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)

The question of bias in methodology and terminology is a problem that faces researchers east, west, north and south; however, it faces Third World intellectuals with special keenness. For although they write in a cultural environment that has its own specific conceptual and cultural paradigms, they nevertheless encounter a foreign paradigm which attempts to impose itself upon their society and upon their very imagination and thoughts. When the term “developmental psychology” for instance is used in the West Arab scholars (...) also say “developmental psychology”, when “applied psychology” is mentioned they hurry to use the same term etc. Why not establish a new science with its own mechanisms, methodologies and points of reference to deal with epistemological biases and open up the gate of ijtihad with respect to them? This collection of papers aims to discover some of the biases latent in our terminology, methodologies, research tools, and conceptual principles, and to propose alternative ones marked by a greater degree of independence and neutrality. This is not to belittle the human value of the West’s creative contributions but to emphasize the danger of making it the ultimate point of reference and then trying to continuously play “catch up” with it. (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)

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)

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)

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)

(2013). A Review of Evidence on Consent Bias in Research. The American Journal of Bioethics: Vol. 13, No. 4, pp. 42-44. doi: 10.1080/15265161.2013.767958.

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)

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)

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)

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)

Neuroscience research, like all science, is vulnerable to the influence of extraneous values in the practice of research, whether in research design or the selection, analysis and interpretation of data. This is particularly problematic for research into the biological mechanisms that underlie behavior, and especially the neurobiological underpinnings of moral development and ethical reasoning, decision-making and behavior, and the other elements of what is often called the neuroscience of ethics. The problem arises because neuroscientists, like most (...) everyone, bring to their work assumptions, preconceptions and values and other sources of potentially inappropriate bias of which they may be unaware. It is important that the training of neuroscientists, and research practice itself, include open and in-depth discussion and examination of the assumptions that underlie research. Further, policy makers, journalists, and the general public, that is, the consumers of neuroscience research findings (and by extension, neurotechnologies) should be made aware of the limitations as well as the strengths of the science, the evolving nature of scientific understanding, and the often invisible values inherent in science. (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)

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.

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 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)

The increasing debate on corporate ethics raises the question of whether consumers are willing to reward and punish corporate behaviour based on its ethicality. In this context, this article investigates the direct effect on consumers' willingness to pay. Price response to product-related ethical information is explored in an experiment dealing with social issues in sportswear and environmental issues in consumer electronics. It is shown that in both areas, consumers demonstrate an increased willingness to pay for ethically produced goods. However, the (...) response is subject to a negativity bias. In contrast to prior research that used abstract stimulus measures, a ratio for quantifying this bias is suggested based on consumers' willingness to pay and their price expectations. This measure allows us to analyse a consumer's individual bias. (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)

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)

Empathy is sharing and understanding others’ emotions. Recently, researchers identified a culture–sex interaction effect in empathy. This phenomenon has been largely ignored by previous researchers. In this study, the culture–sex interaction effect was explored with a cohort of 129 participants (61 Australian Caucasians and 68 Chinese Hans) using both self-report questionnaires (i.e., Empathy Quotient and Interpersonal Reactivity Index) and computer-based empathy tasks. In line with the previous findings, the culture–sex interaction effect was observed for both trait empathy (i.e., the generalized (...) characteristics of empathy, as examined by the self-report questionnaires) and state empathy (i.e., the on-spot reaction of empathy for a specific stimulus, as evaluated by the computer-based tasks). Moreover, in terms of state empathy, the culture–sex interaction effect further interacted with stimulus traits (i.e., stimulus ethnicity, stimulus sex, or stimulus emotion) and resulted in three- and four-way interactions. Follow-up analyses of these higher-order interactions suggested that the phenomena of ethnic group bias and sex group favor in empathy varied among the four culture–sex participant groups (i.e., Australian female, Australian male, Chinese female, and Chinese male). The current findings highlighted the dynamic nature of empathy (i.e., its sensitivity toward both participant traits and stimulus features). Furthermore, the newly identified interaction effects in empathy deserve more investigation and need to be verified with other Western and Asian populations. (shrink)

The phenomenon known as matching bias consists of a tendency to see cases as relevant in logical reasoning tasks when the lexical content of a case matches that of a propositional rule, normally a conditional, which applies to that case. Matching is demonstrated by use of the negations paradigm that is by using conditionals in which the presence and absence of negative components is systematically varied. The phenomenon was first published in 1972 and the present paper reviews the history (...) of research and theorising on the problem in the subsequent 25 years. Theories of matching bias considered include those based on several broad frameworks including the heuristic-analytic theory, the mental models theory, the theory of optimal data selection, and relevance theory as well as the specific processing-negations account. The ability of these theories to account for a range of phenomena is considered, including the effects of linguistic form, realistic content, and explicit negation on the matching bias effect. Of particular importance are recent findings showing that the bias is observable on a wider range of linguistic forms than has generally been thought, and that it is almost entirely dependent on the use of implicit negation in the logical cases to which rules are applied. The reasons for the general suppression of matching when realistic content is used are, however, unclear and a need for further research is identified here. It is concluded that matching bias is a highly robust effect which is closely connected with the problem of understanding implicit negation. Most of the theories in the literature are unable to account for at least some of the major phenomena discovered in research on the bias. The accounts that fare best are those that posit local effects of negation, including the heuristic-analytic and processing negations theories. (shrink)

Animal welfare scientific literature has accumulated rapidly in recent years, but bias may exist which influences understanding of progress in the field. We conducted a survey of articles related to animal welfare or well being from an electronic database. From 8,541 articles on this topic, we randomly selected 115 articles for detailed review in four funding categories: government; charity and/or scientific association; industry; and educational organization. Ninety articles were evaluated after unsuitable articles were rejected. The welfare states of animals (...) in new treatments, conventional treatments or control groups with no treatment were classified as high, medium or low according to one or more. More articles were published in which the welfare of animals in new treatments was better than that of animals in the conventional or no treatment groups, demonstrating a positive result bias. Failure to publish studies with negative or inconclusive results may lead to other scientists unnecessarily repeating the research. The authors’ assessments of the welfare state of the groups were similarly rated high, medium or low, and it was found that new treatments were rated lower if the research was funded by industry, and higher when funded by charities, with government funding agencies intermediate. These differences were not evident in the Five Freedoms assessment, demonstrating an authors’ assessment bias that appeared to support the funding agencies’ interests. North American funded publications rated the welfare of animals in New treatments higher and those in a Conventional or No Treatment lower, compared with European-funded publications. It is concluded that preliminary evidence was provided of several forms of publication bias in animal welfare science. (shrink)

The effect of oxytocin on cognitive bias was investigated in rats in a modified conditioned place preference (CPP) paradigm. Fifteen male rats were trained to discriminate between two different cue combinations, one paired with palatable foods (reward training), and the other paired with unpalatable food (aversive training). Next, their reactions to two ambiguous cue combinations were evaluated and their latency to contact the goal pot recorded. Rats were injected with either oxytocin (OT) or saline with the prediction that rats (...) administered oxytocin would display a shorter average latency to approach on ambiguous trials. There was no significant difference between latencies to approach on ambiguous trials compared to reward trials, but the rats were significantly slower on the aversive compared to the ambiguous conditions. Oxytocin did not affect approach time; however, it was unclear, after follow-up testing, whether the OT doses tested were sufficient to produce the desired effects on cognitive bias. Future research should consider this possibility. (shrink)

When Artificial Intelligence (AI) is applied in decision-making that affects people’s lives, it is now well established that the outcomes can be biased or discriminatory. The question of whether algorithms themselves can be among the sources of bias has been the subject of recent debate among Artificial Intelligence researchers, and scholars who study the social impact of technology. There has been a tendency to focus on examples, where the data set used to train the AI is biased, and denial (...) on the part of some researchers that algorithms can also be biased. Here we illustrate the point that algorithms themselves can be the source of bias with the example of collaborative filtering algorithms for recommendation and search. These algorithms are known to suffer from cold-start, popularity, and homogenizing biases, among others. While these are typically described as statistical biases rather than biases of moral import; in this paper we show that these statistical biases can lead directly to discriminatory outcomes. The intuitive idea is that data points on the margins of distributions of human data tend to correspond to marginalized people. The statistical biases described here have the effect of further marginalizing the already marginal. Biased algorithms for applications such as media recommendations can have significant impact on individuals’ and communities’ access to information and culturally-relevant resources. This source of bias warrants serious attention given the ubiquity of algorithmic decision-making. (shrink)

Substantial research over the last ten years has indicated that many generative artificial intelligence systems (“GAI”) have the potential to produce biased results, particularly with respect to gender. This potential for bias has grown progressively more important in recent years as GAI has become increasingly integrated in multiple critical sectors, such as healthcare, consumer lending, and employment. While much of the study of gender bias in popular GAI systems is focused on text-based GAI such as OpenAI’s ChatGPT (...) and Google’s Gemini (formerly Bard), this article describes the results of a confirmatory experiment of gender bias in visual GAI systems. The authors argue that the potential for gender bias in visual GAI systems is potentially more troubling than bias in textual GAI because of the superior memorability of images and the capacity for emotional communication that images represent. They go on to offer four potential approaches to gender bias in visual GAI based on the roles visual GAI could play in modern society. The article concludes with a discussion of how dominant societal values could influence a choice between those four potential approaches to gender bias in visual GAI and some suggestions for further research. (shrink)

Animal welfare scientific literature has accumulated rapidly in recent years, but bias may exist which influences understanding of progress in the field. We conducted a survey of articles related to animal welfare or well being from an electronic database. From 8,541 articles on this topic, we randomly selected 115 articles for detailed review in four funding categories: government; charity and/or scientific association; industry; and educational organization. Ninety articles were evaluated after unsuitable articles were rejected. The welfare states of animals (...) in new treatments, conventional treatments or control groups with no treatment were classified as high, medium or low according to one or more. More articles were published in which the welfare of animals in new treatments was better than that of animals in the conventional or no treatment groups, demonstrating a positive result bias. Failure to publish studies with negative or inconclusive results may lead to other scientists unnecessarily repeating the research. The authors’ assessments of the welfare state of the groups were similarly rated high, medium or low, and it was found that new treatments were rated lower if the research was funded by industry, and higher when funded by charities, with government funding agencies intermediate. These differences were not evident in the Five Freedoms assessment, demonstrating an authors’ assessment bias that appeared to support the funding agencies’ interests. North American funded publications rated the welfare of animals in New treatments higher and those in a Conventional or No Treatment lower, compared with European-funded publications. It is concluded that preliminary evidence was provided of several forms of publication bias in animal welfare science. (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)

Women’s underrepresentation in science, technology, engineering, and mathematics (STEM) is related to the hierarchical social structure of gender relations in these fields. However, interventions to increase women’s participation have focused primarily on women’s interests rather than on STEM managers’ hiring practices. In this research, we examine STEM hiring practices, explore the implicit bias in criteria used by STEM managers, and suggest possible corrective solutions. Using an experimental design with 213 men and women STEM managers, we show that when (...) evaluating a female candidate, women and men STEM managers apply differential selection criteria, with men demonstrating implicit in-group gender favoritism in their hiring decisions. Specifically, the ability to work long hours was a more important criterion for male managers when evaluating a female candidate, forming an implicit gender bias, whereas female managers gave greater importance to problem-solving ability, a more gender-equal criterion. Adding a personal note to the curriculum vitae stating that the candidate had hired a full-time nanny was useful in decreasing the importance of the ability to work long hours criterion for men managers. We suggest individual and institutional interventions to reduce this bias, as a path to increasing women’s participation in STEM. (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)

Current research in artificial intelligence (AI) sheds light on algorithmic bias embedded in AI systems. The underrepresentation of women in the AI design sector of the tech industry, as well as in training datasets, results in technological products that encode gender bias, reinforce stereotypes and reproduce normative notions of gender and femininity. Biased behaviour is notably reflected in anthropomorphic AI systems, such as personal intelligent assistants (PIAs) and chatbots, that are usually feminized through various design parameters, such (...) as names, voices and traits. Gendering of AI entities, however, is often reduced to the encoding of stereotypical behavioural patterns that perpetuate normative assumptions about the role of women in society. The impact of this behaviour on social life increases, as human-to-(anthropomorphic)machine interactions are mirrored in human-to-human social interactions. This article presents current critical research on AI bias, focusing on anthropomorphic systems. Moreover, it discusses the significance of women’s engagement in AI design and programming, by presenting selected case studies of contemporary female media artists and designers. Finally, it suggests that women, through their creative practice, provide feminist and critical approaches to AI design which are essential for imagining alternative, inclusive, ethic and de-biased futures for anthropomorphic AIs. (shrink)

Gender bias is a recalcitrant problem in academia and society. However, dissent has been created on this issue. We focus on dissenting studies by Stephen J. Ceci and Wendy M. Williams, arguing that they reach conclusions that are unwarranted on the basis of the available evidence and that they ignore fundamental objections to their methodological decisions. Drawing on discussions from other contexts, particularly on manufactured dissent concerning anthropogenic climate change, we conclude that dissent on gender bias substantially contributes (...) to the exacerbation of biases in society and an increasing number of attacks on researchers, making it both epistemically and socially problematic. (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)

To analyze which ethically relevant biases have been identified by academic literature in artificial intelligence algorithms developed either for patient risk prediction and triage, or for contact tracing to deal with the COVID-19 pandemic. Additionally, to specifically investigate whether the role of social determinants of health have been considered in these AI developments or not. We conducted a scoping review of the literature, which covered publications from March 2020 to April 2021. ​Studies mentioning biases on AI algorithms developed for contact (...) tracing and medical triage or risk prediction regarding COVID-19 were included. From 1054 identified articles, 20 studies were finally included. We propose a typology of biases identified in the literature based on bias, limitations and other ethical issues in both areas of analysis. Results on health disparities and SDOH were classified into five categories: racial disparities, biased data, socio-economic disparities, unequal accessibility and workforce, and information communication. SDOH needs to be considered in the clinical context, where they still seem underestimated. Epidemiological conditions depend on geographic location, so the use of local data in studies to develop international solutions may increase some biases. Gender bias was not specifically addressed in the articles included. The main biases are related to data collection and management. Ethical problems related to privacy, consent, and lack of regulation have been identified in contact tracing while some bias-related health inequalities have been highlighted. There is a need for further research focusing on SDOH and these specific AI apps. (shrink)

Purpose The online economy has not resolved the issue of racial bias in its applications. While algorithms are procedures that facilitate automated decision-making, or a sequence of unambiguous instructions, bias is a byproduct of these computations, bringing harm to historically disadvantaged populations. This paper argues that algorithmic biases explicitly and implicitly harm racial groups and lead to forms of discrimination. Relying upon sociological and technical research, the paper offers commentary on the need for more workplace diversity within (...) high-tech industries and public policies that can detect or reduce the likelihood of racial bias in algorithmic design and execution. Design/methodology/approach The paper shares examples in the US where algorithmic biases have been reported and the strategies for explaining and addressing them. Findings The findings of the paper suggest that explicit racial bias in algorithms can be mitigated by existing laws, including those governing housing, employment, and the extension of credit. Implicit, or unconscious, biases are harder to redress without more diverse workplaces and public policies that have an approach to bias detection and mitigation. Research limitations/implications The major implication of this research is that further research needs to be done. Increasing the scholarly research in this area will be a major contribution in understanding how emerging technologies are creating disparate and unfair treatment for certain populations. Practical implications The practical implications of the work point to areas within industries and the government that can tackle the question of algorithmic bias, fairness and accountability, especially African-Americans. Social implications The social implications are that emerging technologies are not devoid of societal influences that constantly define positions of power, values, and norms. Originality/value The paper joins a scarcity of existing research, especially in the area that intersects race and algorithmic development. (shrink)

This study explores whether gender stereotypes about math ability shape high school teachers’ assessments of the students with whom they interact daily, resulting in the presence of conditional bias. It builds on theories of intersectionality by exploring teachers’ perceptions of students in different gender and racial/ethnic subgroups and advances the literature on the salience of gender across contexts by considering variation across levels of math course-taking in the academic hierarchy. Analyses of nationally representative data from the Education Longitudinal Study (...) of 2002 reveal that disparities in teachers’ perceptions of ability that favored white males over minority students of both genders are explained away by student achievement in the form of test scores and grades. However, we find evidence of a consistent bias against white females, which although relatively small in magnitude, suggests that teachers hold the belief that math is just easier for white males than it is for white females. In addition, we find some evidence of variation across course level contexts with regard to bias. We conclude by discussing the implications of our findings for research on the construction of gender inequality. (shrink)

There has been a longstanding bias in the study of spoken language towards using writing to analyse speech. This approach is problematic in that it assumes language to be derived from an autonomous mental capacity to assemble words into sentences, while failing to acknowledge culture-specific ideas linked to writing. Words and sentences are writing constructs that hardly capture the sound-making actions involved in spoken language. This book brings to light research that has long revealed structures present in all (...) languages but which do not match the writing-induced concepts of traditional linguistic analysis. It demonstrates that language processes are not physiologically autonomous, and that speech structures are structures of spoken language. It then illustrates how speech acts can be studied using instrumental records, and how multisensory experiences in semantic memory couple to these acts, offering a biologically-grounded understanding of how spoken language conveys meaning and why it develops only in humans. (shrink)

In this review I describe research conducted in my laboratory concerning implicit mood-congruent memory (MCM) bias in clinical depression. MCM is the tendency for depressed individuals to retrieve more unpleasant information from memory than nondepressed controls, and may be an important maintenance mechanism in depression. MCM has been studied frequently with explicit memory tests, but relatively few studies have investigated MCM using implicit memory tests. I describe several implicit memory studies which show that: (a) an implicit MCM (...) class='Hi'>bias does not appear to exist when perceptually driven tests are used; (b) implicit memory bias can be found when conceptually driven tests are used, but (c) not all conceptually driven tests show implicit MCM bias. I conclude that conceptual processing is necessary, but is not sufficient for demonstrating implicit memory bias in depression. Future studies should investigate specific components of conceptual elaboration that support implicit memory bias in depression. (shrink)

B a c k g r o u n d. The article is devoted to the study of confirmatory distortion as a cognitive bias within the framework of the modern theory of argumentation. In the context of this study, the effectiveness of the critical questioning technique as an argumentation strategy aimed at reducing the negative impact of confirmatory bias is considered. M e t h o d s. To achieve the goals of the research, the method of (...) critical questions is used, which is based on the traditional principles of logic, dialectics and rhetoric. Specific lists of critical questions are developed for each argumentative scheme. R e s u l t s. The article demonstrates that standard critical questions for schemes of practical reasoning, developed by eminent specialists, are able to minimize the negative impact of confirmation bias. This is achieved by taking into account information that may conflict with the agent's action plan. C o n c l u s i o n s. The study highlights the importance of using critical questions as a tool to minimize confirmation bias. Such an approach not only contributes to the substantiation of arguments, but also stimulates self-control and the search for information that may cause doubts about one's own views. The final part of the article examines propaganda as the deliberate use of confirmatory distortion and points to the need for attention to language patterns where it occurs rather unintentionally. In connection with the specificity of the studied phenomenon, the term "confirmation bias" is proposed as a translation of the English "confirmation bias". (shrink)

BackgroundDescriptive studies examining publication rates and citation counts demonstrate a geographic skew toward high-income countries (HIC), and research from low- or middle-income countries (LMICs) is generally underrepresented. This has been suggested to be due in part to reviewers’ and editors’ preference toward HIC sources; however, in the absence of controlled studies, it is impossible to assert whether there is bias or whether variations in the quality or relevance of the articles being reviewed explains the geographic divide. This study (...) synthesizes the evidence from randomized and controlled studies that explore geographic bias in the peer review process.MethodsA systematic review was conducted to identify research studies that explicitly explore the role of geographic bias in the assessment of the quality of research articles. Only randomized and controlled studies were included in the review. Five databases were searched to locate relevant articles. A narrative synthesis of included articles was performed to identify common findings.ResultsThe systematic literature search yielded 3501 titles from which 12 full texts were reviewed, and a further eight were identified through searching reference lists of the full texts. Of these articles, only three were randomized and controlled studies that examined variants of geographic bias. One study found that abstracts attributed to HIC sources elicited a higher review score regarding relevance of the research and likelihood to recommend the research to a colleague, than did abstracts attributed to LIC sources. Another study found that the predicted odds of acceptance for a submission to a computer science conference were statistically significantly higher for submissions from a “Top University.” Two of the studies showed the presence of geographic bias between articles from “high” or “low” prestige institutions.ConclusionsTwo of the three included studies identified that geographic bias in some form was impacting on peer review; however, further robust, experimental evidence is needed to adequately inform practice surrounding this topic. Reviewers and researchers should nonetheless be aware of whether author and institutional characteristics are interfering in their judgement of research. (shrink)

Research in behaviour genetics uncovers causes of behaviour at the population level. For inferences about individuals we also need to know how genes and the environment affect phenotypes. Behaviour genetics fosters a biased view of individual behaviour since it identifies the environment with psychosocial factors and disregards ecology.

Most research on transmission biases in cultural evolution has treated different biases as distinct strategies. Here I present a model that combines both frequency dependent bias (including conformist bias) and payoff bias in a single decision-making calculus and show that such an integrated learning strategy may be superior to relying on either bias alone. Natural selection may operate on humans’ relative dependence on frequency and payoff information, but both are likely to contribute to the spread (...) of variants with high payoffs. Importantly, the magnitude of conformist bias affects the evolutionary dynamics, and I show that an intermediate level of conformity may be most adaptive and may spontaneously evolve as it resists the invasion of low-payoff variants yet enables the fixation of high-payoff variants in the population. (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)