Moral, social, political, and other “nonepistemic” values can lead to bias in science, from prioritizing certain topics over others to the rationalization of questionable research practices. Such values might seem particularly common or powerful in the social sciences, given their subject matter. However, I argue first that the well-documented phenomenon of motivated reasoning provides a useful framework for understanding when values guide scientific inquiry (in pernicious or productive ways). Second, this analysis reveals a parity thesis: values influence the (...) social and natural sciences about equally, particularly because both are so prominently affected by desires for social credit and status, including recognition and career advancement. Ultimately, bias in natural and social science is both natural and social— that is, a part of human nature and considerably motivated by a concern for social status (and its maintenance). Whether the pervasive influence of values is inimical to the sciences is a separate question. (shrink)

This textbook is a comprehensive, engaging, and user-friendly introduction to philosophy of science written by a philosopher and a scientist. By exploring traditional debates within philosophy of science, as well as analysing contemporary scientific controversies for philosophical bias, the reader is invited to reflect upon how philosophical assumptions influence scientific theory, methods, and practice. -/- Key features: -/- - Is an accessible introduction to philosophy of science written by a philosopher and a scientist. - (...) Includes some of the many important contributions from women philosophers and scientists. - Demonstrates the philosophical influences on scientific thinking, practice, and expert disagreement. - Applies philosophy of science to analyse some specific real-life cases of scientific controversy. -/- This book is an essential resource for students and teachers in philosophy of science. It is also ideal for anyone interested in the philosophical influences on contemporary science. (shrink)

It is often argued that while biases routinely influence the generation of scientific theories, a subsequent rational evaluation of such theories will ensure that biases do not affect which theories are ultimately accepted. Against this line of thought, this paper shows that the existence of certain kinds of biases at the generation-stage implies the existence of biases at the evaluation-stage. The key argumentative move is to recognize that a scientist who comes up with a new theory about some phenomena has (...) thereby gained an unusual type of evidence, viz. information about the space of theories that could be true of the phenomena. It follows that if there is bias in the generation of scientific theories in a given domain, then the rational evaluation of theories with reference to the total evidence in that domain will also be biased. (shrink)

The underrepresentation of women, people of color, and especially women of color—and the corresponding overrepresentation of white men—is more pronounced in philosophy than in many of the sciences. I suggest that part of the explanation for this lies in the role played by the idealized rational self, a concept that is relatively influential in philosophy but rarely employed in the sciences. The idealized rational self models the mind as consistent, unified, rationally transcendent, and introspectively transparent. I hypothesize that acceptance of (...) the idealized rational self leads philosophers to underestimate the influence of implicit bias on their own judgments and prevents them from enacting the reforms necessary to minimize the effects of implicit bias on institutional decision-making procedures. I consider recent experiments in social psychology that suggest that an increased sense of one’s own objectivity leads to greater reliance on bias in hiring scenarios, and I hypothesize how these results might be applied to philosophers’ evaluative judgments. I discuss ways that the idealized rational self is susceptible to broader critiques of ideal theory, and I consider some of the ways that the picture functions as a tool of active ignorance and color-evasive racism. (shrink)

Many scientists routinely generalize from study samples to larger populations. It is commonly assumed that this cognitive process of scientific induction is a voluntary inference in which researchers assess the generalizability of their data and then draw conclusions accordingly. We challenge this view and argue for a novel account. The account describes scientific induction as involving by default a generalization bias that operates automatically and frequently leads researchers to unintentionally generalize their findings without sufficient evidence. The result is unwarranted, (...) overgeneralized conclusions. We support this account of scientific induction by integrating a range of disparate findings from across the cognitive sciences that have until now not been connected to research on the nature of scientific induction. The view that scientific induction involves by default a generalization bias calls for a revision of the current thinking about scientific induction and highlights an overlooked cause of the replication crisis in the sciences. Commonly proposed interventions to tackle scientific overgeneralizations that may feed into this crisis need to be supplemented with cognitive debiasing strategies against generalization bias to most effectively improve science. (shrink)

What is the status of research on implicit bias? In light of meta‐analyses revealing ostensibly low average correlations between implicit measures and behavior, as well as various other psychometric concerns, criticism has become ubiquitous. We argue that while there are significant challenges and ample room for improvement, research on the causes, psychological properties, and behavioral effects of implicit bias continues to deserve a role in the sciences of the mind as well as in efforts to understand, and ultimately (...) combat, discrimination and inequality. (shrink)

Psychologists and philosophers have not yet resolved what they take implicit attitudes to be; and, some, concerned about limitations in the psychometric evidence, have even challenged the predictive and theoretical value of positing implicit attitudes in explanations for social behavior. In the midst of this debate, prominent stakeholders in science have called for scientific communities to recognize and countenance implicit bias in STEM fields. In this paper, I stake out a stakeholder conception of implicit bias that responds (...) to these challenges in ways that are responsive to the psychometric evidence, while also being resilient to the sorts of disagreements and scientific progress that would not undermine the soundness of this call. Along the way, my account advocates for attributing collective (group-level) implicit attitudes rather than individual-level implicit attitudes. This position raises new puzzles for future research on the relationship (metaphysical, epistemic, and ethical) between collective implicit attitudes and individual-level attitudes. (shrink)

The concept of bias is pervasive in both popular discourse and empirical theorizing within philosophy, cognitive science, and artificial intelligence. This widespread application threatens to render the concept too heterogeneous and unwieldy for systematic investigation. This article explores recent philosophical literature attempting to identify a single theoretical category—termed ‘bias’—that could be unified across different contexts. To achieve this aim, the article provides a comprehensive review of theories of bias that are significant in the fields of (...) philosophy of mind, cognitive science, machine learning, and epistemology. It focuses on key examples such as perceptual bias, implicit bias, explicit bias, and algorithmic bias, scrutinizing their similarities and differences. Although these explorations may not conclusively establish the existence of a natural theoretical kind, pursuing the possibility offers valuable insights into how bias is conceptualized and deployed across diverse domains, thus deepening our understanding of its complexities across a wide range of cognitive and computational processes. (shrink)

Like any social science, management and organization sits astride two literary and epistemic disciplines; the empirical and the conceptual. I argue that emphasizing the former to the detriment of the latter, as is often the case in management and organization research, creates a conceptual blindness that compromises progress in the field. I show how adopting a more philosophically attuned methodology buttresses the conceptual tools of management and organization research via deduction, induction, normative grounding, and overcoming the illusion of unanimity.

Written by a diverse range of scholars, this accessible introductory volume asks: What is implicit bias? How does implicit bias compromise our knowledge of others and social reality? How does implicit bias affect us, as individuals and participants in larger social and political institutions, and what can we do to combat biases? An interdisciplinary enterprise, the volume brings together the philosophical perspective of the humanities with the perspective of the social sciences to develop rich lines of (...) inquiry. It is written in a non-technical style, using relatable examples that help readers understand what implicit bias is, its significance, and the controversies surrounding it. Each chapter includes discussion questions and additional reading suggestions. A companion webpage contains teaching resources. The volume will be an invaluable resource for students—and researchers—seeking to understand criticisms surrounding implicit bias, as well as how one might answer them by adopting a more nuanced understanding of bias and its role in maintaining social injustice. (shrink)

Some philosophers challenge the advisability of naturalizing social metaphysics by appeal to social science. They argue that social science fails to meet criteria for realist commitment, such as unity and novel predictive power, and that social science would therefore be a poor basis for naturalization. These skeptical challenges are rooted in traditions in the philosophy of science that have held the social sciences in poor esteem. Through a case study that highlights the ways in which archaeology (...) is methodologically converging on hard science, I show that the philosophical bias against social science is outmoded. I suggest that at least some of the methodological advances of archaeology and other social sciences are epistemologically significant and are relevant to the question of realism. However, I conclude with the thought that realist commitment need not be a precondition for naturalization. The paper therefore accomplishes two main things: 1) it allays objections to using social science to naturalize social metaphysics, and 2) it motivates a higher estimation of the epistemological credentials of social science as compared with more skeptical traditions. (shrink)

This paper examines the ways in which social scientific discourse and classification interact with the objects of social scientific investigation. I examine this interaction in the context of the traditional philosophical project of demarcating the social sciences from the natural sciences. I begin by reviewing Ian Hacking’s work on interactive classification and argue that there are additional forms of interaction that must be treated.

My contribution to this Symposium focuses on the links between sexuality and reproduction from the evolutionary point of view.' The relation between women's sexuality and reproduction is particularly importantb ecause of a vital intersectionb etweenp olitics and biology feminists have noticed, for more than a century, that women's identity is often defined in terms of her reproductive capacity. More recently, in the second wave of the feminist movement in the United States, debates about women'si dentityh ave explicitlyi ncludeds exuality;m uch (...) feminist argument in the late 1960's and early 1970's involved an attempt to separate out an autonomous female sexuality from women's reproductive functions. It is especially relevant, then, to examine biological arguments, particularlye volutionarya rgumentst, o see what they say about whether and how women's sexuality is related to reproduction. We shall find that many evolutionarya rgumentss eem to supportt he direct linkingo f female sexualitya nd reproductionY. et I will argue that this supporti s not well-groundedI. n fact, I think evolutionarye xplanationso f female sexuality exemplify how social beliefs and social agendas can influence very basic biological explanations of fundamental physiological processes. In this paper, I shall spend some time spelling out a few examples in which assumptions about the close link between reproduction and sexuality yield misleading results, then I shall conclude with a discussion of the consequences of this case study for issues in the philosophy of science. (shrink)

The possibilities of unconscious perception and unconscious bias prompt parallel debates about unconscious mental content. This chapter argues that claims within these debates alleging the existence of unconscious content are made fraught by ambiguity and confusion with respect to the two central concepts they involve: consciousness and content. Borrowing conceptual resources from the debate about unconscious perception, the chapter distills the two conceptual puzzles concerning each of these notions and establishes philosophical strategies for their resolution. It then argues (...) that empirical evidence for unconscious bias falls victim to these same puzzles, but that progress can be made by adopting similar philosophical strategies. Throughout, the chapter highlights paths forward in both debates, illustrates how they serve as fruitful domains in which to study the relationship between philosophy and empirical science, and uses their combined study to further understanding of a general theory of unconscious content. (shrink)

Empirical philosophers of science aim to base their philosophical theories on observations of scientific practice. But since there is far too much science to observe it all, how can we form and test hypotheses about science that are sufficiently rigorous and broad in scope, while avoiding the pitfalls of bias and subjectivity in our methods? Part of the answer, we claim, lies in the computational tools of the digital humanities, which allow us to analyze large (...) volumes of scientific literature. Here we advocate for the use of these methods by addressing a number of large-scale, justificatory concerns—specifically, about the epistemic value of journal articles as evidence for what happens elsewhere in science, and about the ability of DH tools to extract this evidence. Far from ignoring the gap between scientific literature and the rest of scientific practice, effective use of DH tools requires critical reflection about these relationships. (shrink)

In the philosophy of science, it is a common proposal that values are illegitimate in science and should be counteracted whenever they drive inquiry to the confirmation of predetermined conclusions. Drawing on recent cognitive scientific research on human reasoning and confirmation bias, I argue that this view should be rejected. Advocates of it have overlooked that values that drive inquiry to the confirmation of predetermined conclusions can contribute to the reliability of scientific inquiry at the group level (...) even when they negatively affect an individual’s cognition. This casts doubt on the proposal that such values should always be illegitimate in science. It also suggests that advocates of that proposal assume a narrow, individualistic account of science that threatens to undermine their own project of ensuring reliable belief formation in science. (shrink)

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

Many philosophical thought experiments and arguments involve unusual cases. We present empirical reasons to doubt the reliability of intuitive judgments and conclusions about such cases. Inferences and intuitions prompted by verbal case descriptions are influenced by routine comprehension processes which invoke stereotypes. We build on psycholinguistic findings to determine conditions under which the stereotype associated with the most salient sense of a word predictably supports inappropriate inferences from descriptions of unusual (stereotype-divergent) cases. We conduct an experiment that combines plausibility (...) ratings with pupillometry to document this “salience bias.” We find that under certain conditions, competent speakers automatically make stereotypical inferences they know to be inappropriate. (shrink)

Mainstream views of medical research tell us it should be a fact-based, value-free endeavor: what a scientist (or her funding source) wants or cares about should not influence her findings. At the same time, we also sometimes criticize medical research for failing to embody certain values, e.g. when we criticize pharmaceutical companies for largely ignoring the diseases that affect the global poor. This chapter seeks to reconcile these perspectives by distinguishing appropriate from inappropriate influences of values on medical research. It (...) divides this broad question into two narrower ones, the Role Question (at what points in the research process is value influence potentially acceptable?) and the Content Question (when value influence is potentially acceptable, what specific values should researchers use?), and then draws on the philosophical literature on values in science to explore answers to each of them. (shrink)

Empirical evidence shows that people have multiple time-biases. One is near-bias; another is future-bias. Philosophical theorising about these biases often proceeds on two assumptions. First, that the two biases are _independent_: that they are explained by different factors (the independence assumption). Second, that there is a normative asymmetry between the two biases: one is rationally impermissible (near-bias) and the other rationally permissible (future-bias). The former assumption at least partly feeds into the latter: if the two (...) biases were not explained by different factors, then it would be less plausible that their normative statuses differ. This paper investigates the independence assumption and finds it unwarranted. In light of this, we argue, there is reason to question the normative asymmetry assumption. (shrink)

Philosophers have long noted, and empirical psychology has lately confirmed, that most people are “biased toward the future”: we prefer to have positive experiences in the future, and negative experiences in the past. At least two explanations have been offered for this bias: belief in temporal passage and the practical irrelevance of the past resulting from our inability to influence past events. We set out to test the latter explanation. In a large survey, we find that participants exhibit significantly (...) less future bias when asked to consider scenarios where they can affect their own past experiences. This supports the “practical irrelevance” explanation of future bias. It also suggests that future bias is not an inflexible preference hardwired by evolution, but results from a more general disposition to “accept the things we cannot change”. However, participants still exhibited substantial future bias in scenarios in which they could affect the past, leaving room for complementary explanations. Beyond the main finding, our results also indicate that future bias is stake-sensitive and that participants endorse the normative correctness of their future-biased preferences and choices. In combination, these results shed light on philosophical debates over the rationality of future bias, suggesting that it may be a rational response to empirical realities rather than a brute, arational disposition. (shrink)

The chapter discusses two points of intersection between the communication of science-based information about risk and philosophical ethics. The first is a logically unnecessary bias toward consequentialist ethics, and a corresponding tendency to overlook the significance of deontological and virtue based ways to interpret the findings of a scientific risk analysis. The second is a grammatical bias that puts scientific communicators at odds with the expectations of a non-scientific audience.

The following aesthetic discussion examines in a philosophical-scientific way the relationship between computation and artistic creativity. Currently, there is a criticism about the possible artistic creativity that an algorithm could have. Supporting the above, the term computer-generated art (CG-Art) defined by Margaret Boden would seem to have no exponents yet. Moreover, it has been pointed out that, rather than a matter of primitive technological development, CG-Art would have in its very foundations the inability to exist. This, because art is (...) considered as one of the most unique and exclusive human manifestations of our species. On the contrary, I propose that the denial of CG-Art has an anthropocentric bias. For this, I use the recent studies that, from the cognitive sciences, have been carried out on artistic creativity. In this way, I intend to convince the reader that behind the denial of the creative artistic capacity to the machines, a negationist mysticism of the current scientific advances necessarily lies. (shrink)

The "myside bias'' in evaluating arguments is an empirically well-confirmed phenomenon that consists of overweighting arguments that endorse one's beliefs or attack alternative beliefs while underweighting arguments that attack one's beliefs or defend alternative beliefs. This paper makes two contributions: First, it proposes a probabilistic model that adequately captures three salient features of myside bias in argument evaluation. Second, it provides a Bayesian justification of this model, thus showing that myside bias has a rational Bayesian explanation under (...) certain conditions. (shrink)

What attitude should we take toward a scientific theory when it competes with other scientific theories? This question elicited different answers from instrumentalists, logical positivists, constructive empiricists, scientific realists, holists, theory-ladenists, antidivisionists, falsificationists, and anarchists in the philosophy of science literature. I will summarize the diverse philosophical responses to the problem of underdetermination, and argue that there are different kinds of underdetermination, and that they should be kept apart from each other because they call for different responses.

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

Marine ecosystems are under increasing pressure from human activity, yet successful management relies on knowledge. The evidence-based policy (EBP) approach has been promoted on the grounds that it provides greater transparency and consistency by relying on ‘high quality’ information. However, EBP also creates epistemic responsibilities. Decision-making where limited or no empirical evidence exists, such as is often the case in marine systems, creates epistemic obligations for new information acquisition. We argue that philosophical approaches can inform the science-policy interface. (...) Using marine biosecurity examples, we specifically examine the epistemic challenges in the acquisition and acceptance of evidence to inform policy, discussing epistemic due care and biases in consideration of evidence. (shrink)

This chapter examines the legacy of Kuhn’s Structure for normative philosophy of science. As an argument regarding the history of 20th century philosophy of science, I contend that the main legacy of Structure was destructive: Structure shifted philosophy of science away from addressing general normative philosophical issues (e.g., the demarcation problem, empirical testability) towards more deflationary and local approaches to normative issues. This is evident in the first generation of post-Structure philosophers of science in the (...) 1980s and 1990s, who adopted a pluralist approach to HPS. As a metaphilosophical argument regarding the methods adopted in HPS, I argue that there are a plurality of legitimate philosophical methodologies for inferring normative claims from historical cases. I frame this argument as a response to Pitt’s dilemma of case studies. I reject Pitt’s dilemma for its presupposition of an unrealistic and unfruitful standard (viz., epistemic certainty) for assessing HPS arguments and its analysis of philosophical methodology at the level of individual arguments. Pitt’s dilemma is most usefully understood as identifying potential points of criticism for HPS arguments. -/- The chapter begins with an examination of Kuhn’s normative philosophy of science in Structure and his position that historical cases provide evidence for philosophical claims. Kuhn’s philosophical methodology is insufficiently articulated, and his utilization of case studies is subject to objections (viz., interpretative bias, hasty generalization) implied by Pitt’s dilemma. I subsequently examine four post-Kuhnian methodological perspectives: (1) Ian Hacking’s particularism, (2) Helen Longino’s practice-based approach, (3) Michael Friedman’s neo-Kantianism, and (4) Hasok Chang’s complementary science. These views suggest alternative methodological strategies in HPS for addressing normative issues. I conclude by articulating some outstanding methodological challenges for the pluralist tradition of HPS—associated with the Stanford and Minnesota schools of philosophy of science—that emerged in the 1980s and remains influential. (shrink)

Peer reviewers at many funding agencies and scientific journals are asked to score submissions both on individual criteria and overall. The overall scores should be some kind of aggregate of the criteria scores. Carole Lee identifies this as a potential locus for bias to enter the peer review process, which she calls commensuration bias. Here I view the aggregation of scores through the lens of social choice theory. I argue that, when reviewing grant proposals, it is in many (...) cases impossible to avoid commensuration bias. (shrink)

In the philosophical literature, self-deception is mainly approached through the analysis of paradoxes. Yet, it is agreed that self-deception is motivated by protection from distress. In this paper, we argue, with the help of findings from cognitive neuroscience and psychology, that self-deception is a type of affective coping. First, we criticize the main solutions to the paradoxes of self-deception. We then present a new approach to self-deception. Self-deception, we argue, involves three appraisals of the distressing evidence: (a) appraisal of (...) the strength of evidence as uncertain, (b) low coping potential and (c) negative anticipation along the lines of Damasio’s somatic marker hypothesis. At the same time, desire impacts the treatment of flattering evidence via dopamine. Our main proposal is that self-deception involves emotional mechanisms provoking a preference for immediate reward despite possible long-term negative repercussions. In the last part, we use this emotional model to revisit the philosophical paradoxes. (shrink)

In this paper, I present a new framework supporting the claim that some elements in science play a constitutive function, with the aim of overcoming some limitations of Friedman's (2001) account. More precisely, I focus on what I consider to be the gradualism implicit in Friedman's interpretation of the constitutive a priori, that is, the fact that it seems to allow for degrees of 'constitutivity'. I tease out such gradualism by showing that the constitutive character Friedman aims to track (...) can be captured by three features - namely, quasi-axiomaticity (QA), generative potential (GP), and empirical shielding (ES) - which are exhibited to a maximal degree by the examples Friedman deploys, particularly in his analysis of Newtonian mechanics. I argue that not all varieties of 'constitutivity' can be captured by the kind of gradualism implicit in Friedman's view, although developing the gradualism itself might provide useful insights. To show this, I analyse the function of the Hardy-Weinberg principle (HWP) in population genetics in terms of its QA, GP, and ES. Whereas the HWP does not count as constitutive in classical philosophical interpretations (Sober 1984), nor does it within Friedman's framework, it does nonetheless perform a minimally constitutive function. By means of historical details and considerations on the prospects of replacing the HWP, I show that the HWP is minimally constitutive by being a counterfactual instantiation of a paradigmatically constitutive stability principle, where the latter might itself be regarded as an enabling condition for a variety of modelling practices across the sciences. (shrink)

This paper empirically investigates whether people’s implicit decision theory is more like causal decision theory or more like a non-causal decision theory (such as evidential decision theory). We also aim to determine whether implicit causalists, without prompting and without prior education, make a distinction that is crucial to causal decision theorists: preferring something _as a news item_ and preferring it _as an object of choice_. Finally, we investigate whether differences in people’s implicit decision theory correlate with differences in their level (...) of _future bias_: the preference for positively valenced events to be located in the future and not the past, and negatively valenced events to be located in the past and not the future. We find that people are overwhelmingly non-causalists. We also find that implicit causalists _do not_ make the distinction between news items and objects of choice, and that there is little to no correlation between people’s future bias and their implicit decision theory. We end by discussing the philosophical upshots of this work. (shrink)

1. EXPLICATING THE CONCEPT OF REFLECTION (under review) -/- To understand how ‘reflection’ is used, I consider ordinary, philosophical, and scientific discourse. I find that ‘reflection’ seems to refer to reasoning that is deliberate and conscious, but not necessarily self-conscious. Then I offer an empirical explication of reflection’s conscious and deliberate features. These explications not only help explain how reflection can be detected; they also distinguish reflection from nearby concepts such as ruminative and reformative reasoning. After this, I find (...) that reflection is not obviously limited to only practical or only theoretical reasoning. The chapter ends with reasons to prefer ‘unreflective’ and ‘reflective’ to dual process theorists’ labels about systems or types. -/- 2. BOUNDED REFLECTIVISM & EPISTEMIC IDENTITY (in Metaphilosophy) -/- Reflection features centrally in philosophy (e.g., Korsgaard, 1996; Rawls, 1971; Sosa, 1991) and psychology (e.g., Pennycook, 2018). Bounded reflectivism is an empirically adequate model of reflection that explains reflection’s capacity to either help or hinder reasoning—e.g., reflective equilibrium vs. reflective polarization (e.g., Kahan et al., 2017). One innovation of the model is epistemic identity: an identity that involves particular beliefs—e.g., religious and political identities. When we feel that our epistemic identity is threatened, we can reflectively defend its beliefs rather than update our beliefs according to the best arguments and evidence. The solution, I argue, is not to suppress epistemic identity but embrace it by appealing to shared, superordinate epistemic identities. -/- 3. ALL MEASURES ARE NOT CREATED EQUAL (under review) -/- A bat and a ball cost $1.10 in total. The bat costs $1.00 more than the ball. How much does the ball cost? “10 cents” comes to most people’s minds immediately. However, upon reflection, we can realize that “5 cents” is the correct answer. There are many reflection tests. Each has its limitations. Some reflection tests are mathematical—like the bat-and-ball problem (e.g., Frederick, 2005) and others are logical (e.g., Janis & Frick, 1943). So there are concerns that reflection tests track logical and mathematical competence rather than reflection per se. Also, some psychologists assume a priori that correct answers are reflective and lured answers are unreflective. New evidence raises additional concerns about the plausibility of these assumptions. I argue that think aloud protocols (Ericsson & Simon, 1998) and process dissociation (Jacoby, 1991) can assuage some of these concerns. -/- 4. GREAT MINDS DO NOT THINK ALIKE (in Review of Philosophy and Psychology) -/- Two large studies (N = 1299), one pre-registered, found that many correlations between reflection and philosophical beliefs among non-philosophers replicated among philosophers. For example, less reflective philosophers preferred theism to atheism and utilitarian rather than deontological responses to the trolley problem (Hannikainen & Cova, in prep.; Pennycook et al., 2016; Reynolds, Byrd, & Conway, forthcoming). However, philosophical judgments were sometimes better predicted by factors like education, gender, and personality than by reflection test performance. So although some relationships between reflection and philosophy were robust, there is more to the link between reflection and philosophy. Normative implications are also discussed—e.g., how we can infer the quality of philosophical views from their correlations with reflective or unreflective reasoning. -/- 5. WHAT WE CAN (AND CAN’T) INFER ABOUT IMPLICIT BIAS (in Synthese) -/- Contrary to some philosophers and psychologists, I argue that implicit bias is probably associative. However, I also argue that debiasing is not thereby entirely unconscious and involuntary. Indeed, strong evidence suggests that reflection can change implicitly biased behavior—e.g., conscious and deliberate counterconditioning. This has implications for the science and morality of implicit bias—e.g., evidence suggests that we can reform biases; so. intuitively, we can be responsible for biases. (shrink)

Naturalistic philosophers rely on literature search and review in a number of ways and for different purposes. Yet this article shows how processes of literature search and review are likely to be affected by widespread and systematic biases. A solution to this problem is offered here. Whilst the tradition of systematic reviews of literature from scientific disciplines has been neglected in philosophy, systematic reviews are important tools that minimize bias in literature search and review and allow for greater reproducibility (...) and transparency. If naturalistic philosophers wish to reduce bias in their research, they should then supplement their traditional tools for literature search and review by including systematic methodologies. (shrink)

I argue that philosophical studies of the virtues of creativity should attend to the ways that our conceptions of human creativity may be grounded in conceptions of human nature or the nature of reality. I consider and reject claims in this direction made by David Bohm and Paul Feyerabend. The more compelling candidate is the account of science, creativity, and human nature developed by the early Marx. Its guiding claim is that the forms of creativity enabled by the (...) sciences are ultimately valuable insofar as they advance our emancipation from a state of existential alienation. I end by encouraging future investigations of such vertical explanations of the significance of certain virtues in the context of scientific enquiry. (shrink)

This paper is a review of Suarez, M. (ed.) Fictions in Science (Routledge).

In this paper, we set out to investigate the following question: if science relies heavily on induction, does philosophy of science rely heavily on induction as well? Using data mining and text analysis methods, we study a large corpus of philosophical texts mined from the JSTOR database (n = 14,199) in order to answer this question empirically. If philosophy of science relies heavily on induction, just as science supposedly does, then we would expect to find (...) significantly more inductive arguments than deductive arguments and abductive arguments in the published works of philosophers of science. Using indicator words to classify arguments by type (namely, deductive, inductive, and abductive arguments), we search through our corpus to find patterns of argumentation. Overall, the results of our study suggest that philosophers of science do rely on inductive inference. But induction may not be as foundational to philosophy of science as it is thought to be for science, given that philosophers of science make significantly more deductive arguments than inductive arguments. Interestingly, our results also suggest that philosophers of science do not rely on abductive arguments all that much, even though philosophers of science consider abduction to be a cornerstone of scientific methodology. (shrink)

The task of Philosophy in Science (PinS) is to use philosophical tools to help solve scientific problems. This article describes how I stumbled into this line of work and then addressed several topics in philosophy of biology—units of selection, cladistic parsimony, robustness and trade-offs in model building, adaptationism, and evidence for common ancestry—often in collaboration with scientists. I conclude by offering advice for would-be PinS practitioners.

I first quickly outline what I think grasping is, and suggest that it is both among our basic aims of inquiry and not essentially tied to belief, justification, or knowledge. Then, I briefly look at some places in the metaphysics of science in which it looks like our aim of grasping and our aim in knowing—or perhaps more specifically in knowing the explanations for things—might seem to conflict. I will use this conflict to support a broader view: sometimes, we (...) might develop philosophical views or theories—and even endorse them—in order to better grasp them, regardless of whether we genuinely believe them, or are justified in so doing. At other times, we may be aiming at propositional knowledge. These aims can come apart, and perhaps even systematically come apart. A pluralism about the value of those aims doesn’t entail an “anything goes” attitude with respect to how we think about what philosophical views to put forward, defend, or endorse, however—far from it. Instead, it suggests that what counts as a virtue of a philosophical theory depends on our aims in espousing it. If philosophers have distinct aims at the meta-level, it will be hard for them to engage in joint theory evaluation at the first-order level. At least all three of theoretical virtues, evaluative judgments of philosophical views, and what attitudes we ought to have towards the views we ourselves espouse will vary according to our guiding metaphilosophical aims. (shrink)

Understanding science requires appreciating the values it presupposes and its social context. Both the values that scientists hold and their social context can affect scientific communication. Philosophers of science have recently begun studying scientific communication, especially as it relates to public policy. Some have proposed “guiding principles for communicating scientific findings” to promote trust and objectivity. This paper contributes to this line of research in a novel way using behavioural experimentation. We report results from three experiments testing judgments (...) about the trustworthiness, competence and objectivity of scientists. More specifically, we tested whether such judgments are affected by three factors: consulting or not consulting nonscientists, conducting research under a restrictive or non-restrictive governmental communication policy, and the source of a lab’s funding (i.e., government funding, private funding, or a combination of the two). We found that each of these factors affects ordinary judgments of trustworthiness, competence and objectivity. These findings support several recommendations that could help improve scientific communication and communication policies. (shrink)

Philosophers of science have come to accept that contextual values can play unavoidable and desirable roles in science. This has raised concerns about the need to distinguish legitimate and illegitimate value influences in scientific inquiry. I discuss here four such concerns: epistemic distortion, value imposition, undermining of public trust in science, and the use of objectionable values. I contend that preserving epistemic integrity and avoiding value imposition provide good reasons to attempt to distinguish between legitimate and illegitimate (...) influences of values in science. However, the trust and the objectionable values concerns constitute no good reason for demarcation criteria. (shrink)

This chapter argues for a structural injustice approach to the governance of AI. Structural injustice has an analytical and an evaluative component. The analytical component consists of structural explanations that are well-known in the social sciences. The evaluative component is a theory of justice. Structural injustice is a powerful conceptual tool that allows researchers and practitioners to identify, articulate, and perhaps even anticipate, AI biases. The chapter begins with an example of racial bias in AI that arises from structural (...) injustice. The chapter then presents the concept of structural injustice as introduced by the philosopher Iris Marion Young. The chapter moreover argues that structural injustice is well suited as an approach to the governance of AI and compares this approach to alternative approaches that start from analyses of harms and benefits or from value statements. The chapter suggests that structural injustice provides methodological and normative foundations for the values and concerns of Diversity, Equity, and Inclusion. The chapter closes with an outlook onto the idea of “structure” and on responsibility. The idea of a structure is central to justice. An open theoretical research question is to what extent AI is itself part of the structure of society. Finally, the practice of responsibility is central to structural injustice. Even if they cannot be held responsible for the existence of structural injustice, every individual and every organization has some responsibility to address structural injustice going forward. (shrink)

Philosophers of science often make reference — whether tacitly or explicitly — to the notion of a scientific community. Sometimes, such references are useful to make our object of analysis tractable in the philosophy of science. For others, tracking or understanding particular features of the development of science proves to be tied to notions of a scientific community either as a target of theoretical or social intervention. We argue that the structure of contemporary scientific research poses two (...) unappreciated, or at least underappreciated, challenges to this concept of the “scientific community” in the philosophy of science. In particular, we will present two case studies from robotics research, broadly construed, which show that (1) the boundedness of the scientific community is threatened when private citizens can develop scientific and technological advances at minimal expense (democratization), and (2) the discreteness of scientific research programs is threatened by the complexly interrelated environment of contemporary scientific work (interconnectivity). Taken together, the extent of democratization and interconnectivity present a significant challenge for any practically oriented philosophy of science, one which we hope will be taken on directly by philosophers in the future. (shrink)

Metaphysical considerations aside, today’s inheritors of the tradition of natural philosophy are primarily scientists. However, they are oblivious to the human factor involved in science and in seeing how political, religious, and other ideologies contaminate our visions of nature. In general, philosophers observe human (historical, sociological, and psychological) processes within the construction of theories, as well as in the development of scientific activity itself. -/- In our time, feminism—along with accompanying ideas of identity politics under the slogan “diversity, inclusion, (...) equity”—has emerged in science policies. The vast majority of scientists (including myself) are convinced that discrimination is reprehensible. We also believe that all individuals of any sex, race, ethnic group, or ideology should be valued in academia solely based on his or her merits and potential through equality programs. However, as I will show in this article, political indoctrination has inadmissibly undertaken the struggle for equality in academic institutions in Western countries. I argue here that universities and research institutes should be politically free (neutral) to encourage academic freedom. -/- One negative aspect of equality programs is that worldwide, scientists are harassed for expressing opinions related to the “gender” issue. This situation severely restricts scientists’ freedom of expression, even within the limits of the law. Codes of conduct extending beyond legal boundaries are examples of this issue. Scientists who express their views about “gender” are often harassed, bullied, and socially or academically excluded. Thus, we are witnessing a wave of proselytizing in research institutes and science-associated media. Today, there is widespread biased propaganda of “victimhood”. This propaganda proposes positive discrimination and increasing women’s participation in unnatural ways. It also bends the history of science by overvaluing the creations of forgotten women, offering lectures on indoctrination, organizing congresses on gender and science, and persecuting anyone who sees the subject differently. All of this covered by a multitude of associations that financially benefit from these discourses through succulent subsidies of public money. Apparently, feminism is no longer about fighting against discrimination. Instead, it is about imposing an ideology and giving more power to one group of people. Thus, we must ask whether the end justifies the means. (shrink)

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

It has been argued that implicit biases are operative in philosophy and lead to significant epistemic costs in the field. Philosophers working on this issue have focussed mainly on implicit gender and race biases. They have overlooked ideological bias, which targets political orientations. Psychologists have found ideological bias in their field and have argued that it has negative epistemic effects on scientific research. I relate this debate to the field of philosophy and argue that if, as some studies (...) suggest, the same bias also exists in philosophy then it will lead to hitherto unrecognised epistemic hazards in the field. Furthermore, the bias is epistemically different from the more familiar biases in respects that are important for epistemology, ethics, and metaphilosophy. (shrink)

List of Illustrations Introduction 1 The Didactic and the Elegant: Some Thoughts on Scientific and Technological Illustrations in the Middle Ages and Renaissance 3 2 Temples of the Body and Temples of the Cosmos: Vision and Visualization in the Vesalian and Copernican Revolutions 40 3 Descartes’s Scientific Illustrations and ’la grande mecanique de la nature’ 86 4 Illustrating Chemistry 135 5 Representations of the Natural System in the Nineteenth Century 164 6 Visual Representation in Archaeology: Depicting the Missing-Link in Human (...) Origins 184 7 Towards an Epistemology of Scientific Illustration 215 8 Illustration and Inference 250 9 Visual Models and Scientific Judgment 269 10 Are Pictures Really Necessary? The Case of Sewall Wright’s ’Adaptive Landscapes’ 303 Bibliography 339 Notes on Contributors 373 Index 377. (shrink)

Development in all of its stages, from organizing the vision and strategy to implementing plans, requires policy-making. We show that the division of labor and specialization of sciences and some philosophical doctrines cause the emergence of technocracy in policies. Technocracy makes development not happen in the direction of public welfare. For this reason, for sustainable development, we need institutions, strategies, and philosophical contexts that provide a democratic ground for the possibility of criticizing and reforming policies.

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)