive risk of philosophy more than a half century before these issues became fashionable again. (shrink)

The value-free ideal in science has been criticised as both unattainable and undesirable. We argue that it can be defended as a practical principle guiding scientific research even if the unattainability and undesirability of a value-free end-state are granted. If a goal is unattainable, then one can separate the desirability of accomplishing the goal from the desirability of pursuing it. We articulate a novel value-free ideal, which holds that scientists should act as if science should be value-free, and we argue (...) that even if a purely value-free science is undesirable, this value-free ideal is desirable to pursue. (shrink)

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

There is a growing consensus among philosophers of science that core parts of the scientific process involve non-epistemic values. This undermines the traditional foundation for public trust in science. In this article I consider two proposals for justifying public trust in value-laden science. According to the first, scientists can promote trust by being transparent about their value choices. On the second, trust requires that the values of a scientist align with the values of an individual member of the public. I (...) argue that neither of these proposals work and suggest an alternative that does better. When scientists must appeal to values in the course of their research, they should appeal to democratic values: the values of the public or its representatives. (shrink)

Philosophers of science now broadly agree that doing good science involves making non-epistemic value judgments. I call attention to two very different normative standards which can be used to evaluate such judgments: standards grounded in ethics and standards grounded in political philosophy. Though this distinction has not previously been highlighted, I show that the values in science literature contain arguments of each type. I conclude by explaining why this distinction is important. Seeking to determine whether some value-laden determination meets substantive (...) ethical standards is a very different endeavor from seeking to determine if it is politically legitimate. (shrink)

Roughly, empirical AI alignment research (AIA) is an area of AI research which investigates empirically how to design AI systems in line with human goals. This paper examines the role of non-epistemic values in AIA. It argues that: (1) Sciences differ in the degree to which values influence them. (2) AIA is strongly value-laden. (3) This influence of values is managed inappropriately and thus threatens AIA’s epistemic integrity and ethical beneficence. (4) AIA should strive to achieve value transparency, critical scrutiny (...) from inside and outside the discipline – involving the public –, and to empower actors without strong commercial interests. (shrink)

This paper examines religious epistemics in relationship to recent defenses of belief-credence dualism among analytic Christian philosophers, connecting what is most plausible and appealing in this proposal to Wittgenstein’s thought on the nature of religious praxis and affectively-engaged language-use. How close or far is Wittgenstein’s thought about faith to the analytic Christian philosophers’ thesis that “beliefs and credences are two epistemic tools used for different purposes”? While I find B-C dualism appealing for multiple reasons, the paper goes on to raise (...) critical concerns about the manner in which it has been applied to the epistemology of religious belief. I argue that this application is at odds with some of Wittgenstein’s best insights, and that it presents a promising but comparatively unbalanced account of religious epistemics. (shrink)