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)

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)

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)

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)

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)

There are two problems with Cimpian & Salomon’s (C&S’s) claim that an innate inherence heuristic is part of our cognitive makeup. First, some of their examples of inherent features do not seem to accord with the authors’ own definition of inherence. Second, rather than posit an inherence heuristic to explain why humans rely more heavily on inherent features, it may be more parsimonious to do so on the basis of aspects of the world itself and our relationship to it.

In this article, we describe a hitherto undocumented fallacy-in the sense of a mistake in reasoning-constituted by a negativity bias in the way that people attribute motives to others. We call this the "worst-motive fallacy," and we conducted two experiments to investigate it. In Experiment 1, participants expected protagonists in a variety of fictional vignettes to pursue courses of action that satisfy the protagonists' worst motive, and furthermore, participants significantly expected the protagonist to pursue a worse course of action (...) than they would prefer themselves. Experiment 2 was a preregistered attempted replication of Experiment 1, including a bigger range of vignettes; the first effect was not replicated for the new vignettes tested but was for the original set. Also, we once again found that participants expected protagonists to be more likely than they were themselves to pursue courses of action that they considered morally bad. We discuss the worst-motive fallacy's relation to other well-known biases as well as its possible evolutionary origins and its ethical consequences. (shrink)

While classical neo-positivists reject any role for traditionally understood values in science, Kuhn identifies five specific values as criteria for assessing a scientific theory; this approach has been further developed by several other authors. This paper focuses on Helen Longino, who presents a significant contemporary critique of Kuhn’s concept. The most controversial aspect of Longino’s position is arguably her claim that the criterion of empirical adequacy is the least defensible basis for assessing theories. The de-emphasizing of the importance of (...) external consistency as a value and the introduction of socio-political considerations into the processes of an assessment of scientific theories are also considered problematic issues. I provide arguments against Longino’s conception, identify some of its problems, and argue for refusal of her approach. (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)

As algorithms have become ubiquitous in consequential domains, societal concerns about the potential for discriminatory outcomes have prompted urgent calls to address algorithmic bias. In response, a rich literature across computer science, law, and ethics is rapidly proliferating to advance approaches to designing fair algorithms. Yet computer scientists, legal scholars, and ethicists are often not speaking the same language when using the term ‘bias.’ Debates concerning whether society can or should tackle the problem of algorithmic bias (...) are hampered by conflations of various understandings of bias, ranging from neutral deviations from a standard to morally problematic instances of injustice due to prejudice, discrimination, and disparate treatment. This terminological confusion impedes efforts to address clear cases of discrimination. -/- In this paper, we examine the promises and challenges of different approaches to disambiguating bias and designing for justice. While both approaches aid in understanding and addressing clear algorithmic harms, we argue that they also risk being leveraged in ways that ultimately deflect accountability from those building and deploying these systems. Applying this analysis to recent examples of generative AI, our argument highlights unseen dangers in current methods of evaluating algorithmic bias and points to ways to redirect approaches to addressing bias in generative AI at its early stages in ways that can more robustly meet the demands of justice. (shrink)

Dubljević and company’s proposed approach for incorporating a socio-political perspective into neuroethics has clear potential to help mitigate the effects of research ‘hype’ relating to neuroethics. Their approach serves as a social regulation meant to improve the realizability of neuroethics research. Drawing on Dubljević et al. s suggestion, we consider how incorporating a socio-political perspective in other scientific disciplines could help the scientific community as a whole move beyond the infamous ‘reproducibility crisis’ in science. The reproducibility crisis is a (...) concern in science stemming from the revelation that most scientific results are difficult, or impossible, to replicate (Frias-Navarro et al., 2020). By applying the four principles proposed by Dubljević et al., the scientific community can avoid many of the pitfalls that have led to the reproducibility crisis, such as the file drawer effect, a publication bias preventing negative results from being published, or the publish-or-perish culture - the pressure for scientists to publish highly influential papers in high impact journals in order to keep their funding (Rosenthal, 1979; Begley & Ioannidis, 2015). As such, we argue that, in its final form, this socio-political framework begs for true open science, wherein systematically sharing data would enable enlightened policymaking by showing a picture closer to the ground-level realities of scientific research. (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)

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)

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)

The social sciences face a problem of sample non-representation, where the majority of samples consist of undergraduate students from Euro-American institutions. The problem has been identified for decades with little trend of improvement. In this paper, I trace the history of sampling theory. The dominant framework, called the design-based approach, takes random sampling as the gold standard. The idea is that a sampling procedure that is maximally uninformative prevents samplers from introducing arbitrary bias, thus preserving sample representation. I show (...) how this framework, while good in theory, faces many challenges in application. Instead, I advocate for an alternative framework, called the model-based approach to sampling, where representative samples are those balanced in composition, however they were drawn. I argue that the model-based framework is more appropriate in the social sciences because it allows for systematic assessment of imperfect samples and methodical improvement in resource-limited scientific contexts. I end with practical proposals of improving sample quality in the social sciences. (shrink)

This paper challenges the first Gettier counterexample to the tripartite account of knowledge. Noting that 'the man who will get the job' is a description and invoking Donnellan's distinction between their 'referential' and 'attributive' uses, I argue that Smith does not actually believe that the man who will get the job has ten coins in his pocket. Smith's ignorance about who will get the job shows that the belief cannot be understood referentially, his ignorance of the coins in his pocket (...) shows that it cannot be understood attributively. An explanation for why Smith appeared to have justified true belief is given by distinguishing between 'belief' and 'belief in truth'. Smith believes the sentence 'the man who will get the job has ten coins in his pocket' to be true (he mistakenly believes that Jones will get the job, of whom he knows that he has ten coins in his pocket) (hence his 'belief'), the sentence is true (hence 'truth'), and he has sufficient reason to assent to it (hence his 'justification'). But he does not believe the proposition expressed. Hence he does not know it either. (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)

In this paper, I will try to answer the question: How are we supposed to assess the expert’s opinion in an argument from the position of an outsider to the specialized field? by placing it in the larger context of the political status of epistemic authority. In order to do this I will first sketch the actual debate around the problem of expertise in a democracy and relate this to the issue of the status of science in society. Secondly, (...) I will review how Douglas Walton’s pragma-dialectical approach offers a practical procedure to assess the expert bias from a nonprofessional’s perspective. Thirdly, I will introduce the problem of group bias using insights from Bohman and Fischer and show how Walton’s solution does not address this specific type of bias. Lastly, I will try proposing a revision of Walton’s solution in order to address this problem. In order to make the explanation more easy to follow I will use a case study concerning the medical expertise in the public debate on second-hand smoke. (shrink)

Some recent work in philosophy of religion addresses what can be called the “axiological question,” i.e., regardless of whether God exists, would it be good or bad if God exists? Would the existence of God make the world a better or a worse place? Call the view that the existence of God would make the world a better place “Pro-Theism.” We argue that Pro-Theism is not implausible, and moreover, many Theists, at least, (often implicitly) think that it is true. That (...) is, many Theists think that various good outcomes would arise if Theism is true. We then discuss work in cognitive science concerning human cognitive bias, before discussing two noteworthy attempts to show that at least some religious beliefs arise because of cognitive bias: Hume’s, and Draper’s and Nichols’s. We then argue that, as a result of certain cognitive biases that result when good outcomes might be at stake, Pro-Theism causes many Theists to inflate the epistemic probability that God exists, and as a result, Theists should lower the probability they assign to God’s existence. Finally, based our arguments, we develop a novel objection to Pascal’s wager. (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)

In this paper, I argue against the view that the representational structure of the implicit attitudes responsible for implicitly biased behaviour is propositional—as opposed to associationist. The proposal under criticism moves from the claim that implicit biased behaviour can occasionally be modulated by logical and evidential considerations to the view that the structure of the implicit attitudes responsible for such biased behaviour is propositional. I argue, in particular, against the truth of this conditional. Sensitivity to logical and evidential considerations, I (...) contend, proves to be an inadequate criterion for establishing the true representational structure of implicit attitudes. Considerations of a different kind, which emphasize the challenges posed by the structural social injustice that implicit attitudes reflect, offer, I conclude, better support for deciding this issue in favour of an associationist view.En este artículo cuestiono la tesis de que la estructura representacional de las actitudes implícitas responsables del comportamiento implícitamente sesgado es proposicional—en lugar de asociacionista. De acuerdo con la propuesta criticada, si la conducta implícita sesgada puede ocasionalmente ser modulada por consideraciones lógicas y evidenciales, entonces la estructura de las actitudes implícitas responsables de esa conducta es proposicional. Cuestiono, en particular, la verdad de este condicional. Sostengo que la sensibilidad de las actitudes implícitas a consideraciones lógicas y evidenciales resulta ser un criterio inadecuado para establecer su verdadera estructura representacional. Consideraciones de otro tipo, que enfatizan los desafíos planteados por la injusticia social estructural que las actitudes implícitas reflejan, ofrecen, concluyo, un mejor apoyo para decidir esta cuestión a favor de una visión asociacionista. (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.

In this paper, I argue against the view that the representational structure of the implicit attitudes responsible for implicitly biased behaviour is propositional—as opposed to associationist. The proposal under criticism moves from the claim that implicit biased behaviour can occasionally be modulated by logical and evidential considerations to the view that the structure of the implicit attitudes responsible for such biased behaviour is propositional. I argue, in particular, against the truth of this conditional. Sensitivity to logical and evidential considerations, I (...) contend, proves to be an inadequate criterion for establishing the true representational structure of implicit attitudes. Considerations of a different kind, which emphasize the challenges posed by the structural social injustice that implicit attitudes reflect, offer, I conclude, better support for deciding this issue in favour of an associationist view. (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.

The results of forensic science are believed to be reliable, and are widely used in support of verdicts around the world. However, due to the lack of suitable empirical studies, we actually know very little about the reliability of such results. In this paper, I argue that phenomena analogous to the main culprits for the replication crisis in psychology are also present in forensic science. Therefore forensic results are significantly less reliable than is commonly believed. I conclude that (...) in order to obtain reliable estimates for the reliability of forensic results, we need to conduct studies analogous to the large-scale replication projects in psychology. Additionally, I point to some ways for improving the reliability of forensic science, inspired by the reforms proposed in response to the replicability crisis. (shrink)

In addressing the Lucretian symmetry problem, the temporal bias approach claims that death is bad because it deprives us of something about which it is rational to care (e.g., future pleasures), whereas prenatal nonexistence is not bad because it only deprives us of something about which it is rational to remain indifferent (e.g., past pleasures). In a recent contribution to the debate on this approach, Miguel and Santos argue that a late beginning can deprive us of a future pleasure. (...) Their argument is based on the claim that for birth or death to deprive a person of any value in life, the historically closest counterfactual situation that contains the value is such that the person begins to exist earlier or dies later. This is what they call the Historical Condition. However, the Historical Condition is untenable for several reasons. First, this condition substantially weakens the explanatory capacity of the deprivation account because it implies that most ordinary sorts of pleasures are not deprived by death. In addition, the Historical Condition is vulnerable to counterexamples. In particular, what they offer as a standard case of the deprivation of future pleasure due to a late beginning (what they call Seeing The Beatles), or some of its variants, can be used to falsify this condition. Finally, the Historical Condition is theoretically indefensible because it is based on a faulty analysis of deprivation. (shrink)

Cognitive scientists claim to have discovered a large number of cognitive biases, which have a tendency to mislead reasoners. Might cognitive scientists themselves be subject to the very biases they purport to discover? And how should this alter the way they evaluate their research as evidence for the existence of these biases? In this paper, we posit a new paradox (the ‘Self-Reflexive Bias Paradox’), which bears a striking resemblance to some classical logical paradoxes. Suppose that research R appears to (...) be good evidence for the existence of bias B, but if B exists, then R would have been subject to B. Thus, it seems sensible for the researcher to reject R as good evidence for the existence of B. However, rejecting R for this reason admits the existence of B. We examine four putative cognitive biases and criticisms of them, each of which seem to be subject to self-reflexivity. In two cases, we argue, paradox is avoidable. In the remaining two, we cannot find a way to avoid the paradox, which poses a practical obstacle to scientific inquiry and results in an intriguing theoretical quandary. (shrink)

Discussions in social psychology overlook an important way in which biases can be encoded in conceptual representations. Most accounts of implicit bias focus on ‘mere associations’ between features and representations of social groups. While some have argued that some implicit biases must have a richer conceptual structure, they have said little about what this richer structure might be. To address this lacuna, we build on research in philosophy and cognitive science demonstrating that concepts represent dependency relations between features. (...) These relations, in turn, determine the centrality of a feature f for a concept C: roughly, the more features of C depend on f, the more central f is for C. In this paper, we argue that the dependency networks that link features can encode significant biases. To support this claim, we present a series of studies that show how a particular brilliance-gender bias is encoded in the dependency networks which are part of the concepts of female and male academics. We also argue that biases which are encoded in dependency networks have unique implications for social cognition. (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)

Michael Brownstein, Alex Madva, and Bertram Gawronski articulate a careful defense of research on implicit bias. They argue that though there is room for improvement in various areas, when we set the bar appropriately and when we are comparing relevant events, the test–retest stability and predictive ability of implicit bias measures are respectable. Edouard Machery disagrees. He argues that theories of implicit bias have failed to answer four fundamental questions about measures of implicit bias, and this (...) undermines their utility in further scientific research and policy making. In this article, I offer my perspective on this important debate. I argue that there is a theoretical mismatch in debating the merits of a research program on the terms of a specific theory within the research program. Nevertheless, the discussion allows us to see which questions are answered from within the perspective of a particular theory. I argue that the emphasis should be on whether implicit bias theories predict novel facts. (shrink)

In 2006, in a special issue of this journal, several authors explored what they called the dual nature of artefacts. The core idea is simple, but attractive: to make sense of an artefact, one needs to consider both its physical nature—its being a material object—and its intentional nature—its being an entity designed to further human ends and needs. The authors construe the intentional component quite narrowly, though: it just refers to the artefact’s function, its being a means to realize a (...) certain practical end. Although such strong focus on functions is quite natural , I argue in this paper that an artefact’s intentional nature is not exhausted by functional considerations. Many non-functional properties of artefacts—such as their marketability and ease of manufacture—testify to the intentions of their users/designers; and I show that if these sorts of considerations are included, one gets much more satisfactory explanations of artefacts, their design, and normativity.Keywords: Artefacts; Dual Nature program; Function; Intentionality; Normativity. (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)

Recent work in the behavioral sciences asserts that we are subject to a variety of cognitive biases. For example, we mourn losses more than we prize equivalently sized gains; we are more inclined to believe something if it matches our previous beliefs; and we even relate more warmly or coldly to others depending on whether the coffee cup we are holding is warm or cold. Drawing on this work, case law and legal scholarship have asserted that we have reason to (...) select legal norms, or revise existing norms, so as to eliminate the influence of these and other cognitive biases. -/- In this Article, I critically evaluate whether and when this reaction is warranted. I begin by contrasting predominantly descriptive definitions of bias, on which bias is merely deviation from a predictive model, with prescriptive definition of bias, on which biased conduct is conduct that actors ought not do. I then similarly contrast the behavioral-scientific concepts of statistical significance and effect size with the concept of significance required to justify legal conclusions. -/- With this apparatus in place, I go on to consider a variety of examples where legal commentators and decisionmakers have worried about the effects of cognitive bias on law. I argue that many of these cognitive biases (for example, our aversion to losses), while reflecting deviations from behavioral scientists’ models of human behavior, are not normatively objectionable and so give us no reason to revise our legal norms to eliminate their effect. Others (e.g., the effect of judges’ hunger on their decisionmaking), however, constitute biases under both descriptive and prescriptive definitions and therefore give us good reason to revise our legal norms. -/- I conclude by contrasting my conclusion — that evaluation of cognitive biases’ legal significance must explicitly evaluate the normative arguments for and against the model of decisionmaking in question on a case-by-case basis — with the arguments of influential scientists and legal commentators like Daniel Kahneman and John Mikhail, who treat cognitive heuristics and biases as more broadly desirable or objectionable. (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)

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)

Artificial intelligence has arrived. In the online world it is already a part of everyday life, sitting invisibly behind a wide range of search engines and online commerce sites. It offers huge potential to enable more efficient and effective business and government but the use of artificial intelligence brings with it important questions about governance, accountability and ethics. Realising the full potential of artificial intelligence and avoiding possible adverse consequences requires societies to find satisfactory answers to these questions. This report (...) sets out some possible approaches, and describes some of the ways government is already engaging with these issues. (shrink)

This chapter introduces topical issues in the ethical debate on speciesism. It does so against a background of the history of the debate and with an emphasis on concerns that arise at the intersection of speciesism and science. The term speciesism was coined in the 1970s by Richard Rider and popularized by Peter Singer, who defined speciesism as “a prejudice or attitude of bias in favor of the interests of members of one’s own species and against those of (...) members of other species.” Critiques of speciesism are undergirded by the principle that comparable interests should be given equal consideration, regardless of species-membership. To what extent the interests of humans and non-humans are comparable, however, has been a matter of contention and is partly beholden to empirical findings. Diverging opinions on this matter have given rise to a variety of more and less species-egalitarian views, often paired with rivalling accounts of “moral status”. A minority of ethicists have explicitly defended speciesism or some version thereof, including Bernard Williams and, more recently, Shelly Kagan. Apart from the back-and-forths between critics and defenders, the speciesism debate has transformed over the last decade, in three respects. First, discourse on animal ethics has witnessed a “political turn”, moving away from analyses of moral status and towards discussions of human-animal relations in interspecies societies. Secondly, apart from anthropocentric speciesism, i.e., privileging humans over non-humans, there has been an increasing interest in non-anthropocentric speciesism, i.e., privileging some non-human species over others. Thirdly, speciesism has been endorsed as a prominent topic in the new, activist-leaning research field of Critical Animal Studies, and has recently garnered substantial attention from psychologists. As these disciplinary changes and conceptual refinements suggest, half a century after its coinage, speciesism continues to be an important scholarly and ethical concept whose history is still in the making. (shrink)

One of the predominant debates in AI Ethics is the worry and necessity to create fair, transparent and accountable algorithms that do not perpetuate current social inequities. I offer a critical analysis of Reuben Binns’s argument in which he suggests using public reason to address the potential bias of the outcomes of machine learning algorithms. In contrast to him, I argue that ultimately what is needed is not public reason per se, but an audit of the implicit moral assumptions (...) of societies within which algorithms are built and applied. Public justification is appealing since it offers us the possibility to align the decision-making outcomes of the algorithm with the core moral values of stakeholders within a constitutional democratic society. My concern is that the common moral principles that form the foundation of public reason are not necessarily neutral, as they still express specific moral ideals and normative standards even if there is moral agreement by society as a whole, or among different stakeholders within society. Appealing to such normative standards may thus still lead to algorithmic outcomes being biased as common moral values may very well still be discriminatory even though they are formed from a consensus, and even if public reason is applied as a kind of filter for potential algorithmic outcomes. Hence, I argue that these implicit moral norms within society that we take as a given in public reasoning, need to be audited from generation to generation in order to effectively mitigate potential algorithmic bias. (shrink)

High percentages of submitted papers are rejected at editorial levels without offering a second chance to authors by sending their papers for further peer-reviews. In most cases, the rejections are typical quick answers without helpful argumentations related to the content of the rejected material. More surprisingly, some journals vaunt their high rejection rates as a “mark of prestige”!However, journals that reject high percentages of submitted papers have built their prominent positions based on a flawed measure, the impact factor, and from (...) a long and favorable historical context. Their shareholders may think that they are allowed to have a large margin of rejection rates without affecting their sponsorship or funding sources thanks to an extended anchorage since tens, or in some cases hundreds, of years compared to unknown or new journals that struggle to pave a way in the scientific publication world. Historical anchorage of some journals also makes it unfair to compare old and new .. (shrink)

Cognitive tests show that identity and symmetry reflect intellect. 'Guess of other guess' creates various symmetries, while only one is right: 'absolute symmetry', which can be outvoted by the majority. Prejudices result from differences between ME (my identity) and others. Unbiased judgement is symmetrical, always in the middle: neither in favor, nor against ME. Intelligence reduces prejudices, but the lack of opportunities can counterbalance it. That's why type of bias differs in various groups: people from war zones, people in (...) therapy, artists, etc.. "The law of values' equity" is a symmetrical principle redefining utility in economics, when people equate all their values. E.g. 2 children averagely rich, is better than one child rich and another poor. If 'a' is an average richness, and 'x' is a difference in richness, and Utility multiplies all values, then: a * a > (a - x) * (a + x), which is: a² > a² - x². It does not however imply egalitarianism, as it is still better to have both children rich than both average or poor. (shrink)

Radical skepticism is the view that we know nothing or at least next to nothing. Nearly no one actually believes that skepticism is true. Yet it has remained a serious topic of discussion for millennia and it looms large in popular culture. What explains its persistent and widespread appeal? How does the skeptic get us to doubt what we ordinarily take ourselves to know? I present evidence from two experiments that classic skeptical arguments gain potency from an interaction between two (...) factors. First, people evaluate inferential belief more harshly than perceptual belief. Second, people evaluate inferential belief more harshly when its content is negative (i.e., that something is not the case) than when it is positive (i.e., that something is the case). It just so happens that potent skeptical arguments tend to focus our attention on negative inferential beliefs, and we are especially prone to doubt that such beliefs count as knowledge. That is, our cognitive evaluations are biased against this specific combination of source and content. The skeptic sows seeds of doubt by exploiting this feature of our psychology. (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)

The underreporting of suspected adverse drug reactions hinders pharmacovigilance. Solutions to underreporting are oftentimes directed at clinicians and health care professionals. However, given the recent rise of public inclusion in medical science, solutions may soon begin more actively involving patients. I aim to offer an evaluative framework for future possible proposals that would engage patients with the aim of mitigating underreporting. The framework may also have value in evaluating current reporting practices. The offered framework is composed of three criteria (...) that are bioethical, social-epistemic, and pragmatic: (i) patients should not be exposed to undue harms, e.g., nocebo effects; (ii) data should be collected, analyzed, and communicated prioritizing pharmacovigilance’s aims, i.e., free from industry bias; and (iii) proposals should account for existing and foreseeable pragmatic constraints like clinician ‘buy in’ and existing reporting infrastructure. Proposals to engage patients in pharmacovigilance that fulfil or address these criteria are preferable to those that do not. (shrink)

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)

This paper means to demonstrate the theoretical-and- methodological potential of a particular pattern of thought about culture. Employing an end-means and absolute value plus concept of reality approach, the continuous model of culture aims to embrace from one holistic standpoint various concepts and debates of the modern human, social, and political sciences. The paper revisits the debates of fact versus value, nature versus culture, culture versus structure, agency versus structure, and economics versus politics and offers the concepts of the rule (...) of law, state capitalism, a dialectical model of progress, and interpretative qualitative research, as well as of cultural diffusion, autonomy, alienation, and individuality. This model distinguishes between the ideal-symbolical and the instrumental functions of culture, sees culture as being sewn from universal binaries, and provides a certain understanding of the cognitive function of a value judgment, with positivism so far vague about the topic. It, too, suggests an extra method for investigating culture : the comparative literature study of culture enables social science to view literature as its potential in-depth interviewee— a case for arguing for a certain conception of interdisciplinarity as well. In addition, it predicts that cultural particularism or individuality remains an essential factor of human existence. Analyzing the issue of Eurocentrism in social science, the model finds modernity ’s concept of reality to be involved in ” methodological ” intellectualistic reductionism, characterizing it since the empiricism/ rationalism origination. Systematically confusing the universal oppositions in a Eurocentric manner, intellectualism becomes a contributing factor in unfolding post- modernity. (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.

Philip Kitcher rejects the global pessimists' view that the conclusions reached in inquiry are determined by the interests of some segment of the population, arguing that only some inquiries, for example, inquiries into race and gender, are adversely affected by interests. I argue that the biases Kitcher believes affect such inquiries are operative in all domains, but the prevalence of such biases does not support global pessimism. I argue further that in order to address the global pessimists' concerns, the scientific (...) community needs criticism from people with diverse interests and background assumptions. (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)