: In the last two decades, scientists, government officials, and science policy experts have expressed concerns about the increasing role of financial interests in research. Many believe that these interests are undermining research by causing bias and error, suppression of results, and even outright fraud. This paper seeks to shed some light on this view by (1) explicating the concept research bias, (2) describing some ways that financial interests can cause research biases, and (3) (...) discussing some strategies for mitigating or managing the influence of financial interests. These strategies include (a) using government funds to counter-balance privately funded research, (b) increasing public input into government funding decisions, (c) disclosing and managing conflicts of interest in research, (d) auditing data, (e) expanding access to data. Since it is neither possible nor desirable to eliminate financial interests from research, the wisest policy is to manage and counter-balance these interests for the good of science and society. (shrink)

When interests and preferences of researchers or their sponsors cause bias in experimental design, data interpretation or dissemination of research results, we normally think of it as an epistemic shortcoming. But as a result of the debate on science and values, the idea that all extra-scientific influences on research could be singled out and separated from pure science is now widely believed to be an illusion. I argue that nonetheless, there are cases in which research is (...) rightfully regarded as epistemologically deficient due to the influence of preferences on its outcomes. I present examples from biomedical research and offer an analysis in terms of social epistemology. (shrink)

When ethical decisions have to be taken in critical, complex medical situations, they often involve decisions that set the course for or against life-sustaining treatments. Therefore the decisions have far-reaching consequences for the patients, their relatives, and often for the clinical staff. Although the rich psychology literature provides evidence that reasoning may be affected by undesired influences that may undermine the quality of the decision outcome, not much attention has been given to this phenomenon in health care or ethics consultation. (...) In this paper, we aim to contribute to the sensitization of the problem of systematic reasoning biases by showing how exemplary individual and group biases can affect the quality of decision-making on an individual and group level. We are addressing clinical ethicists as well as clinicians who guide complex decision-making processes of ethical significance. Knowledge regarding exemplary group psychological biases (e.g. conformity bias), and individual biases (e.g. stereotypes), will be taken from the disciplines of social psychology and cognitive decision science and considered in the field of ethical decision-making. Finally we discuss the influence of intuitive versus analytical (systematical) reasoning on the validity of ethical decision-making. (shrink)

For synergistic interactions between humans and artificial intelligence (AI) systems, AI outputs often need to be explainable to people. Explainable AI (XAI) systems are commonly tested in human user studies. However, whether XAI researchers consider potential cultural differences in human explanatory needs remains unexplored. We highlight psychological research that found significant differences in human explanations between many people from Western, commonly individualist countries and people from non-Western, often collectivist countries. We argue that XAI research currently overlooks these variations (...) and that many popular XAI designs implicitly and problematically assume that Western explanatory needs are shared cross-culturally. Additionally, we systematically reviewed over 200 XAI user studies and found that most studies did not consider relevant cultural variations, sampled only Western populations, but drew conclusions about human-XAI interactions more generally. We also analyzed over 30 literature reviews of XAI studies. Most reviews did not mention cultural differences in explanatory needs or flag overly broad cross-cultural extrapolations of XAI user study results. Combined, our analyses provide evidence of a cultural bias toward Western populations in XAI research, highlighting an important knowledge gap regarding how culturally diverse users may respond to widely used XAI systems that future work can and should address. (shrink)

Current research has documented how cases of irresponsible corporate behavior generate negative reactions from consumers and other stakeholders. Existing research, however, has not examined empirically whether the characteristics of the victims of corporate malfeasance contribute to shaping individual reactions. This study examines, through four experimental surveys, the role played by the national identity of the people affected on consumers’ intentions to spread negative word of mouth. It is shown that national identity influences individual reactions indirectly; mediated by perceived (...) similarity and sympathy. Consumers perceive foreign victims as different from the self and this reduces the sympathy experienced towards them. Sympathy is an emotion that shapes consumer reactions and regulates WOM. The study identifies two moderating processes of this effect. Individuals who score high on collective narcissism are most likely to be strongly biased against foreign victims. In-group bias is also moderated by the perceived severity of the crisis. When a case is perceived as very serious, perceived similarity plays a less important role in generating sympathy because consumers focus on the perceived suffering of the victims. Hence, in-group bias is stronger in cases perceived as having minor consequences. The paper contributes to the literature on corporate social irresponsibility and offers implications for both scholars and managers. (shrink)

Gender is one of the most researched and contentious topics in consumer ethics research. It is common for researchers of gender studies to presume that women are more ethical than men because of their reputation for having a selfless, sensitive nature. Nevertheless, we found evidence that women behaved less ethically than men in two field experiments testing a passive form of unethical behavior. Women benefited to a larger extent from a cashier miscalculating the bill in their favor than men. (...) However, in three follow-up studies, we found that women did not necessarily intend to benefit at the expense of someone else. Women are less prone to speak up to a cashier than men are, even when the mistake is made in their disfavor. These results reveal that gender differences in assertiveness affect differences in unethical behavior. (shrink)

This study examines the impact of a social desirability response bias as a personality characteristic (self-deception and impression management) and as an item characteristic (perceived desirability of the behavior) on self-reported ethical conduct. Findings from a sample of college students revealed that self-reported ethical conduct is associated with both personality and item characteristics, with perceived desirability of behavior having the greatest influence on self-reported conduct. Implications for research in business ethics are drawn, and suggestions are offered for reducing (...) the effects of a socially desirable response bias. (shrink)

Gender is one of the most researched and contentious topics in consumer ethics research. It is common for researchers of gender studies to presume that women are more ethical than men because of their reputation for having a selfless, sensitive nature. Nevertheless, we found evidence that women behaved less ethically than men in two field experiments testing a passive form of unethical behavior. Women benefited to a larger extent from a cashier miscalculating the bill in their favor than men. (...) However, in three follow-up studies, we found that women did not necessarily intend to benefit at the expense of someone else. Women are less prone to speak up to a cashier than men are, even when the mistake is made in their disfavor. These results reveal that gender differences in assertiveness affect differences in unethical behavior. (shrink)

The concept of equipoise is considered by many to be part of the ethical justification for using human subjects in clinical research. In general, equipoise indicates some uncertainty about the relative merits of the experimental intervention compared to existing treatments. Relieving this uncertainty gives scientific value to an experiment, thereby making the risks to human subjects in the trial acceptable, other considerations notwithstanding. But characterizing equipoise remains controversial since Freedman’s groundbreaking publication on the subject. We offer a new account (...) of equipoise that draws on and extends an option Freedman discarded. After establishing the importance of some account of equipoise as part of ethically justified clinical trials, we revisit Freedman’s distinction between clinical and theoretical equipoise. We raise concerns about Freedman’s preferred clinical equipoise and then rehabilitate theoretical equipoise. In particular, we use a variety of arguments from epistemology to show how Freedman was too hasty in rejecting theoretical equipoise. In addition, we argue that theoretical equipoise is a subspecies of epistemic equipoise, which we characterize as a form of uncertainty that is the result of the possibility of error. This type of uncertainty can best be alleviated by research, which produces beliefs supported by strong statistical evidence, which is a key aim of clinical trials. Further, this type of uncertainty can explain why even clinicians with more firsthand experience with an intervention than their peers, and who may not be in theoretical equipoise, could still justifiably support a trial designed to ameliorate the possibility of error due to cognitive bias. (shrink)

Researchers increasingly rely on large data sets of health information, often linked with biological specimens. In recent years, the argument has been made that obtaining informed consent for conducting records-based research is unduly burdensome and results in ?consent bias.? As a type of selection bias, consent bias is said to exist when the group giving researchers access to their data differs from the group denying access. Therefore, to promote socially beneficial research, it is argued that (...) consent should be unnecessary. After analyzing the biostatistics evidence and bioethics arguments, the article concludes that (1) claims about the amount of consent bias are overstated; (2) commonly used statistical methods usually can account for consent bias; and (3) any residual effects of consent bias are below an acceptable level of imprecision and constitute a reasonable social cost for conducting ethically responsible research. (shrink)

Cesario's critiques and suggestions for redesigning social psychology experiments echo Dahl's call for developmental researchers to use experimental and naturalistic methods in a complementary manner for understanding children's development. We provide examples of how naturalistic observations can rectify Cesario's missing flaws for developmental studies investigating children's social biases and help researchers derive theories they can then experimentally test.

Randomised controlled trials (RCTs) are often seen as the 'gold standard' of evaluative research. However, whilst randomisation will ensure comparable groups, trials are still vulnerable to a range of biases that can undermine their internal validity. In this paper we describe a number of common threats to the internal validity of RCTs and methods of countering them. We highlight a number of examples from randomised trials in education and health care where problems of execution and analysis of the RCT (...) has undermined their internal validity. However, awareness of these potential biases can lead to careful planning to avoid or reduce their occurrence. If good quality randomised trials are to inform policy and practice in education then rigorous trials need to be designed that are the least susceptible to threats to their validity. (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)

BackgroundPublication and outcome reporting bias is often caused by researchers selectively choosing which scientific results and outcomes to publish. This behaviour is ethically significant as it distorts the literature used for future scientific or clinical decision-making. This study investigates the practicalities of using ethics applications submitted to a UK National Health Service research ethics committee to monitor both types of reporting bias.MethodsAs part of an internal audit we accessed research ethics database records for studies submitting an (...) end of study declaration to the Hampshire A research ethics committee between 1st January 2010 and 31st December 2011. A literature search was used to establish the publication status of studies. Primary and secondary outcomes stated in application forms were compared with outcomes reported in publications.ResultsOut of 116 studies the literature search identified 57 publications for 37 studies giving a publication rate of 32 %. Original Research Ethics Committee applications could be obtained for 28 of the published studies. Outcome inconsistencies were found in 16 of the published studies.ConclusionsThis study showed that the problem of publication and outcome reporting bias is still significant in the UK. The method described here demonstrates that UK NHS research ethics committees are in a good position to detect such bias due to their unique access to original research protocols. Data gathered in this way could be used by the Health Research Authority to encourage higher levels of transparency in UK research. (shrink)

Social desirability bias (SDB) is one of the main concerns in self-reported studies that measures explicit attitudes such as ethics research. Although SDB was introduced since the early 1950s, little effort has been made to understand the necessity of including an SDB scale in studies of sensitive topics such as ethics. The purpose of this paper was to (1) identify whether current ethics-related studies considered SDB when conducting their research and (2) ascertain whether SDB was a significant (...) variable in such studies. This investigation takes the form of a systematic review of articles published within the last 20 years in well-known business ethics journals (2000–2019). We found that (a) only 13.67% of ethics research measured SDB; (b) although the majority of the reviewed articles were from the West, researchers in Asia have also made significant progress in recent years in measuring SDB in their studies; (c) SDB was used mainly as a control variable and as such researchers preferred scales with fewer items; and (d) SDB was unavoidable even when using online surveys. Based on our findings, we attempt to provide an overview of SDB in ethics research and encourage ethics researchers who adopt self-reported surveys to include an SDB measurement in their studies to control SDB. (shrink)

Gender is one of the most frequently studied variables within the ethics literature. In prior studies that find gender differences, females consistently report more ethical responses than males. However, prior research also indicates that females are more prone to responding in a socially desirable fashion. Consequently, it is uncertain whether gender differences in ethical decision-making exist because females are more ethical or perhaps because females are more prone to the social desirability response bias. Using a sample of 30 (...) scenarios from prior studies that find gender differences, we examine whether these gender differences remain robust once social desirability is controlled for in the analysis. Our data suggest that the effect of gender on ethical decision-making is largely attenuated once social desirability is included in the analysis. In essence, the social desirability response bias appears to be driving a significant portion of the relationship between gender and ethical decision-making. We discuss several important research implications of this study. (shrink)

Empirical data can be an extremely powerful and influential tool in bioethical research. However, when researchers or policy makers look for answers to ethical questions by engaging with empirical research, there can be a tendency (conscious or unconscious) to shape, report, and use empirical research in a way that confirms their own preferred ethical conclusions. This skewing effect - what we call ‘normative bias’ - is often so subtle it falls short of clear misconduct and thus (...) can be difficult to call out. However, we argue that this subtle influence of bias has the potential to significantly influence debate and policy around highly sensitive ethical issues and must be guarded against. In this paper we share the lessons we have learned through a journey of self-reflection around the effect that normative bias can have when reporting on and referring to empirical data relating to ethical issues. We use a variety of papers from our area of the ethics of routine prenatal screening to illustrate these subtle but often powerfully distorting effects of bias. Our aim in doing so is not to criticise the work of others, as we recognise our own normative bias, but to improve awareness of this issue, remind the need for reflexivity to guard against our own biases, and introduce a new criterion - the idea of a ‘limitation prominence assessment’ - that can work as a practical way to evaluate the seriousness of the limitations of an empirical study and thus, the risks of the study being misread or misinterpreted through superficial reading. (shrink)

he paper analyses migration flows from the Philippines in two gendered occupations: domestic helpers and computer programmers. The international division of labour theory claims that foreign investment determines migration from developing countries, especially of women, towards low-skilled gendered occupations in developed countries. This paper shows that the division of labour is neither gendered nor international in the predicted sense. For instance, data from Philippines Overseas Employment Agency shows that the theory is Eurocentric as Northern America and Europe are destinations for (...) only 3 per cent of domestic workers’ flows. The paper argues that neo-Marxism creates bias in gender and migration research and hinders understanding of important gendered effects concerning migrants. Two examples of such gendered effects are highlighted here: the higher vulnerability to legislative change of migrant men employed as domestic workers in Italy and the higher penetration of women into computer programming in the migrant flows to the U.S. (shrink)

Research on academic pay finds an unexplained gender pay gap that has not fully dissolved over time and that appears to increase with years of experience. In this study, I consider how role congruity bias contributes to this pay gap. Bias is more likely to manifest in a context where there is some ambiguity about performance and where stereotypes are stronger. I predict that bias in the attribution of credit for coauthored research leads to lower (...) returns to research for female professors. To test this prediction, I use a sample of Canadian faculty in accounting, where research is typically coauthored, where females are underrepresented at the most senior ranks, and where many universities evaluate merit in research, teaching, and service to determine salary increases. In regressions of salary on individual and institutional determinants of salary, I find that women earn marginally less than men. However, the pay gap is only evident for women who publish in a selective list of journals; for the subset of faculty with no publications from this list, there are no significant differences in salary. For researching faculty, the pay gap relates specifically to research productivity. While women publish less on average than men, the returns to their research are also lower. In particular, the relation between the individual’s research ranking and salary is significantly lower for women who publish a higher proportion of their work with men, than for all other faculty. Additional analysis of salary and coauthor patterns confirms that women receive significantly less credit for coauthored articles they publish with men than those they publish with other women but that no similar variations in reward are evident for men across publishing patterns. These findings suggest bias in the attribution of credit for coauthored research in the determination of salary, consistent with role congruity theory, and provide an important potential explanation for why salaries for women vary systematically from those of men even after considering productivity. Providing lower rewards for equal work represents a continuing ethical issue in academe and compounds the challenges women already facing in the profession. (shrink)

Exploratory studies employing volunteer subjects are especially vulnerable to race and class bias. This article illustrates how inattention to race and class as critical dimensions in women's lives can produce biased research samples and lead to false conclusions. It analyzes the race and class background of 200 women who volunteered to participate in an in-depth study of Black and White professional, managerial, and administrative women. Despite a multiplicity of methods used to solicit subjects, White women raised in middle-class (...) families who worked in male-dominated occupations were the most likely to volunteer, and White women were more than twice as likely to respond to media solicitations or letters. To recruit most Black subjects and address their concerns about participation required more labor-intensive strategies involving personal contact. The article discusses reasons for differential volunteering and ways to integrate race and class into qualitative research on women. (shrink)

In this essay, I want to identify an invidious bias that is embedded in much research into sex differences. I shall argue that bias against women is endemic in any such research programme that fails to take account at every stage of women's social inequality. It is primarily because its view of the relation between sexual difference and sexual inequality is too simplistic that much sex differences research rationalizes and so perpetuates women's subordination.

There are two problems with the logic of Cesario's argument for abandoning existing research on social bias. First, laboratory findings of decisional bias have social significance even if Cesario is right that the research strips away real-world context. Second, the argument makes overly skeptical demands of a research program seeking complex causal linkages between micro- and macro-scale phenomena.

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

Abstract:Suppose we want to know whether the ethics of persons with one characteristic differ from the ethics of persons having another characteristic. Self-selection bias occurs if people have control over that characteristic. When there is self-selection bias, we cannot be sure observed differences in ethics are correlated with the characteristic or are the result of individual self-selection. Self-selection bias is germane to many important business ethics questions. In this paper I explain what self-selection bias is, how (...) it relates to business ethics research, and how to correct for it. I also illustrate the correction process in an empirical analysis of the effect of organizational rank on worker ethics. Using data from the European Values Survey, I find that being a supervisor is positively correlated with worker ethics. However, I also find a negative self-selection effect. Workers with relatively lower ethics are selected into supervisory roles. (shrink)

In the mid-1980s, social scientists compared outcome measures of related drug studies, some funded by private companies and others by nonprofit organizations or government agencies. The concept of a “funding effect” was coined when it was discovered that study outcomes could be statistically correlated with funding sources, largely in drug safety and efficacy studies. Also identified in tobacco research and chemical toxicity studies, the “funding effect” is often attributed, implicitly or explicitly, to research bias. This article discusses (...) the meaning of scientific bias in research, examines the strongest evidence for the “funding effect,” and explores the question of whether the “funding effect” is an indicator of biased research that is driven by the financial interests of the for-profit sponsor. This article argues that the “funding effect” is merely a symptom of the factors that could be responsible for outcome disparities in product assessment. Social scientists should not suspend their skepticism and choose as a default hypothesis that bias is always or typically the cause. (shrink)

BackgroundThe public and healthcare workers have a high expectation of animal research which they perceive as necessary to predict the safety and efficacy of drugs before testing in clinical trials. However, the expectation is not always realised and there is evidence that the research often fails to stand up to scientific scrutiny and its 'predictive value' is either weak or absent.DiscussionProblems with the use of animals as models of humans arise from a variety of biases and systemic failures (...) including: 1) bias and poor practice in research methodology and data analysis ; 2) lack of transparency in scientific assessment and regulation of the research; 3) long-term denial of weaknesses in cross-species translation; 4) profit-driven motives overriding patient interests; 5) lack of accountability of expenditure on animal research; 6) reductionist-materialism in science which tends to dictate scientific inquiry and control the direction of funding in biomedical research.SummaryBias in animal research needs to be addressed before medical research and healthcare decision-making can be more evidence-based. Research funding may be misdirected on studying 'disease mechanisms' in animals that cannot be replicated outside tightly controlled laboratory conditions, and without sufficient critical evaluation animal research may divert attention away from avenues of research that hold promise for human health. The potential for harm to patients and trial volunteers from reliance on biased animal data1 requires measures to improve its conduct, regulation and analysis. This article draws attention to a few of the many forms of bias in animal research that have come to light in the last decade and offers a strategy incorporating ten recommendations stated at the end of each section on bias. The proposals need development through open debate and subsequent rigorous implementation so that reviewers may determine the value of animal research to human health. The 10Rs + are protected by a Creative Commons Attribution 3.0 Unported License and therefore may be 'shared, remixed or built on, even commercially, so long as attributed by giving appropriate credit with a link to the license, and indicate if changes were made.’. (shrink)

Inferences from clinical research results to estimates of therapeutic effectiveness suffer due to various biases. I argue that predictions of medical effectiveness are prone to failure because current medical research overlooks the impacts of a particularly detrimental set of biases: meta-biases. Meta-biases are linked to higher-level characteristics of medical research and their effects are only observed when comparing sets of studies that share certain meta-level properties. I offer a model for correcting research results based on meta- (...) class='Hi'>research evidence, the bias dynamics model, which employs regularly updated empirical bias coefficients to attenuate estimates of therapeutic effectiveness. (shrink)

BackgroundHealth data holds great potential for improved treatments. Big data research and machine learning models have been shown to hold great promise for improved diagnostics and treatment planning. The potential is tied, however, to the availability of personal health data. In recent years, it has been argued that data from health records should be available for health research, and that individuals have a duty to make the data available for such research. A central point of debate is (...) whether such secondary use of health data requires informed consent.Main bodyIn response to recent writings this paper argues that a requirement of informed consent for health record research must be upheld. It does so by exploring different contrasting notions of the duty of easy rescue and arguing that none of them entail aperfectduty to participate in health record research. In part because the costs of participation cannot be limited to 1) the threat of privacy breaches, but includes 2) the risk of reduced trust and 3) suboptimal treatment, 4) stigmatization and 5) medicalisation, 6) further stratification of solidarity and 7) increased inequality in access to treatment and medicine. And finally, it defends the requirement of informed consent by arguing that the mere possibility of consent bias provides a rather weak reason for making research participation mandatory, and that there are strong, independent reasons for making.ConclusionArguments from the duty of easy rescue in combination with claims about little risk of harm and potential consent bias fail to establish not only aperfectduty to participate in health record research, but also that participation in such research should be mandatory. On the contrary, an analysis of these arguments indicates that the duty to participate in research is most adequately construed as animperfectduty, and reveals a number of strong reasons for insisting that participation in health records research is based on informed consent. (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)

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)

All else being equal, most of us typically prefer to have positive experiences in the future rather than the past and negative experiences in the past rather than the future. Recent empirical evidence tends not only to support the idea that people have these preferences, but further, that people tend to prefer more painful experiences in their past rather than fewer in their future (and mutatis mutandis for pleasant experiences). Are such preferences rationally permissible, or are they, as time-neutralists contend, (...) rationally impermissible? And what is it that grounds their having the normative status that they do have? We consider two sorts of arguments regarding the normative status of future-biased preferences. The first appeals to the supposed arbitrariness of these preferences, and the second appeals to their upshot. We evaluate these arguments in light of the recent empirical research on future-bias. (shrink)

“Implicit bias” is a term of art referring to relatively unconscious and relatively automatic features of prejudiced judgment and social behavior. While psychologists in the field of “implicit social cognition” study “implicit attitudes” toward consumer products, self-esteem, food, alcohol, political values, and more, the most striking and well-known research has focused on implicit attitudes toward members of socially stigmatized groups, such as African-Americans, women, and the LGBTQ community.[1] For example, imagine Frank, who explicitly believes that women and men (...) are equally suited for careers outside the home. Despite his explicitly egalitarian belief, Frank might nevertheless implicitly associate women with the home, and this implicit association might lead him to behave in any number of biased ways, from trusting feedback from female co-workers less to hiring equally qualified men over women. Psychological research on implicit bias is relatively recent (§1), but a host of metaphysical (§2), epistemological (§3), and ethical questions (§4) about implicit bias are pressing.[2]. (shrink)

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)

At the University of Sheffield during 2011 and 2012, a leading group of philosophers, psychologists, and others gathered to explore the nature and significance of implicit bias. The two volumes of Implicit Bias and Philosophy emerge from these workshops. Each volume philosophically examines core areas of psychological research on implicit bias as well as the ramifications of implicit bias for core areas of philosophy. Volume I: Metaphysics and Epistemology is comprised of two parts: “The Nature (...) of Implicit Attitudes, Implicit Bias, and Stereotype Threat,” and “Skepticism, Social Knowledge, and Rationality.” The first part contains chapters examining the relationship between implicit attitudes and “dual process” models of the mind; the role of affect in the formation and change of implicit associations; the unity (or disunity) of implicit attitudes; whether implicit biases are mental states at all; and whether performances on stereotype-relevant tasks are automatic and unconscious or intentional and strategic. The second part contains chapters examining implicit bias and skepticism; the effects of implicit bias on scientific research; the accessibility of social stereotypes in epistemic environments; the effects of implicit bias on the self-perception of members of stigmatized social groups as rational agents; the role of gender stereotypes in philosophy; and the role of heuristics in biased reasoning. (shrink)

Research on bias in peer review examines scholarly communication and funding processes to assess the epistemic and social legitimacy of the mechanisms by which knowledge communities vet and self-regulate their work. Despite vocal concerns, a closer look at the empirical and methodological limitations of research on bias raises questions about the existence and extent of many hypothesized forms of bias. In addition, the notion of bias is predicated on an implicit ideal that, once articulated, (...) raises questions about the normative implications of research on bias in peer review. This review provides a brief description of the function, history, and scope of peer review; articulates and critiques the conception of bias unifying research on bias in peer review; characterizes and examines the empirical, methodological, and normative claims of bias in peer review research; and assesses possible alternatives to the status quo. We close by identifying ways to expand conceptions and studies of bias to countenance the complexity of social interactions among actors involved directly and indirectly in peer review. (shrink)

Data‐driven algorithms are widely used to make or assist decisions in sensitive domains, including healthcare, social services, education, hiring, and criminal justice. In various cases, such algorithms have preserved or even exacerbated biases against vulnerable communities, sparking a vibrant field of research focused on so‐called algorithmic biases. This research includes work on identification, diagnosis, and response to biases in algorithm‐based decision‐making. This paper aims to facilitate the application of philosophical analysis to these contested issues by providing an overview (...) of three key topics: What is algorithmic bias? Why and how can it occur? What can and should be done about it? Throughout, we highlight connections—both actual and potential—with philosophical ideas and concerns. (shrink)

Recent social‐psychological research suggests that a considerable amount of, for example, racial and gendered discrimination may be connected to implicit biases: mental processes beyond our direct control or endorsement, that influence our behaviour toward members of socially salient groups. In this article I seek to improve our understanding of the phenomenon of implicit bias, including its moral status, by examining it through the lens of a theory of discrimination. In doing so, I also suggest ways to improve this (...) theory of discrimination, by creating conceptual space for implicit bias discrimination. I explore two ways of distinguishing direct and indirect discrimination and spell out the resulting four different forms of discrimination. The resulting taxonomy provides some room for implicit bias discrimination. I also deal with four challenges to my proposal for capturing implicit bias within discrimination theory: the metaphysical challenge, the moral insignificance challenge, the causal connection challenge, and the challenge from irreducibly collective bias. (shrink)

In this paper, I sketch a general framework for theorizing about bias and bias attributions. According to the account, paradigmatic cases of bias involve systematic departures from genuine norms. I attempt to show that the account illuminates a number of important psychological phenomena, including: the fact that accusations of bias frequently inspire not only denials but also countercharges of bias (“you only think that I'm biased because you're biased!”); the fact that we tend to see (...) ourselves as less biased than our peers (the so‐called ‘bias blind spot’); and the fact that we tend to see people who share our views as less biased than people who don't. I explore the circumstances in which we're committed to believing that those who disagree with us are not only mistaken but also biased simply because they disagree with us in the way that they do. In addition, the account also sheds light on another notorious and well‐documented psychological phenomenon: the fact that introspection is an unreliable way of detecting our biases. On the account that I offer, the unreliability of introspection for this purpose isn't a contingent fact that depends on the finer details of human psychology but rather holds of necessity: even God could not have made us creatures who reliably detect our own biases by way of introspection. (shrink)

Implicit biases involve associations outside conscious awareness that lead to a negative evaluation of a person on the basis of irrelevant characteristics such as race or gender. This review examines the evidence that healthcare professionals display implicit biases towards patients. PubMed, PsychINFO, PsychARTICLE and CINAHL were searched for peer-reviewed articles published between 1st March 2003 and 31st March 2013. Two reviewers assessed the eligibility of the identified papers based on precise content and quality criteria. The references of eligible papers were (...) examined to identify further eligible studies. Forty two articles were identified as eligible. Seventeen used an implicit measure, to test the biases of healthcare professionals. Twenty five articles employed a between-subjects design, using vignettes to examine the influence of patient characteristics on healthcare professionals’ attitudes, diagnoses, and treatment decisions. The second method was included although it does not isolate implicit attitudes because it is recognised by psychologists who specialise in implicit cognition as a way of detecting the possible presence of implicit bias. Twenty seven studies examined racial/ethnic biases; ten other biases were investigated, including gender, age and weight. Thirty five articles found evidence of implicit bias in healthcare professionals; all the studies that investigated correlations found a significant positive relationship between level of implicit bias and lower quality of care. The evidence indicates that healthcare professionals exhibit the same levels of implicit bias as the wider population. The interactions between multiple patient characteristics and between healthcare professional and patient characteristics reveal the complexity of the phenomenon of implicit bias and its influence on clinician-patient interaction. The most convincing studies from our review are those that combine the IAT and a method measuring the quality of treatment in the actual world. Correlational evidence indicates that biases are likely to influence diagnosis and treatment decisions and levels of care in some circumstances and need to be further investigated. Our review also indicates that there may sometimes be a gap between the norm of impartiality and the extent to which it is embraced by healthcare professionals for some of the tested characteristics. Our findings highlight the need for the healthcare profession to address the role of implicit biases in disparities in healthcare. More research in actual care settings and a greater homogeneity in methods employed to test implicit biases in healthcare is needed. (shrink)

The bias–variance tradeoff is a theoretical concept that suggests machine learning algorithms are susceptible to two kinds of error, with some algorithms tending to suffer from one more than the other. In this letter, we claim that the bias–variance tradeoff is a general concept that can be applied to human cognition as well, and we discuss implications for research in cognitive science. In particular, we show how various strands of research in cognitive science can be interpreted (...) in light of the bias–variance tradeoff, giving insight into individual differences in learning, the nature of cognitive processes, and debates in cognitive science research. (shrink)