In this paper, I discuss the objectivity of science in the context of commercialized research. Objectivity has traditionally been associated with the behavior of individual scientists and their willingness and ability to base their reasoning on data and logic. By introducing some examples of problematic practices in current research, I show that this view is insufficient. A view that I call the Social View on objectivity succeeds better in accommodating the way in which commercialization affects research.

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 this paper, I develop and defend a moralized conception of epistemic trust in science against a particular kind of non-moral account defended by John (2015, 2018). I suggest that non-epistemic value considerations, non-epistemic norms of communication and affective trust properly characterize the relationship of epistemic trust between scientific experts and non-experts. I argue that it is through a moralized account of epistemic trust in science that we can make sense of the deep-seated moral undertones that are often at play (...) when non-experts (dis)trust science. (shrink)

Physicist Percy Bridgman has been taken by Heather Douglas to be an exemplar defender of an untenable value-free ideal for science. This picture is complicated by a detailed study of Bridgman's philosophical views of the relation between science and society. The normative autonomy of science, a version of the value-free ideal, is defended. This restriction on the provenance of permissible values in science is given a basis in Bridgman's broader philosophical commitments, most importantly, his view that science is primarily an (...) individual commitment to a set of epistemic norms and values. Considerations of external moral or social values are not, on this view, intrinsic to scientific practice, though they have a broader pragmatic significance. What Bridgman takes as the proper relation between science and society is shown through analysis of his many writings on the topic and consideration of his rarely remarked upon involvement in the most problematic example of "Big Science" of his day: the atomic bomb. A reevaluation of Bridgman's views provides a unique characterization of what is at stake in the values in science debate: the normative autonomy of science. (shrink)

A great many important decisions we make in life depend on scientific information that we are not in a position to assess. So it seems we must defer to experts. By now there are a variety of criteria on offer by which non-experts can judge the trustworthiness of a scientist responsible for producing or promulgating this information. But science is, for the most part, a collective not an individual enterprise. This paper explores which of the criteria for judging the trustworthiness (...) of individual scientists can be amended for use in assessing the trustworthiness of scientific collectives. It also offers some new proposals specifically geared to assessing collective trustworthiness in science, notably, an analysis of where to apply the criteria (for example at the group or individual level) and additional criteria to assess group infrastructure and design. The paper ends with some practical suggestions for how to assist the non-expert in this task. (shrink)

If scientists violate principles and practices of routine science to quickly develop interventions against catastrophic threats, they are engaged in what I call fast science. The magnitude, imminence, and plausibility of a threat justify engaging in and acting on fast science. Yet, that justification is incomplete. I defend two principles to assess fast science, which say: fast science should satisfy as much as possible the reliability-enhancing features of routine science, and the fast science developing an intervention against a threat should (...) not depend on the same problematic assumptions as the fast science which estimates the magnitude, imminence, and plausibility of the threat. (shrink)

In the social epistemology of scientific knowledge, it is largely accepted that relationships of trust, not just reliance, are necessary in contemporary collaborative science characterised by relationships of opaque epistemic dependence. Such relationships of trust are taken to be possible only between agents who can be held accountable for their actions. But today, knowledge production in many fields makes use of AI applications that are epistemically opaque in an essential manner. This creates a problem for the social epistemology of scientific (...) knowledge, as scientists are now epistemically dependent on AI applications that are not agents, and therefore not appropriate candidates for trust. (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)

During emerging public health crises, both policymakers and members of the public are looking to scientific experts to provide guidance. Even in cases where there are significant uncertainties, there is pressure for experts to “speak with one voice” to avoid confusion, allow officials to make evidence-based decisions rapidly, and encourage public support for such decisions. This can lead experts to engage in masking of information about the state of the science or regarding assumptions involved in policy recommendations. Although experts might (...) have good reasons for masking disagreements, uncertainties, or assumptions when offering policy advice, we argue that this strategy can result in epistemic harms. Using the case of the COVID-19 pandemic, we show that public health authorities masked two types of information necessary for laypersons to evaluate public health recommendations: (1) experts’ disagreements about the scientific evidence and (2) the role of values in making inferences from the science to policy positions. We contend that this resulted in epistemic harms against laypeople that provide a pro tanto case against masking information. We further argue that when the science is in flux and policies need to be implemented despite significant uncertainties, there is an all-things-considered case against masking the types of information discussed. (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)

In this paper, I provide an epistemic evaluation of the harms that result from the widespread marketing of direct-to-consumer (DTC) genetic tests. While genetic tests are a valuable accessory diagnostic tool when ordered by a medical practitioner, there are different implications when they are sold directly to consumers. I aim to show that there are both epistemic and non-epistemic harms associated with the widespread commoditization of DTC genetic tests. I argue that the epistemic harms produced by DTC genetic tests have (...) been disregarded in discussions on the topic. Drawing on the notion of contributory epistemic injustices, I highlight two pertinent epistemic harms: (1) a failure to uptake an individual’s articulations about their identity and (2) the presiding reductionist framework dismisses useful hermeneutical resources. I then propose ways to mitigate these harms. (shrink)

Cultural phylogenetics has made remarkable progress by relying on methods originally developed in biology. But biological and cultural evolution do not always proceed according to the same principles. So what, if anything, could justify the use of phylogenetic methods to reconstruct the evolutionary history of culture? In this paper, we describe models used to assess the reliability of inference methods and show how these models play an underappreciated role in addressing that question. The notion of reliability is of course central (...) to these models. As we explain, a common way of understanding reliability is in terms of low error rates. A careful look at case studies in cultural phylogenetics suggests that reliability models partly corroborate this understanding of reliability but also raises points of tension. We conclude by hinting at a few ways forward. (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)

Deep learning (DL) has become increasingly central to science, primarily due to its capacity to quickly, efficiently, and accurately predict and classify phenomena of scientific interest. This paper seeks to understand the principles that underwrite scientists’ epistemic entitlement to rely on DL in the first place and argues that these principles are philosophically novel. The question of this paper is not whether scientists can be justified in trusting in the reliability of DL. While today’s artificial intelligence exhibits characteristics common to (...) both scientific instruments and scientific experts, this paper argues that the familiar epistemic categories that justify belief in the reliability of instruments and experts are distinct, and that belief in the reliability of DL cannot be reduced to either. Understanding what can justify belief in AI reliability represents an occasion and opportunity for exciting, new philosophy of science. (shrink)

Expert knowledge regularly informs personal and civic-decision making. To decide which experts to trust, lay publics —including policymakers and experts from other domains—use different epistemic and non-epistemic cues. Epistemic cues such as honesty, like when experts are forthcoming about conflicts of interest, are a popular way of understanding how people evaluate and decide which experts to trust. However, many other epistemic cues, like the evidence supporting information from experts, are inaccessible to lay publics. Therefore, lay publics simultaneously use second-order social (...) cues in their environment to inform decisions to trust. These second-order social cues, or ‘social indicators of trust’, prevent lay publics from having to trust blindly. Social indicators of trust therefore inform lay publics’ epistemic vigilance, or constant low level-monitoring of testimony from experts. This special issue examines the nature, acquisition and application of social indicators of trust for scientific experts and institutions. It also raises questions about the types of trust asked of lay publics and challenges traditional normative assumptions about the relationship between science and lay publics through study of attitudes, values, and experiences. The issue descriptively re-examines the structure of institutions, their role and methods for ferrying information, as well as how social indicators operate in times of crisis. In this collection of works, we bridge history, science, philosophy of science, science and technology studies, science communication and social epistemology, to broaden the discourse on trust in experts and more accurately reflect the imperfect yet indispensable endeavour that trusting is. (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)

The COVID-19 crisis has highlighted the considerable challenge of sourcing expertise and determining which experts to trust. Dissonant information fostered controversy in public discourse and encouraged an appeal to a wide range of social indicators of trustworthiness in order to decide whom to trust. We analyze public discourse on expertise by examining how social indicators inform the reputation of Dr. Didier Raoult, the French microbiologist who rose to international prominence as an early advocate for using hydroxychloroquine to treat COVID-19. To (...) comprehend how these indicators came to inform his reputation, we outline Dr. Raoult's rise to fame based on discourse about hydroxychloroquine. We then discuss why we trust in experts like scientist-practitioners. This is followed by an examination of how social indicators of trust like status, epistemic authority, influence and values have informed Dr. Raoult's reputation. We conclude with recommendations for how to improve the selection and evaluation social indicators of trust and reputations. Our aim here, instead of making a claim about the efficacy of hydroxychloroquine or Dr. Raoult's reputation per se, is to outline through this case study how social indicators of trust inform reputation and the challenge they present to evaluating expertise. (shrink)

Policy-makers often rely on scientists to inform their decisions. When advising policy-makers, what should scientists say? One view says that scientists ought to say what they have a high credence in. Another view says that scientists ought to say what they expect to lead to good policy outcomes. We explore a third view: scientists ought to say what they expect to make the policy-makers’ credences accurate.

Like any science, archaeology relies on trust between actors involved in the production of knowledge. In the early history of archaeology, this epistemic trust was complicated by histories of Orientalism in the Middle East and colonialism more broadly. The racial and power dynamics underpinning 19th- and early 20th-century archaeology precluded the possibility of interpersonal moral trust between foreign archaeologists and locally hired labourers. In light of this, archaeologists created systems of reward, punishment, and surveillance to ensure the honest behaviour of (...) site workers. They thus invented a set of structural conditions that produced sufficient epistemic trust for archaeological research to proceed—a system that continues to shape archaeology to the present day. (shrink)

Heather Douglas has helped to set the standard for twenty-first century discussions in philosophy of science on the topics of values in science and science in democracy. Douglas’s work has been part of a movement to bring the question of values in science back to center of the field and to focus especially on policy-relevant science. This first chapter, on the pervasive entanglement of science and values, includes an improved and definitive statement of the argument from inductive risk, which she (...) is single-handedly responsible for rehabilitating and returning to the center of the debate. This statement makes clear the fundamental and absolutely pervasive nature of inductive risk and its import for our understanding of the role of values in science. The chapter also provides a survey of the current field of alternative approaches to ideals for the epistemic role of values in science that is comprehensive and generous, yet critical of each. -/- In these brief comments, I focus on providing an alternative perspective on some conceptual and rhetorical issues in Douglas’s account, specifically dealing with the nature of values and the relation of the descriptive and the normative. This will lead me to somewhat different evaluations of two of the five new ideals for values in science that Douglas canvasses in the chapter. (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)

Much work performed under the banner of social epistemology still centers the problems of the individual cognitive agent. AU distinguishes multiple senses of "social," some of which are more social than others, and argues that different senses are at work in various contributions to social epistemology. Drawing on work in history and philosophy of science and addressing the literature on testimony and disagreement in particular, this paper argues for a more thoroughgoing approach in social epistemology.

This article develops an account of distributive epistemic justice in the production of scientific knowledge. We identify four requirements: (a) science should produce the knowledge citizens need in order to reason about the common good, their individual good and pursuit thereof; (b) science should produce the knowledge those serving the public need to pursue justice effectively; (c) science should be organized in such a way that it does not aid the wilful manufacturing of ignorance; and (d) when making decisions about (...) epistemic risks, scientists should make sure that there aren’t social groups or weighty interests that are neglected. After discussing these requirements, we examine the relationship between discriminatory and distributive epistemic injustice in science and argue that they often compound each other. (shrink)

Although the impact of so-called “sponsorship bias” has been the subject of increased attention in the philosophy of science, what exactly constitutes its epistemic wrongness is still debated. In this paper, I will argue that neither evidential accounts nor social–epistemological accounts can fully account for the epistemic wrongness of sponsorship bias, but there are good reasons to prefer social–epistemological to evidential accounts. I will defend this claim by examining how both accounts deal with a paradigm case from medical epistemology, recently (...) discussed in a paper by Bennett Holman. I will argue that evidential accounts cannot adequately capture cases of sponsorship bias that involve the manufacturing of certainty because of their neutrality with respect to the role of non-epistemic values in scientific practice. If my argument holds, it further highlights the importance of integrating social and ethical concerns into epistemological analysis, especially in applied contexts. One can only properly grasp sponsorship bias as an epistemological problem if one resists the methodological tendency to analyze social, ethical, and epistemological issues in isolation from each other. (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)

The paper has two interconnected objectives. It argues that the intrinsic epistemic value of testimonies can be reduced to their moral and social values, that is, to their competent, conscientious, and honest performance. Consequently, competence, conscientiousness, and honesty are intrinsic epistemic values in science. The second objective is to offer an answer to the questions why and under what conditions a hearer can rationally accept a testimony in science. The values and subsequent norms of testimony are espoused and strictly enforced (...) by the scientific community. The norms of testimony ensure that rule-following scientists testify competently, conscientiously, and honestly. Due to value reduction, such testimonies also manifest their intrinsic epistemic value, that is, they serve as evidence for their content. So, if the norms of testimony are followed, then it is epistemically rational to adopt also the norm of the acceptance of testimonies. When the hearer accepts a testimony, he simply—and usually blindly—complies with this norm. Yet, he is epistemically rational because the norm he follows is epistemically rational, as well. (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)

Many philosophers have claimed that relying on the testimony of others in normative questions is in some way problematic. In this paper, I consider whether we should be troubled by deference in democratic politics. I argue that deference is less problematic in impure cases of political deference, and most non-ideal cases of political deference are impure. To establish the second point, I rely on empirical research from political psychology. I also outline two principled reasons why we should expect political deference (...) to be untroubling: political problems are difficult and require a division of epistemic labour; furthermore, there is value in exercising epistemic solidarity with those one shares an identity or interests with. (shrink)

Mathematicians appear to have quite high standards for when they will rely on testimony. Many mathematicians require that a number of experts testify that they have checked the proof of a result p before they will rely on p in their own proofs without checking the proof of p. We examine why this is. We argue that for each expert who testifies that she has checked the proof of p and found no errors, the likelihood that the proof contains no (...) substantial errors increases because different experts will validate the proof in different ways depending on their background knowledge and individual preferences. If this is correct, there is much to be gained for a mathematician from requiring that a number of experts have checked the proof of p before she will rely on p in her own proofs without checking the proof of p. In this way a mathematician can protect her own work and the work of others from errors. Our argument thus provides an explanation for mathematicians’ attitude towards relying on testimony. (shrink)

I examine ramifications of the widespread view that scientific objectivity gives us a permission to trust scientific knowledge claims. According to a widely accepted account of trust and trustworthiness, trust in scientific knowledge claims involves both reliance on the claims and trust in scientists who present the claims, and trustworthiness depends on expertise, honesty, and social responsibility. Given this account, scientific objectivity turns out to be a hybrid concept with both an epistemic and a moral-political dimension. The epistemic dimension tells (...) us when scientific knowledge claims are reliable, and the moral-political dimension tells us when we can trust scientists to be socially responsible. While the former dimension has received a fair amount of attention, the latter is in need of analysis. I examine what it means for scientists to be socially responsible, that is, to follow “sound” moral and social values in different stages of scientific inquiry. Social responsibility is especially important when scientists function as experts in society. Members of the public and policymakers do not want to rely on scientific research shaped by moral and social values they have good reasons to reject. Moreover, social responsibility is important in social research in which moral and social values can legitimately play many roles. I discuss the strengths and weaknesses of different answers to the question of how social scientists can identify appropriate moral and social values to inform their research. I argue that procedural accounts of social responsibility, such as well-ordered science and deliberative polling, have limitations. (shrink)

Biased research occurs frequently in the sciences. In this paper, I will focus on one particular kind of biased research: research that is subject to sponsorship bias. I will address the following epistemological question: what precisely is epistemically wrong with biased research of this kind? I will defend the evidential account of epistemic wrongness: that is, research affected by sponsorship bias is epistemically wrong if and only if the researchers in question make false claims about the evidential support of some (...) hypothesis H by data E. I will argue that the evidential account captures the epistemic wrongness of three paradigmatic types of sponsorship bias. (shrink)

We provide an analysis of the public's having warranted epistemic trust in science, that is, the conditions under which the public may be said to have well-placed trust in the scientists as providers of information. We distinguish between basic and enhanced epistemic trust in science and provide necessary conditions for both. We then present the controversy regarding the connection between autism and measles–mumps–rubella vaccination as a case study to illustrate our analysis. The realization of warranted epistemic public trust in science (...) requires various societal conditions, which we briefly introduce in the concluding section. (shrink)

Replicability is widely taken to ground the epistemic authority of science. However, in recent years, important published findings in the social, behavioral, and biomedical sciences have failed to replicate, suggesting that these fields are facing a “replicability crisis.” For philosophers, the crisis should not be taken as bad news but as an opportunity to do work on several fronts, including conceptual analysis, history and philosophy of science, research ethics, and social epistemology. This article introduces philosophers to these discussions. First, I (...) discuss precedents and evidence for the crisis. Second, I discuss methodological, statistical, and social-structural factors that have contributed to the crisis. Third, I focus on the philosophical issues raised by the crisis. Finally, I discuss proposed solutions and highlight the gaps that philosophers could focus on. (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)

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)

Health care systems can positively influence our personal decision-making and health-related behavior only if we trust them. I propose a conceptual analysis of the trust relation between the public and a healthcare system, drawing from healthcare studies and philosophical proposals. In my account, the trust relation is based on an epistemic component, epistemic authority, and on a value component, the benevolence of the healthcare system. I argue that it is also modified by the vulnerability of the public on healthcare matters, (...) and by the system’s credibility. I apply my proposed analysis of public trust in health care systems to the phenomenon of vaccine hesitancy, a tendency to question vaccine policies, and to seek alternative vaccine schedules or to refuse vaccination. Understanding the role of trust and its components can be key to understanding the phenomenon. (shrink)

Building, restoring and maintaining well-placed trust between scientists and the public is a difficult yet crucial social task requiring the successful cooperation of various social actors and institutions. Kitcher’s takes up this challenge in the context of liberal democratic societies by extending his ideal model of “well-ordered science” that he had originally formulated in his. However, Kitcher nowhere offers an explicit account of what it means for the public to invest epistemic trust in science. Yet in order to understand how (...) his extended model and its implementation in the actual world address the problem of trust as well as to evaluate it critically, an explicit account of epistemic public trust in science needs to be given first. In this article we first present such an account and then scrutinize his project of building public trust in science in light of it. We argue that even though Kitcher’s ideal model and his proposals for its implementation in the real world face a number of problems, they can be addressed with the resources of our account. (shrink)

These preprints were automatically compiled into a PDF from the collection of papers deposited in PhilSci-Archive in conjunction with the PSA 2018.

Experimental design is one aspect of a scientific method. A well-designed, properly conducted experiment aims to control variables in order to isolate and manipulate causal effects and thereby maximize internal validity, support causal inferences, and guarantee reliable results. Traditionally employed in the natural sciences, experimental design has become an important part of research in the social and behavioral sciences. Experimental methods are also endorsed as the most reliable guides to policy effectiveness. Through a discussion of some of the central concepts (...) associated with experimental design, including controlled variation and randomization, this chapter will provide a summary of key ethical issues that tend to arise in experimental contexts. In addition, by exploring assumptions about the nature of causation and by analyzing features of causal relationships, systems, and inferences in social contexts, this chapter will summarize the ways in which experimental design can undermine the integrity of not only social and behavioral research but policies implemented on the basis of such research. (shrink)

In this paper we address the question of how it can be possible for a non-expert to acquire justified true belief from expert testimony. We discuss reductionism and epistemic trust as theoretical approaches to answer this question and present a novel solution that avoids major problems of both theoretical options: Performative Expert Testimony (PET). PET draws on a functional account of expertise insofar as it takes the expert’s visibility as a good informant capable to satisfy informational needs as equally important (...) as her specific skills and knowledge. We explain how PET generates justification for testimonial belief, which is at once assessable for non-experts and maintains the division of epistemic labor between them and the experts. Thereafter we defend PET against two objections. First, we point out that the non-expert’s interest in acquiring widely assertable true beliefs and the expert’s interest in maintaining her status as a good informant counterbalances the relativist account of justification at work in PET. Second, we show that with regard to the interests at work in testimonial exchanges between experts and non-experts, PET yields a better explanation of knowledge-acquisition from expert testimony than externalist accounts of justification such as reliabilism. As our arguments ground in a conception of knowledge, which conceives of belief-justification as a declarative speech act, throughout the rearmost sections of this paper we also indicate to how such a conception is operationalized in PET. (shrink)

. Science at the interface with society is regarded with mistrust among parts of the public. Scientific judgments on matters of practical concern are not infrequently suspected of being incompetent and biased. I discuss two proposals for remedying this deficiency. The first aims at strengthening the independence of science and suggests increasing the distance to political and economic powers. The drawback is that this runs the risk of locking science in an academic ivory tower. The second proposal favors “counter-politicization” in (...) that research is strongly focused on projects “in the public interest,” that is, on projects whose expected results will benefit all those concerned by these results. The disadvantage is that the future use of research findings cannot be delineated reliably in advance. I argue that the underlying problem is the perceived lack of relevance and reliability and that pluralism is an important step toward its solution. Pluralism serves to stimulate a more inclusive research agenda and strengthens the well-testedness of scientific approaches. However, pluralism also prevents the emergence of clear-cut practical suggestions. Accordingly, pluralism is part of the solution to the credibility crisis of science, but also part of the problem. In order for science to be suitable as a guide for practice, the leeway of scientific options needs to be narrowed – in spite of uncertainty in epistemic respect. This reduction can be achieved by appeal to criteria that do not focus on the epistemic credentials of the suggestions but on their appropriateness in practical respect. (shrink)

In their attempt to defend philosophy from accusations of uselessness made by prominent scientists, such as Stephen Hawking, some philosophers respond with the charge of ‘scientism.’ This charge makes endorsing a scientistic stance, a mistake by definition. For this reason, it begs the question against these critics of philosophy, or anyone who is inclined to endorse a scientistic stance, and turns the scientism debate into a verbal dispute. In this paper, I propose a different definition of scientism, and thus a (...) new way of looking at the scientism debate. Those philosophers who seek to defend philosophy against accusations of uselessness would do philosophy a much better service, I submit, if they were to engage with the definition of scientism put forth in this paper, rather than simply make it analytic that scientism is a mistake. (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)

The problem this paper addresses is that scientists have to take normatively charged decisions which can have a significant impact on individual members of the public or the public as a whole. And yet mechanisms to exercise democratic control over them are often absent. Given the normative nature of these choices, this is often perceived to be at odds with basic democratic principles. I show that this problem applies in similar ways to civil service institutions and draw on political philosophy (...) literature on the civil service (e.g. Rosanvallon, 2011; Heath, 2022) to discuss when such normative judgements can nevertheless be said to be democratically legitimate. Concretely, I seek to show that normative judgements in research need not be democratically legitimated in order for science to be democratically legitimate. Indeed, it can be democratically legitimate for scientists to go against the expressed views of the public or political representatives if this is justified in light of, firstly, the role science has been asked to fulfil and, secondly, when it is in line with public institutions’ key principles. This is a counter-position to views currently held in the values in science debate (e.g. by Kitcher, 2011; Intemann, 2015; Schroeder, 2021; Lusk, 2021) which argue that value-laden judgements in science are legitimate if they are aligned with the public’s views or directly decided by public. (shrink)

Several science studies scholars report instances of scientific “hype,” or sensationalized exaggeration, in journal articles, institutional press releases, and science journalism in a variety of fields (e.g., Caulfield and Condit 2012). Yet, how “hype” is being conceived varies. I will argue that hype is best understood as a particular kind of exaggeration, one that explicitly or implicitly exaggerates various positive aspects of science in ways that undermine the goals of science communication in a particular context. This account also makes clear (...) the ways that value judgments play a role in judgments of “hype,” which has implications for detecting and addressing this problem. (shrink)