There is increasing attention to the centrality of idealization in science. One common view is that models and other idealized representations are important to science, but that they fall short in one or more ways. On this view, there must be an intermediary step between idealized representation and the traditional aims of science, including truth, explanation, and prediction. Here I develop an alternative interpretation of the relationship between idealized representation and the aims of science. In my view, continuing, widespread idealization (...) calls into question the idea that science aims for truth. I argue that understanding must replace truth as the ultimate epistemic aim of science. Additionally, science has a wide variety aims, epistemic and non-epistemic, and these aims motivate different kinds of scientific products. Finally, I show how these diverse aims---all rather distant from truth---result in the expanded influence of social values on science. (shrink)

Recent efforts to argue that nonepistemic values have a legitimate role to play in assessing scientific models, theories, and hypotheses typically either reject the distinction between epistemic and nonepistemic values or incorporate nonepistemic values only as a secondary consideration for resolving epistemic uncertainty. Given that scientific representations can legitimately be evaluated not only based on their fit with the world but also with respect to their fit with the needs of their users, we show in two case studies that nonepistemic (...) values can play a legitimate role as factors that override epistemic considerations in assessing scientific representations for practical purposes. (shrink)

Although the philosophical literature on science and values has flourished in recent years, the central concept of “values” has remained ambiguous. This paper endeavors to clarify the nature of values as they are discussed in this literature and then highlights some of the major implications of this clarification. First, it elucidates four major concepts of values and discusses some of their strengths and weaknesses. Second, it clarifies the relationships between these concepts of values and a wide variety of related concepts (...) that are sometimes used interchangeably in the philosophical literature. Third, it argues that this conceptual clarification reveals that much of the literature on science and values has discussed different concepts of values without making these differences clear. The paper illustrates this point by analyzing the different concepts of values at play in different arguments against the value-free ideal and in proposals for managing values. Understanding the literature on values in science as a patchwork of related discourses rather than a single discourse can help researchers more thoughtfully choose a concept of values that best fits their philosophical targets and goals, rather than conflating different discourses because of the common terminology of “values.”. (shrink)

Engineering accident investigations are systematic inquiries into the facts and causes of engineering accidents. The aims of an engineering accident investigation include identifying significant truths about an accident, learning lessons to prevent similar future accidents, and authoritatively communicating the investigative results to the stakeholders. An important normative dimension along which an engineering accident investigation can be evaluated is its degree of success in fulfilling these aims. In this paper, I propose criteria for evaluating the degree of success of an engineering (...) accident investigation using a question-centered framework, and then argue for the relevance of this proposal to the actual engineering practice. The basic idea of my proposal is that an engineering accident investigation is successful to the extent that (1) questions that should arise in the investigation do arise, and (2) questions that arise—especially the more significant ones—are resolved satisfactorily by the end of the investigation. The first part of this paper unpacks my proposal by analyzing the following three concepts and illustrating them using examples from the TWA Flight 800 accident investigation: The (satisfactory) resolution of questions, the significance of questions, and the arising of questions. The second part of this paper argues for the relevance of my proposal to the practitioners and stakeholders of engineering accident investigations. First, I argue that my proposal is sensitive to the aims of the investigators and stakeholders regarding engineering accident investigations, and that it helps them navigate competing and conflicting aims. Second, I go beyond the TWA 800 case study and argue that my proposal explains the strengths and limitations of different types of accident causation models used in investigations. (shrink)

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

This paper presents a program of action for the philosophy of regulatory science, based on a general theory of social epistemology. Two candidates are considered. The first one, offered by Alvin Goldman, is not fit for our purposes because it is focused on a veritism incompatible with non‐epistemic aims of regulatory science. The second, championed by Steve Fuller, sociologically investigates the existing means of producing knowledge, to modify them with the goal of obtaining democratic aims through action on a legislative (...) meta‐level. The program has been built upon this procedure, instantiated by the identification, characterization, and modification of epistemic policies. (shrink)

The anti-psychiatry movement of the 20th century has notably denounced the role of values and social norms in the shaping of psychiatric categories. Recent activist movements also recognize that psychiatry is value-laden, however, they do not fight for a value-free psychiatry. On the contrary, some activist movements of the 21st century advocate for self-advocacy in sciences of mental health in order to reach a more accurate understanding of psychiatric categories/mental distress. By aiming at such epistemic gain, they depart from the (...) anti-psychiatry movement. Through the analysis of the epistemic and political influence of two of these movements – Neurodiversity and the Mad Studies, we show how this new activism has taken a scientific turn compatible with current philosophical scientific frameworks, while still developing a critical approach on psychiatry. (shrink)

There is much debate on how social values should influence scientific research. However, the question of practical applicability of philosophers’ normative proposals has received less attention. Here, we test the attainability of Matthew J. Brown’s (2020) Moral Imagination ideal (MI ideal), which aims to help scientists to make warranted value-judgements through reflecting on goals, options, values, and stakeholders of research. Here, the tools of the MI ideal are applied to a climate modelling setting, where researchers are developing aerosol-cloud interaction (ACI) (...) parametrizations in an Earth System Model with the broader goal of improving climate sensitivity estimation. After the identification of minor obstacles to applying the MI ideal, we propose two ways to increase its applicability. First, its tools should be accompanied with more concrete guidance for identifying how social values enter more technical decisions in scientific research. Second, since research projects can have multiple goals, examining the alignment between broader societal aims of research and more technical goals should be part of the tools of the MI ideal. (shrink)

The argument from inductive risk is considered to be one of the strongest challenges for value-free science. A great part of its appeal lies in the idea that even an ideal epistemic agent—the “perfect scientist” or “scientist qua scientist”—cannot escape inductive risk. In this paper, I scrutinize this ambition by stipulating an idealized Bayesian decision setting. I argue that inductive risk does not show that the “perfect scientist” must, descriptively speaking, make non-epistemic value-judgements, at least not in a way that (...) undermines the value-free ideal. However, the argument is more successful in showing that there are cases where the “perfect scientist” should, normatively speaking, use non-epistemic values. I also show that this is possible without creating problems of illegitimate prescription and wishful thinking. Thus, while inductive risk does not refute value-freedom completely, it still represents a powerful critique of value-free science. (shrink)

In “Should We Strive to Make Science Bias‑Free? A Philosophical Assessment of the Reproducibility Crisis”, I argue that the problem of bias in science, a key factor in the current reproducibility crisis, is worsened if we follow Heather Douglas and Kevin C. Elliott’s advice and introduce non-epistemic values into the evidential assessment of scientific hypotheses. In their response to my paper, Douglas and Elliott complain that I misrepresent their views and fall victim to various confusions. In this rebuttal I argue, (...) by means of an examination of their published views, that my initial interpretation of their work is accurate and that, in their hands, science is generally prone to deviations from truth. (shrink)

This paper advocates for making epistemic interests a central object of philosophical analysis in epistemology and philosophy of science. It is argued that the importance of epistemic interests derives from their fundamental importance for the notion of objectivity. Epistemic interests are defined as individuated by a set of objectives, each of which represents a dimension of the search for truth. Among these dimensions, specificity, sensitivity, and productivity are discussed in detail. It is argued that the relevance of productivity is often (...) overlooked in debates about the ends and means of science. A definition of the objectivity of inquiry is proposed that takes the notion of epistemic interest as its starting point. (shrink)

I address options for providing scientific policy advice and explore the relation between scientific knowledge and political, economic and moral values. I argue that such nonepistemic values are essential for establishing the significance of questions and the relevance of evidence, while, on the other hand, such social choices are the prerogative of society. This tension can be resolved by recognizing social values and identifying them as separate premises or as commissions while withholding commitment to them, and by elaborating a plurality (...) of policy packages that envisage the implementation of different social goals. There are limits to upholding the value-free ideal in scientific research. But by following the mentioned strategy, science can give useful policy advice by leaving the value-free ideal largely intact. Such scientific restraint avoids the risk of appearing to illegitimately impose values on the public and could make the advice given more trustworthy. (shrink)

In the past few years, social epistemologists have developed several formal models of the social organisation of science. While their robustness and representational adequacy has been analysed at length, the function of these models has begun to be discussed in more general terms only recently. In this article, I will interpret many of the current formal models of the scientific community as representing the latest development of what I will call the ‘Kuhnian project’. These models share with Kuhn a number (...) of questions about the relation between individuals and communities. At the same time, they also inherit some of Kuhn’s problematic characterisations of the scientific community. In particular, current models of the social organisation of science represent the scientific community as essentially value-free. This may put into question both their representational adequacy and their normative ambitions. In the end, it will be shown that the discussion on the formal models of the scientific community may contribute in fruitful ways to the ongoing debates on value judgements in science. (shrink)

Anti-ageing medicines are products intended to extend lifespan and healthspan in humans that have a good potential use in public health policies. In the European Union, their development, production and consumption are dependent on regulatory science performed by the European Medicines Agency and its associated epistemic policies. They impose, among other things, an unfavourable burden of proof, a strict standard of proof and meta-methodological constrictions related to some theoretical issues. This results in a distribution of errors that tends to reduce (...) false positives while increasing false negatives, leading to a set of social consequences that are generally accepted when the focus is placed on conventional medicines. However, when the same epistemic policies are applied to anti-ageing medicines, the distribution of errors is imbalanced, and undesirable outcomes like research discouragement and waiting time extensions appear. Three possible strategies that policymakers could implement to unblock the situation are presented for future reflection: the consideration of ageing as a disease, the application of methodological asymmetry and the use of biomarkers during clinical research. (shrink)

Simple idealized models seem to provide more understanding than opaque, complex, and hyper-realistic models. However, an increasing number of scientists are going in the opposite direction by utilizing opaque machine learning models to make predictions and draw inferences, suggesting that scientists are opting for models that have less potential for understanding. Are scientists trading understanding for some other epistemic or pragmatic good when they choose a machine learning model? Or are the assumptions behind why minimal models provide understanding misguided? In (...) this paper, using the case of deep neural networks, I argue that it is not the complexity or black box nature of a model that limits how much understanding the model provides. Instead, it is a lack of scientific and empirical evidence supporting the link that connects a model to the target phenomenon that primarily prohibits understanding. (shrink)

This response addresses the excellent responses to my book provided by Heather Douglas, Janet Kourany, and Matt Brown. First, I provide some comments and clarifications concerning a few of the highlights from their essays. Second, in response to the worries of my critics, I provide more detail than I was able to provide in my book regarding my three conditions for incorporating values in science. Third, I identify some of the most promising avenues for further research that flow out of (...) this interchange. (shrink)

Courts have determined that adaptive management does not satisfy the Endangered Species Act's requirement to use the ‘best available science’. This is due, in part, to the failure to recognise the role of non-epistemic values in science. We examine the role of values in the legal controversy over the scientific reports and adaptive management plans for endangered salmon in the Columbia River Basin. To do this, we employ philosophical concepts related to risk and uncertainty that demonstrate how non-epistemic values are (...) internal to science. We describe how, because adaptive management is a method for dealing with inductive risk, by remaining flexible, responsive and adaptive in those circumstances where the costs of making a mistake are very high, it requires special attention to ensure that it remains useful. We conclude that, because non-epistemic values will inevitably influence the ‘best available science’, it is critical that they are clarified in any adaptive management planning so that we can ensure the salmon conservation that the ESA mandates. Fortunately, because adaptive management is iterative in nature and includes opportunities for engagement between policymakers and scientists, it enables clarification of non-epistemic values through making standards of evidence transparent, acknowledging aims and goals and dealing with uncertainty at the institutional level. (shrink)

While it is widely acknowledged that science is not “free” of non-epistemic values, there is disagreement about the roles that values can appropriately play. Several have argued that non-epistemic values can play important roles in modeling decisions, particularly in addressing uncertainties ; Risbey 2007; Biddle and Winsberg 2010; Winsberg : 111-137, 2012); van der Sluijs 359-389, 2012). On the other hand, such values can lead to bias ; Bray ; Oreskes and Conway 2010). Thus, it is important to identify when (...) it is legitimate to appeal to non-epistemic values in modeling decisions. An approach is defended here whereby such value judgments are legitimate when they promote democratically endorsed epistemological and social aims of research. This framework accounts for why it is legitimate to appeal to non-epistemic values in a range of modeling decisions, while addressing concerns that the presence of such values will lead to bias or give scientists disproportionate power in deciding what values ought to be endorsed. (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 aim of this article is to critically build on Justin Biddle and Anna Leuschner’s characterization of epistemologically detrimental dissent in the context of science. We argue that the presence of nonepistemic agendas and severe nonepistemic consequences offers neither necessary nor sufficient conditions for EDD to obtain. We clarify their role by arguing that they are contingent enabling factors, not stable difference-makers, in the production of EDD. We maintain that two stable difference-makers are core to the production of EDD: production (...) of skewed science and effective public dissemination. (shrink)

The argument from inductive risk has been embraced by many as a successful account of the role of values in science that challenges the value-free ideal. We argue that it is not obvious that the argument from inductive risk actually undermines the value-free ideal. This is because the inductive risk argument endorses an assumption held by proponents of the value-free ideal: that contextual values never play an appropriate role in determining evidence. We show that challenging the value-free ideal ultimately requires (...) rejecting this assumption. (shrink)

Much of the literature on values in science is limited in its perspective because it focuses on the role of values in individual scientists’ decision making, thereby ignoring the context of scientific collaboration. I examine the epistemic structure of scientific collaboration and argue that it gives rise to two arguments showing that moral and social values can legitimately play a role in scientists’ decision to accept something as scientific knowledge. In the case of scientific collaboration some moral and social values (...) are properly understood to be extrinsic epistemic values, that is, values that promote the attainment of scientific knowledge. (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)

Current debates over inductive risk and the role of values in science have largely revolved around the question of the moral responsibilities of scientists: Do scientists have the duty to consider the potential non-epistemic consequences of theories they advocate and, if yes, what values should be taken into account in decision-making? The paper discusses two different – though potentially complementary – responses to this question: a) H. Douglas’s view that scientists should avoid causing reckless or negligent harm to others as (...) a result of the decisions they make and b) K. Elliott’s Multiple Goals Criterion. Drawing from the case of potential coronavirus transmission by sharing the Holy Communion that recently divided Greek society and medical experts, it shows the tensions emerging between autonomy and the moral responsibilities of scientists, when the boundaries of science are blurred and the epistemic goal of truth is inconsistent with alternative goals. It argues that the balance attempted between scientific principles and religious beliefs was unattainable and concludes that the need to distinguish between epistemic and non-epistemic values, which is traditionally related to the ideal of value free science, should be reconsidered and even prioritized among the responsibilities of scientists. (shrink)

A general criterion for distinguishing between epistemic and non-epistemic values is that the former promotes the attainment of truth whereas the latter does not. Daniel Steel is a proponent of this criterion, although it was initially proposed by McMullin. There are at least two consequences of this criterion; it always prioritizes epistemic values over non-epistemic values in scientific research, and it overlooks the diverse aims of science, especially the aims of regulatory or policy-oriented science. This criterion assumes the lexical priority (...) of truth or lexical priority of evidence. This paper attempts to show a few inadequacies of this assumption. The paper also demonstrates why epistemic priority over non-epistemic values is a problematic stance and how constraining the role of non-epistemic values as ‘tiebreakers’ may undermine the diverse aims of science. (shrink)

Solving the “new demarcation problem” requires a distinction between epistemically legitimate and illegitimate roles for non-epistemic values in science. This paper addresses one ‘half’ (i.e. a sub-problem) of the new demarcation problem articulated by the Gretchenfrage: What makes the role of a non-epistemic value in science epistemically illegitimate? I will argue for the Explaining Epistemic Errors (EEE) account, according to which the epistemically illegitimate role of a non-epistemic value is defined via an explanatory claim: the fact that an epistemic agent (...) is motivated by a non-epistemic value explains why the epistemic agent commits a particular epistemic error. The EEE account is inspired by Douglas’ and Steel’s “functionalist” or “epistemic constraint” accounts of epistemic illegitimacy. I will suggest that the EEE account is able to meet two challenges that these two accounts face, while preserving the key intuition underlying both accounts. If my arguments succeed, then the EEE account provides a solution to one half of the new demarcation problem (by providing a definition of what makes the role of a non-epistemic value epistemically illegitimate) and it opens up new ways for addressing the other half (i.e. characterizing an epistemically legitimate role for non-epistemic values). (shrink)

Responsible research and innovation features the dialog of science “with society,” and research performed “for society,” i.e., for the benefit of the people. I focus on this latter, outcome-oriented notion of RRI and discuss two kinds of problems. The first one concerns options to anticipate the future course of science and technology. Such foresight knowledge seems necessary for subjecting research to demands of social and moral responsibility. However, predicting science and technology is widely considered impossible. The second problem concerns moral (...) evaluation. The benefit or harm produced by certain research and innovation achievements is often hard to estimate. Against this background of uncertainty in factual and moral assessment, I explore opportunities left for RRI. First, RRI should contribute to maintaining a wide range of approaches. Second, judgments about RRI should draw on zones of convergence among the variety of research approaches pursued. Third, decisions about implementing a technology should be revisable. Fourth, the more specific inclusion of demands from society should be reserved to technology development. Fifth, in many respects, the social compatibility of a new technology is due rather to the social context than the inherent features of the product. Favorable circumstances are transparency, representation of all relevant parties, and procedural fairness. As a result, some of the benefits and detriments of research and innovation can be identified without detailed knowledge of future findings. (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)

The standard view on economics imperialism is that it should be resisted when it is epistemically or morally harmful. I argue that the moral dimension of economics imperialism is in need of further analysis. In my view, economics imperialism is wrong when imperialists violate the epistemic responsibility they have towards scientists working in the discipline that is the target for imperialist explorations. By epistemic responsibility, I refer to a moral duty to justify one’s knowledge claims to a particular audience so (...) that the justification appeals to at least some of the standards of argumentation recognized by that audience. (shrink)

Within the context of the discussion about value-free science ideal, Heather Douglas claims that in several cases non-epistemic values are needed for good reasoning in science. In this article I aim at recovering her viewpoint in order to examine the research driving to the Genetic Grandparent Inclusion-Probability Index, a crucial element to restitute the identity of children who were abducted during Argentinean dictatorship. Thus, my purposes are to reconstruct Douglas´ main theoretical contributions, specifically her reasons to reject the ideal as (...) well as the distinction between direct and indirect roles for values in science; and to analyze the scientific paper resulting from the “Grandparent-Inclusion Index” research. The main hypothesis is that several decisions of this research, particularly the establishment of what is to be considered sufficient evidence, should be explained by reference to social, ethical and political values. Both because of the non-epistemic consequences of the inquiry related to its inductive risk and because such inquiry is a case in which there is legitimate and necessary integration between epistemic and non-epistemic values and that it is also a case in which Douglas’ criteria of objectivity is reached. By virtue of these reasons, the significance of Douglas’ contribution to the analysis of the relationship between science and politics is emphasized. (shrink)

The function and legitimacy of values in decision making is a critically important issue in the contemporary analysis of science. It is particularly relevant for some of the more application-oriented areas of science, specifically decision-oriented science in the field of regulation of technological risks. Our main objective in this paper is to assess the diversity of roles that non-cognitive values related to decision making can adopt in the kinds of scientific activity that underlie risk regulation. We start out, first, by (...) analyzing the issue of values with the help of a framework taken from the wider philosophical debate on science and values. Second, we study the principal conceptualizations used by scholars who have applied them to numerous case studies. Third, we appraise the links between those conceptualizations and learning processes in decision-oriented science. In this, we recur to the concept of methodological learning, i.e., learning about the best methodologies for generating knowledge that is useful for science-based regulatory decisions. The main result of our analysis is that non-cognitive values can contribute to methodological improvements in science in three principal ways: as basis for critical analysis, for contextualizing methodologies, and for establishing the burden of proof. (shrink)

This article examines the relevance of survey data of scientists’ attitudes about science and values to case studies in philosophy of science. We describe two methodological challenges confronting such case studies: 1) small samples, and 2) potential for bias in selection, emphasis, and interpretation. Examples are given to illustrate that these challenges can arise for case studies in the science and values literature. We propose that these challenges can be mitigated through an approach in which case studies and survey methods (...) are viewed as complementary, and use data from the Toolbox Dialogue Initiative to illustrate this claim. (shrink)

The purpose of this paper is to discuss Miller’s recent claim that 1) the ideal of value-freedom is implausible because evidence from experimental psychology reveals how scientific reasoning is val...

In this article, I offer a partial analysis of the role of values in qualitative data collection in social research. The partial analysis shows that nonepistemic values have both required and permissible roles to play during this phase of research. By appeal to the analysis, I reject the ideal of value-free science as applied to qualitative data collection, and I demonstrate why two alternative ideals should likewise be dismissed as standards for values in qualitative data collection. Also, I briefly discuss (...) the extent to which the partial analysis carries over to quantitative data collection in social research. (shrink)