It is now commonly held that values play a role in scientific judgment, but many arguments for that conclusion are limited. First, many arguments do not show that values are, strictly speaking, indispensable. The role of values could in principle be filled by a random or arbitrary decision. Second, many arguments concern scientific theories and concepts which have obvious practical consequences, thus suggesting or at least leaving open the possibility that abstruse sciences without such a connection could be value-free. Third, (...) many arguments concern the role values play in inferring from evidence, thus taking evidence as given. This paper argues that these limitations do not hold in general. There are values involved in every scientific judgment. They cannot even conceivably be replaced by a coin toss, they arise as much for exotic as for practical sciences, and they are at issue as much for observation as for explicit inference. (shrink)

Many philosophers and statisticians argue that risk assessors are morally obligated to evaluate the probabilities and consequences of methodological error, and to base their decisions of whether to adopt a given parameter value, model, or hypothesis on those considerations. This argument is couched within the rubric of null hypothesis testing, which I suggest is a poor descriptive and normative model for risk assessment. Risk regulation is not primarily concerned with evaluating the probability of data conditional upon the null hypothesis, but (...) rather with measuring risks, estimating the consequences of available courses of action and inaction, formally characterising uncertainty, and deciding what to do based upon explicit values and decision criteria. In turn, I defend an ideal of value-neutrality, whereby the core inferential tasks of risk assessment – such as weighing evidence, estimating parameters, and model selection – should be guided by the aim of correspondence to reality. This is not to say that value-judgments be damned, but rather that they should be accounted for within a structured approach to decision analysis, rather than embedded within risk assessment in an informal manner. (shrink)

The literature on values in science struggles with questions about how to describe and manage the role of values in scientific research. We argue that progress can be made by shifting this literature’s current emphasis. Rather than arguing about how non-epistemic values can or should figure into scientific assessment, we suggest analyzing how scientific assessment can accommodate non-epistemic values. For scientific assessment to do so, it arguably needs to incorporate goals that have been traditionally characterized as non-epistemic. Building on this (...) insight, we show how the adequacy-for-purpose framework recently developed for assessing scientific models can provide a general framework for describing scientific assessment so that it goes beyond purely epistemic considerations. Adopting this framework has significant advantages and opens the possibility of effecting a partial rapprochement between critics and proponents of the value-free ideal. (shrink)

Le débat sur le rôle des valeurs en science survient également dans les sciences appliquées, en particulier dans les sciences régulatives. Nous proposons une analyse, sous l’angle des valeurs, des controverses récentes sur le rôle de la connaissance scientifique dans la régulation des risques technologiques. Nous distinguons trois perspectives sur les valeurs cognitives et non-cognitives, dans le contexte de l’évaluation et de la gestion du risque. Notre analyse montre que les deux types de valeurs interagissent au sein du processus de (...) génération de connaissances dans les sciences régulatives, et que des propositions de changements méthodologiques dépendent de la reconnaissance explicite du rôle opérant des valeurs. Notre contribution indique que l’analyse philosophique des valeurs peut aider à clarifier les controverses actuelles sur les risques technologiques. (shrink)

Le débat sur le rôle des valeurs en science survient également dans les sciences appliquées, en particulier dans les sciences régulatives. Nous proposons une analyse, sous l’angle des valeurs, des controverses récentes sur le rôle de la connaissance scientifique dans la régulation des risques technologiques. Nous distinguons trois perspectives sur les valeurs cognitives et non-cognitives, dans le contexte de l’évaluation et de la gestion du risque. Notre analyse montre que les deux types de valeurs interagissent au sein du processus de (...) génération de connaissances dans les sciences régulatives, et que des propositions de changements méthodologiques dépendent de la reconnaissance explicite du rôle opérant des valeurs. Notre contribution indique que l’analyse philosophique des valeurs peut aider à clarifier les controverses actuelles sur les risques technologiques. (shrink)

The UK-based deliberations that led up to the legalisation of two new ‘mitochondrial donation’ techniques in 2015, and which continued after that time as regulatory details were determined, featured a division of advisory labour that is common when decisions are made about new technologies. An expert panel was convened by the Human Fertilisation and Embryology Authority, charged with assessing the scientific and technical aspects of these techniques. Meanwhile, the Nuffield Council on Bioethics addressed the ethical issues. While this division of (...) labour was undertaken in the name of thoroughness, I argue here that it can have the unintended consequence that hybrid questions that simultaneously involve ethical and technical aspects—especially questions about where to set evidential thresholds for the acceptance of new technology—do not receive enough attention. (shrink)

Several authors have recently contended that modern statistical theory provides a powerful argument in favor of the view that if scientists accept or reject hypotheses at all they do so only in a behavioral sense--i.e., in a sense which reduces "accepting P" to "acting on the basis of P relative to an objective O". In this paper, the argument from statistics in favor of a behavioral view is outlined; an interpretation of two statistical procedures (Bayes method and signifigance testing) is (...) offered which does not entail a behavioral analysis of "accepting a hypothesis"; and the conclusion that non-behavioral analyses of belief are compatible with the application of current statistical theory in the sciences is tentatively advanced. (shrink)

This paper is an investigation of the relation between personal and social conditions of knowledge. A coherence theory of knowledge and justification is assumed, according to which incoming information is evaluated in terms of background information. The evaluation of incoming information in terms of background information is a higher order or metamental activity. Personal knowledge and justification is based on the coherent integration of individual information. Social knowledge and justification is based on the coherent aggregation of social information, that is, (...) the information of individuals belonging to the social group. Personal justification and consensual justification are based upon personal and consensual probabilities respectively. Consensual and personal probabilities may differ, but under salient conditions personal probabilities will coincide with consensual probabilities and consensual probabilities will coincide with truth. (shrink)

A Lockean metaphysics of belief that understands outright belief as a determinable with degrees of confidence as determinates is supposed to effect a unification of traditional coarse-grained epistemology of belief with fine-grained epistemology of confidence. But determination of belief by confidence would not by itself yield the result that norms for confidence carry over to norms for outright belief unless belief and high confidence are token identical. We argue that this token-identity thesis is incompatible with the neglected phenomenon of “mistuned (...) knowledge” – knowledge in the absence of rational confidence. We show how partial epistemological unification can be secured, even without token identity, given determination of outright belief by degrees of confidence. Finally, we suggest a direction for the pursuit of thoroughgoing epistemological unification. (shrink)

I examine the construction and evaluation of machine learning binary classification models. These models are increasingly used for societal applications such as classifying patients into two categories according to the presence or absence of a certain disease like cancer and heart disease. I argue that the construction of ML classification models involves an optimisation process aiming at the minimization of the inductive risk associated with the intended uses of these models. I also argue that the construction of these models is (...) underdetermined by the available data, and that this makes it necessary for ML modellers to make social value judgments in determining the error costs used in ML optimization. I thus suggest that the assessment of the inductive risk with respect to the social values of the intended users is an integral part of the construction and evaluation of ML classification models. I also discuss the implications of this conclusion for the philosophical debate concerning inductive risk. (shrink)

Many philosophers have challenged the ideal of value-free science on the grounds that social or moral values are relevant to inferential thresholds. But given this view, how precisely and to what extent should scientists adjust their inferential thresholds in light of nonepistemic values? We suggest that signal detection theory provides a useful framework for addressing this question. Moreover, this approach opens up further avenues for philosophical inquiry and has important implications for philosophical debates concerning inductive risk. For example, the signal (...) detection theory framework entails that considerations of inductive risk and inferential-threshold placement cannot be conducted in isolation from base-rate information. (shrink)

Associated with Bayesianism is the claim that insofar as thereis anything like scientific theory-commitment, it is not a doxastic commitment to the truth of the theory or any proposition involving the theory, but is rather an essentiallypractical commitment to behaving in accordance with a theory. While there are a number of a priori reasons to think that this should be true, there is stronga posteriori reason to think that it is not in fact true of current scientific practice.After outlining a (...) feature that distinguishes doxastic from practical commitment, I presentempirical evidence that suggests that, like perhaps all other theoretical commitment,scientific theory-commitment is doxastic. (shrink)

This paper re-interprets the precautionary principle as a ‘social epistemic rule’. First, it argues that sometimes policy-makers should act on claims which have not been scientifically established....

In a recent paper, Gregor Betz has defended the value-free ideal: “the justification of scientific findings should not be based on non-epistemic values”against the methodological critique, by reference to the work of the International Panel on Climate Change . This paper argues that Betz’s defence is unsuccessful. First, Betz’s argument is sketched, and it is shown that the IPCC does not avoid the need to “translate” claims. In Section 2, it is argued that Betz mischaracterises the force of the methodological (...) critique. Section 3 shows why the methodological critique still applies to the work of the IPCC even on a refined version of Betz’s argument. Section 4 then considers an alternative way of defending the work of the IPCC which is in-line with, but does not clearly vindicate, the value-free ideal. (shrink)

In recent years, the argument from inductive risk against value free science has enjoyed a revival. This paper investigates and clarifies this argument through means of a case-study: neonicitinoid research. Sect. 1 argues that the argument from inductive risk is best conceptualised as a claim about scientists’ communicative obligations. Sect. 2 then shows why this argument is inapplicable to “public communication”. Sect. 3 outlines non-epistemic reasons why non-epistemic values should not play a role in public communicative contexts. Sect. 4 analyses (...) the implications of these arguments both for the specific case of neonicitinoid research and for understanding the limits of the argument from inductive risk. Sect. 5 sketches the broader implications of my claims for understanding the “Value Free Ideal” for science. (shrink)

In recent years, the value-freeness of science has come under extensive critique. Early objectors to the notion of value-free science can be found in Rudner and Churchman, later objections occur in Leach and Gaa, and more recent critics are Kitcher, Douglas, and Elliott. The goal of this paper is to examine and critique two arguments opposed to the notion of a value-free science. The first argument, the uncertainty argument, cites the endemic uncertainty of science and concludes that values are needed (...) to give direction to scientific investigation. The second, or moral argument, cites the fact that scientists have moral obligations just like everyone else, and.. (shrink)

In an important 2006 paper, Nishi Shah defends ‘evidentialism’, the position that only evidence for a proposition’s truth constitutes a reason to believe this proposition. In opposition to Shah, Anthony Robert Booth, Andrew Reisner and Asbjørn Steglich-Petersen argue that things other than evidence of truth, so-called non-evidential or ‘pragmatic’ reasons, constitute reasons to believe a proposition. I argue that we can effectively respond to Shah’s pragmatist critics if, following Shah, we are careful to distinguish the evaluation of the reasons for (...) a belief from the process of actually forming a belief and allowing it to influence action. Drawing this distinction is assisted if we utilize Rudolf Carnap’s probabilistic interpretation of what it means to be disposed to believe a claim. (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)

There is now a general consensus amongst philosophers in the values in science literature that values necessarily play a role in core areas of scientific inquiry. We argue that attention should now be turned from debating the value-free ideal to delineating legitimate from illegitimate influences of values in science, a project we dub “The New Demarcation Problem.” First, we review past attempts to demarcate the uses of values and propose a categorization of the strategies by where they seek to draw (...) legitimacy from. Next, we propose a set of desiderata for what we take to be a satisfactory solution and present a case study where conflicting sets of values clearly impinge on science, but where the legitimacy of their influence is ambiguous. We use these desiderata and the case study to illustrate what we take to be the strengths and weaknesses of current strategies. To be clear, our goal is not to answer the question we pose, but to articulate a framework within which a solution can be judged. (shrink)

The argument from inductive risk, as developed by Rudner and others, famously concludes that the scientist qua scientist makes value judgments. The paper aims to show that trust in the soundness of the argument is overrated – that philosophers who endorse its conclusion fail to refute two of the most important objections that have been raised to its soundness: Jeffrey’s objection that the genuine task of the scientist is to assign probabilities to hypotheses, and Levi’s objection that the argument is (...) ambiguous about decisions about how to act and decisions about what to believe, that only the former presuppose value judgments, and that qua scientist, the scientist only needs to decide what to believe. (shrink)

To explain the phenomena in the world of our experience, to answer the question “why?” rather than only the question “what?”, is one of the foremost objectives of all rational inquiry; and especially, scientific research in its various branches strives to go beyond a mere description of its subject matter by providing an explanation of the phenomena it investigates. While there is rather general agreement about this chief objective of science, there exists considerable difference of opinion as to the function (...) and the essential characteristics of scientific explanation. In the present essay, an attempt will be made to shed some light on these issues by means of an elementary survey of the basic pattern of scientific explanation and a subsequent more rigorous analysis of the concept of law and of the logical structure of explanatory arguments. (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)

In standard Bayesian probability revision, the adoption of full beliefs (propositions with probability 1) is irreversible. Once an agent has full belief in a proposition, no subsequent revision can remove that belief. This is an unrealistic feature, and it also makes probability revision incompatible with belief change theory, which focuses on how the set of full beliefs is modified through both additions and retractions. This problem in probability theory can be solved in a model that (i) lets the codomain of (...) the probability function be a hyperreal-valued rather than the real-valued closed interval [0, 1], and (ii) identifies the full beliefs as the propositions whose probability is either 1 or infinitesimally smaller than 1. In this model, changes in the probability function will result in changes in the set of full beliefs (belief set), which constitutes a submodel that can be conceived as the “tip of the iceberg” within the larger model that also contains beliefs on lower levels of probability. The patterns of change in the set of full beliefs in this modified Bayesian model coincides with the corresponding pattern in a slightly modified version of AGM revision, which is commonly conceived as the gold standard of (dichotomous) belief change. The modification only concerns the marginal case of revision by an inconsistent input sentence. These results show that probability revision and dichotomous belief change can be unified in one and the same framework, or – if we so wish – that belief change theory can be subsumed under a modified version of probability revision that allows for iterated change and for the removal of full beliefs. (shrink)

Additionally, the text shows how to develop computationally feasible methods to mesh with this framework.

n the John Locke Lectures, included in Meaning and the Moral Sciences, Hilary Putnam argues that "the 'softness' of social facts may affect the 'hard' notions of truth and reference" Without fully endorsing Putnam's argument, I hope to show that a similar argument could be constructed for a slightly different conclusion: that the 'softness' of ethics may affect the 'hard' notions of truth and reference.

The few extant arguments concerning the autonomy of science in the rational acceptance of hypotheses are examined. It is concluded that science is not morally autonomous, and that the attendant notion of rationality in science decisionmaking is inadequate. A more comprehensive notion of scientific rationality, which encompasses the old one, is proposed as a replacement. The general idea is that scientists qua scientist ought, in their acceptance decisions, to take into account the ethical consequences of acceptance as well as the (...) consequences with regard to the attainment of "purely scientific" or "epistemic" objectives. The result constitutes an argument for a (presumably cooperative) game theoretic treatment of inductive logic. (shrink)

Using climate policy debates as a case study, I argue that a certain response to the argument from inductive risk, the hedging defense, runs afoul of a reasonable ethical principle: the no-passing-...

Environmental health research produces scientific knowledge about environmental hazards crucial for public health and environmental justice movements that seek to prevent or reduce exposure to these hazards. The environment in environmental health research is conceptualized as the range of possible social, biological, chemical, and/or physical hazards or risks to human health, some of which merit study due to factors such as their probability and severity, the feasibility of their remediation, and injustice in their distribution. This paper explores the ethics of (...) identifying the relevant environment for environmental health research, as judgments involved in defining an environmental hazard or risk, judgments of that hazard or risk's probability, severity, and/ or injustice, as well as the feasibility of its remediation, all ought to appeal to non-epistemic as well as epistemic values. I illustrate by discussing the case of environmental lead, a housing-related hazard that remains unjustly distributed by race and class and is particularly dangerous to children. Examining a controversy in environmental health research ethics where researchers tested multiple levels of lead abatement in lead-contaminated households, I argue that the broader perspective on the ethics of environmental health research provided in the first part of this paper may have helped prevent this controversy. (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 motivates a shift in certain strands of the debate over legitimate roles for nonepistemic values in scientific practice from investigating what is involved in taking cognitive attitudes like acceptance toward an empirical hypothesis to looking at a social understanding of assertion, the act of communicating that hypothesis. I argue that speech act theory’s account of assertion as a type of doing makes salient legitimate roles nonepistemic values can play in scientific practice. The article also shows how speech act (...) theory might provide a framework for fruitfully extending aspects of the social and pragmatic turns in the philosophy of science. (shrink)

The doctrinal paradox shows that aggregating individual judgments by taking a majority vote does not always yield a consistent set of collective judgments. Philip Pettit, Luc Bovens, and Wlodek Rabinowicz have recently argued for the epistemic superiority of an aggregation procedure that always yields a consistent set of judgments. This paper identifies several additional epistemic advantages of their consistency maintaining procedure. However, this paper also shows that there are some circumstances where the majority vote procedure is epistemically superior. The epistemic (...) value of maintaining consistency does not always outweigh the epistemic value of making true judgments. (shrink)

Several different Bayesian models of epistemic utilities (see, e. g., [37], [24], [40], [46]) have been used to explain why it is rational for scientists to perform experiments. In this paper, I argue that a model-suggested independently by Patrick Maher [40] and Graham Oddie [46]-that assigns epistemic utility to degrees of belief in hypotheses provides the most comprehensive explanation. This is because this proper scoring rule (PSR) model captures a wider range of scientifically acceptable attitudes toward epistemic risk than the (...) other Bayesian models that have been proposed. I also argue, however, that even the PSR model places unreasonably tight restrictions on a scientist's attitude toward epistemic risk. As a result, such Bayesian models of epistemic utilities fail as normative accounts-not just as descriptive accounts (see, e. g., [31], [14])-of scientific inquiry. (shrink)

The paper’s target is the historically influential betting interpretation of subjective probabilities due to Ramsey and de Finetti. While there are several classical and well-known objections to this interpretation, the paper focuses on just one fundamental problem: There is a sense in which degrees of belief cannot be interpreted as betting rates. The reasons differ in different cases, but there’s one crucial feature that all these cases have in common: The agent’s degree of belief in a proposition A does not (...) coincide with her degree of belief in a conditional that A would be the case if she were to bet on A, where the belief in this conditional itself is conditioned on the supposition that the agent will have an opportunity to make such a bet. Even though the two degrees of belief sometimes can coincide (they will coincide in those cases when the bet has no expected causal bearings on the proposition A and the opportunity to bet have no evidential bearings on that proposition), it is the latter belief rather than the former that guides the agent’s rational betting behaviour. The reason is that this latter belief takes into consideration potential interferences that bet opportunities and betting itself might create with regard to the proposition to be betted on. It is because of this interference problem that the agent’s degree of belief in A cannot be interpreted as her betting rate for A. (shrink)

In recent papers and a book, Heather Douglas has expanded on the well-known argument from inductive risk, thereby launching an influential contemporary critique of the value-free ideal for science. This paper distills Douglas’s critique into four major claims. The first three claims provide a significant challenge to the value-free ideal for science. However, the fourth claim, which delineates her positive proposal to regulate values in science by distinguishing direct and indirect roles for values, is ambiguous between two interpretations, and both (...) have weaknesses. Fortunately, two elements of Douglas’s work that have previously received much less emphasis provide resources for developing a more promising approach for regulating values in science. (shrink)

Belief and credence are often characterized in three different ways—they ought to govern our actions, they ought to be governed by our evidence, and they ought to aim at the truth. If one of these roles is to be central, we need to explain why the others should be features of the same mental state rather than separate ones. If multiple roles are equally central, then this may cause problems for some traditional arguments about what belief and credence must be (...) like. I read the history of formal and traditional epistemology through the lens of these functional roles, and suggest that considerations from one literature might have a role in the other. The similarities and differences between these literatures may suggest some more general ideas about the nature of epistemology in abstraction from the details of credence and belief in particular. (shrink)

Although epistemic values have become widely accepted as part of scientific reasoning, non-epistemic values have been largely relegated to the "external" parts of science (the selection of hypotheses, restrictions on methodologies, and the use of scientific technologies). I argue that because of inductive risk, or the risk of error, non-epistemic values are required in science wherever non-epistemic consequences of error should be considered. I use examples from dioxin studies to illustrate how non-epistemic consequences of error can and should be considered (...) in the internal stages of science: choice of methodology, characterization of data, and interpretation of results. (shrink)

In this paper we introduce the overlapping design consensus for the construction of models in design and the related value judgments. The overlapping design consensus is inspired by Rawls’ overlapping consensus. The overlapping design consensus is a well-informed, mutual agreement among all stakeholders based on fairness. Fairness is respected if all stakeholders’ interests are given due and equal attention. For reaching such fair agreement, we apply Rawls’ original position and reflective equilibrium to modeling. We argue that by striving for the (...) original position, stakeholders expel invalid arguments, hierarchies, unwarranted beliefs, and bargaining effects from influencing the consensus. The reflective equilibrium requires that stakeholders’ beliefs cohere with the final agreement and its justification. Therefore, the overlapping design consensus is not only an agreement to decisions, as most other stakeholder approaches, it is also an agreement to their justification and that this justification is consistent with each stakeholders’ beliefs. For supporting fairness, we argue that fairness qualifies as a maxim in modeling. We furthermore distinguish values embedded in a model from values that are implied by its context of application. Finally, we conclude that for reaching an overlapping design consensus communication about properties of and values related to a model is required. (shrink)

Deductive Cogency holds that the set of propositions towards which one has, or is prepared to have, a given type of propositional attitude should be consistent and closed under logical consequence. While there are many propositional attitudes that are not subject to this requirement, e.g. hoping and imagining, it is at least prima facie plausible that Deductive Cogency applies to the doxastic attitude involved in propositional knowledge, viz. belief. However, this thought is undermined by the well-known preface paradox, leading a (...) number of philosophers to conclude that Deductive Cogency has at best a very limited role to play in our epistemic lives. I argue here that Deductive Cogency is still an important epistemic requirement, albeit not as a requirement on belief. Instead, building on a distinction between belief and acceptance introduced by Jonathan Cohen and recent developments in the epistemology of understanding, I propose that Deductive Cogency applies to the attitude of treating propositions as given in the context of attempting to understand a given phenomenon. I then argue that this simultaneously accounts for the plausibility of the considerations in favor of Deductive Cogency and avoids the problematic consequences of the preface paradox. (shrink)

I examine how Heather Douglas’ account of values in science applies to the assessment of actual cases of scientific practice. I focus on the case of applied toxicologists’ acceptance of molecular evidence-gathering methods and evidential sources. I demonstrate that a set of social and institutional processes plays a philosophically significant role in changing toxicologists’ inductive risk judgments about different kinds of evidence. I suggest that Douglas’ inductive risk framework can be integrated with a suitable account of evidence, such as Helen (...) Longino’s contextual empiricism, to address the role of social context in the cases like the one examined here. I introduce such an integrated account and show how Longino’s contextual empiricism and inductive risk framework fruitfully complement each other in analyzing the novel aspects of the toxicology case. (shrink)

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)

This paper has two goals. The first is to fill a gap in the literature on inductive risk by exploring the relevance of the notion of inductive risk to macroeconomics and monetary policy. The second goal is to draw some general lessons about inductive risk from the case discussed. The most important of these lessons is that the notion of inductive risk is no less relevant to the relationship between the proximate and distal goals of policy than it is to (...) the relationship between policies and their goals. (shrink)

A popular view in philosophy of science contends that scientific reasoning is objective to the extent that the appraisal of scientific hypotheses is not influenced by moral, political, economic, or social values, but only by the available evidence. A large body of results in the psychology of motivated-reasoning has put pressure on the empirical adequacy of this view. The present study extends this body of results by providing direct evidence that the moral offensiveness of a scientific hypothesis biases explanatory judgment (...) along several dimensions, even when prior credence in the hypothesis is controlled for. Furthermore, it is shown that this bias is insensitive to an economic incentive to be accurate in the evaluation of the evidence. These results contribute to call into question the attainability of the ideal of a value-free science. (shrink)