Health technology assessment (HTA) is often biased in the sense that it neglects relevant perspectives on the technology in question. To incorporate different perspectives in HTA, we should pursue agreement about what are relevant, plausible, and feasible research questions; interactive technology assessment (iTA) might be suitable for this goal. In this way a kind of procedural ethics is established. Currently, ethics too often is focussed on the application of general principles, which leaves a lot of confusion as to what really (...) is the matter in specific cases; in an iTA clashes of values should not be approached by use of such ethics. Instead, casuistry, as a tool used within the framework of iTA, should help to articulate and clarify what is the matter, as to make room for explication and consensus building. (shrink)

Health technology assessment (HTA) is often biased in the sense that it neglects relevant perspectives on the technology in question. To incorporate different perspectives in HTA, we should pursue agreement about what are relevant, plausible, and feasible research questions; interactive technology assessment (iTA) might be suitable for this goal. In this way a kind of procedural ethics is established. Currently, ethics too often is focussed on the application of general principles, which leaves a lot of confusion as to what really (...) is the matter in specific cases; in an iTA clashes of values should not be approached by use of such ethics. Instead, casuistry, as a tool used within the framework of iTA, should help to articulate and clarify what is the matter, as to make room for explication and consensus building. (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)

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)

Extant research has shown that ordinary causal judgments are sensitive to normative factors. For instance, agents who violate a norm are standardly deemed more causal than norm-conforming agents in identical situations. In this paper, we explore two competing explanations for the Norm Effect: the Responsibility View and the Bias View. According to the former, the Norm Effect arises because ordinary causal judgment is intimately intertwined with moral responsibility. According to the alternative view, the Norm Effect is the result (...) of a blame-driven bias. In a series of five preregistered experiments (N = 2688), we present evidence that predominantly favours the Bias View. In particular, and against predictions made by the Responsibility View, we show that participants deem agents who violate nonpertinent or silly norms – norms that do not relate to the outcome at hand – as more causal, and that this effect cannot be explained in terms of plausible mediators such as the agent’s foreknowledge and desire, or the foreseeability of harm. We close with a discussion regarding the implications of these findings, in as regards the just assessment of proximate cause in the law. (shrink)

We argue that work on norms provides a way to move beyond debates between proponents of individualist and structuralist approaches to bias, oppression, and injustice. We briefly map out the geography of that debate before presenting Charlotte Witt’s view, showing how her position, and the normative ascriptivism at its heart, seamlessly connects individuals to the social reality they inhabit. We then describe recent empirical work on the psychology of norms and locate the notions of informal institutions and soft (...) structures with respect to it. Finally, we argue that the empirical resources enrich Witt’s ascriptivism, and that the resulting picture shows theorists need not, indeed should not, choose between either the individualist or structuralist camp. (shrink)

A regulative norm for permissible defense distinguishes the conditions under which we will hold defenders to be innocent of any wrongdoing from those in which we hold them responsible for assault or manslaughter. The norm must strike a fair balance between defenders' security, on the one hand, and other agents’ legitimate claim to live without fear of suffering mistaken defensive harm, on the other. Since agents must make defensive decisions under high pressure and on only partial information, they will sometimes (...) make mistakes. We have reason to want a norm that considers a mistake permissible when it was highly likely on the evidence that defense was proportionate and necessary to avert a threat. However, adopting an evidentialist norm under non-ideal conditions is treacherous business. I briefly survey empirical data suggesting that the type and extent of bias prevalent in the US renders a straightforward evidentialist norm unjust, and thus since the legal practice in the US relies on such a norm, we must explore avenues for reform. Preferably this will take the form of adopting a modified evidential norm, and I explore some promising options. If this proves impossible, however, then we have to accept a strict regulative norm (which does not consider any mistakes permissible), as the sole just alternative. (shrink)

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

Andrew Feenberg’s distinction between formal and substantive bias in the design of technology is interrogated. The two dimensions of his definition—inten­tion and the enhancement of specific social interests—are examined and eight logical possibilities arising from his argument are identified. These possibilities are explored through discussion of examples and it is argued that Feenberg has both: a) not broken sufficiently with substantivist philosophies of technology so that he retains ambivalence on technology’s ‘biased essence,’ and b) illegitimately rejected the idea of (...) a technology that is biased in itself. The latter category is important to critical theory of technology and the paper offers a conceptualization of it that draws on Habermas’s discourse ethics. (shrink)

The term 'implicit bias' has very swiftly been incorporated into philosophical discourse. Our aim in this paper is to scrutinise the phenomena that fall under the rubric of implicit bias. The term is often used in a rather broad sense, to capture a range of implicit social cognitions, and this is useful for some purposes. However, we here articulate some of the important differences between phenomena identified as instances of implicit bias. We caution against ignoring these differences: (...) it is likely they have considerable significance, not least for the sorts of normative recommendations being made concerning how to mitigate the bad effects of implicit bias. (shrink)

BackgroundThere is a growing concern about artificial intelligence (AI) applications in healthcare that can disadvantage already under-represented and marginalised groups (eg, based on gender or race).ObjectivesOur objectives are to canvas the range of strategies stakeholders endorse in attempting to mitigate algorithmic bias, and to consider the ethical question of responsibility for algorithmic bias.MethodologyThe study involves in-depth, semistructured interviews with healthcare workers, screening programme managers, consumer health representatives, regulators, data scientists and developers.ResultsFindings reveal considerable divergent views on three key (...) issues. First, views on whether bias is a problem in healthcare AI varied, with most participants agreeing bias is a problem (which we call the bias-critical view), a small number believing the opposite (the bias-denial view), and some arguing that the benefits of AI outweigh any harms or wrongs arising from the bias problem (the bias-apologist view). Second, there was a disagreement on the strategies to mitigate bias, and who is responsible for such strategies. Finally, there were divergent views on whether to include or exclude sociocultural identifiers (eg, race, ethnicity or gender-diverse identities) in the development of AI as a way to mitigate bias.Conclusion/significanceBased on the views of participants, we set out responses that stakeholders might pursue, including greater interdisciplinary collaboration, tailored stakeholder engagement activities, empirical studies to understand algorithmic bias and strategies to modify dominant approaches in AI development such as the use of participatory methods, and increased diversity and inclusion in research teams and research participant recruitment and selection. (shrink)

AI systems have often been found to contain gender biases. As a result of these gender biases, AI routinely fails to adequately recognize the needs, rights, and accomplishments of women. In this article, we use Axel Honneth’s theory of recognition to argue that AI’s gender biases are not only an ethical problem because they can lead to discrimination, but also because they resemble forms of misrecognition that can hurt women’s self-development and self-worth. Furthermore, we argue that Honneth’s theory of recognition (...) offers a fruitful framework for improving our understanding of the psychological and normative implications of gender bias in modern technologies. Moreover, our Honnethian analysis of gender bias in AI shows that the goal of responsible AI requires us to address these issues not only through technical interventions, but also through a change in how we grant and deny recognition to each other. (shrink)

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

I find much to like in Craig Callender's [2022] arguments for the rational permissibility of non-exponential time discounting when these arguments are viewed in a conditional form: viz., if one thinks that time discounting is rationally permissible, as the social scientist does, then one should think that non-exponential time discounting is too. However, time neutralists believe that time discounting is rationally impermissible, and thus they take zero time discounting to be the normative standard. The time neutralist rejects time discounting (...) because they think it is rationally impermissible to prefer to live a worse life in expectation because of arbitrariness. Callender’s attack on the time-neutralist position is the following: the time-neutralist’s non-arbitrariness intuition assumes the existence of nonexistent ‘pure’ time preferences. In response, I aim to clarify the time-neutralist position and show that the non-arbitrariness argument does not rely on the existence of pure time preferences. Instead, the debate between time neutralism and permissivism about time discounting boils down to a methodological question: can we ever criticize the content of preferences? If so, we should embrace time neutralism. (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)

This article sets out to describe and solve two puzzles that emerge in segregated labour markets (e.g. the USA or Sweden). First, in many hiring contexts people profess to adhere to egalitarian norms, and specifically to a qualification norm according to which job qualification should be the basis of employment. Still there is evidence of frequent norm violations (discrimination). Surprisingly, the norm persists and people do not frequently protest against such norm violations. The second puzzle is that people are suspicious (...) of the hiring of minorities, perceiving such hirings as evidence that a ‘political correctness’ norm has replaced the qualification norm. The article proposes that both puzzles can be solved within a game-theoretical model of social norm-following, where implicit bias is introduced into an ‘employment game’. Within this model, implicit bias plays a double role. First, it interferes with employers' hiring decisions regarding ethnic majority and minority members, respectively. This is the standard way of understanding the effects of implicit bias. Second, implicit bias interferes with bystander evaluations of hired candidates' qualifications. This is a hitherto overlooked effect of implicit bias. The article concludes that once we understand the double role of implicit bias, the two puzzles are resolved. (shrink)

This book is a philosophical exploration of bias and our practices of attributing it. It develops and defends the norm-theoretic account of bias, according to which objectionable biases involve systematic departures from objective norms or standards of correctness. It explores the perspectival character of bias attributions, or the ways in which our views about which people and sources of information are biased about a topic are influenced and constrained, both rationally and psychologically, by our views about the (...) topic itself. The book defends a robust pluralism about bias, according to which a radical diversity of things are genuinely biased, with none of these more fundamental than all of the rest. Biases of people are understood as multiply realizable dispositions to depart from objective norms. It offers a novel account of the bias blind spot, or our tendency to fail to see bias in ourselves in a way that we see it in others. It explores the connections between bias and central topics in the theory of knowledge, including truth, knowledge, rationality, reliability, introspection, skepticism, and disagreement. A number of racial conclusions are defended: that both rationality and morality sometimes require us to be biased; that in many cases of disagreement, we are rationally required to view those who disagree with us as biased, even if we know nothing about how they arrived at their views or why they hold them; and that even God could not have made us reliable detectors of our own biases through introspection. (shrink)

Why does social injustice exist? What role, if any, do implicit biases play in the perpetuation of social inequalities? Individualistic approaches to these questions explain social injustice as the result of individuals’ preferences, beliefs, and choices. For example, they explain racial injustice as the result of individuals acting on racial stereotypes and prejudices. In contrast, structural approaches explain social injustice in terms of beyond-the-individual features, including laws, institutions, city layouts, and social norms. Often these two approaches are seen as competitors. (...) Framing them as competitors suggests that only one approach can win and that the loser offers worse explanations of injustice. In this essay, we explore each approach and compare them. Using implicit bias as an example, we argue that the relationship between individualistic and structural approaches is more complicated than it may first seem. Moreover, we contend that each approach has its place in analyses of injustice and raise the possibility that they can work together—synergistically—to produce deeper explanations of social injustice. If so, the approaches may be complementary, rather than competing. (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)

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)

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)

Future-bias is the preference, all else being equal, for positive states of affairs to be located in the future not the past, and for negative states of affairs to be located in the past not the future. Three explanations for future-bias have been posited: the temporal metaphysics explanation, the practical irrelevance explanation, and the three mechanisms explanation. Understanding what explains future-bias is important not only for better understanding the phenomenon itself, but also because many philosophers think that (...) which explanation is the correct one has implications for our evaluation of the normative status of future-bias. In this paper we focus on the connection between future-bias and the temporal value asymmetry. The latter refers to the fact that people tend to assign more value to a state of affairs when it is located in the future, as opposed to being equidistant in the past. All three candidate explanations offered for future-bias proceed by explaining the temporal value asymmetry, and then supposing that future-bias is simply a manifestation of that asymmetry. Recently, however, it has been argued that the conditions under which people display the temporal value asymmetry and future-bias are different, and that this is reason to doubt that the latter is a manifestation of the former. In this paper we empirically test one response to this argument against the manifestation thesis—the simulation response—according to which once we control for the degree to which people can simulate the object of their preference, we find that people display future-bias and the temporal value asymmetry in the same conditions. We find no evidence in favour of the simulation response. Moreover, our results support some previous research that suggests that the temporal value asymmetry is less robust than previously thought, and this in itself casts doubt on the idea that future bias is just a manifestation of this asymmetry. (shrink)

In this introduction, we acquaint readers with a selection of work coming out of the "Bias in Context" conference series, which ran from 2016 to 2017. Featured authors in the symposium include Gabriella Beckles-Raymond (writing about bad faith and implicit bias explanations), Daniel Kelly and Lacey Davidson (writing about gender norms and the internalization of social structures), and Alex Madva (writing about solutions to racial integration and an empirical mindset). We sketch the larger themes of the conference, as (...) well as how these three pieces of work fit into them. (shrink)

Mundane and often subtle forms of bias generate harms that can be fruitfully understood as akin to the harms evident in rudeness. Although subclinical expressions of bias are not mere rudeness, like rudeness they often manifest through the breach of mannerly norms for social cooperation and collaboration. At a basic level, the perceived harm of mundane forms of bias often has much to do with feeling oneself unjustly or arbitrarily cut out of a group, a group that (...) cooperates and collaborates but does not do so with me. Appealing to the subtle but familiar choreography of mannered social interaction, I argue, makes it easier to recognize how exclusion can be accomplished through slight but symbolically significant gestures and styles of interaction, where bias manifests not in announced hostility but in an absence of the cooperation and collaboration upon which we rely socially. (shrink)

A growing body of research has examined how people judge the persistence of identity over time—that is, how they decide that a particular individual is the same entity from one time to the next. While a great deal of progress has been made in understanding the types of features that people typically consider when making such judgments, to date, existing work has not explored how these judgments may be shaped by normative considerations. The present studies demonstrate that normative (...) beliefs do appear to play an important role in people's beliefs about persistence. Specifically, people are more likely to judge that the identity of a given entity remains the same when its features improve than when its features deteriorate. Study 1 provides a basic demonstration of this effect. Study 2 shows that this effect is moderated by individual differences in normative beliefs. Study 3 examines the underlying mechanism, which is the belief that, in general, various entities are essentially good. Study 4 directly manipulates beliefs about essence to show that the positivity bias regarding essences is causally responsible for the effect. (shrink)

Of the many far-reaching implications of Fincher & Thornhill's (F&T's) theory, we focus on the consequences of parasite stress for mating strategies, marriage, and the differing roles and restrictions for men and women. In particular, we explain how examination of cultures of honor can provide a theoretical bridge between effects of parasite stress and disproportionate emphasis on female purity.

Over recent decades International Relations scholars have investigated norm dynamics processes at some length, with the norm entrepreneur concept having become a common reference point in the literature. The focus on norm entrepreneurs has, however, resulted in a bias towards investigating the agents and processes of successful normative change. This book challenges this inherent bias by explicitly focusing on those who resist normative change - norm antipreneurs. The utility of the norm antipreneur concept is explored through (...) a series of case studies encompassing a range of issue areas and contributed by a mix of well-known and emergent scholars of norm dynamics. In examining the complexity of norm resistance, particular attention is paid to the nature and intent of the actors involved in norm-contestation, the sites and processes of resistance, the strategies and tactics antipreneurs deploy to defend the values and interests they perceive to be threatened by the entrepreneurs, and whether it is the entrepreneurs or the antipreneurs who enjoy greater inherent advantages. This text will therefore be of interest to scholars and students of International Relations, International Law, Political Science, Sociology and History. ". (shrink)

In this chapter, we explore whether agents have an epistemic duty to eradicate implicit bias. Recent research shows that implicit biases are widespread and they have a wide variety of epistemic effects on our doxastic attitudes. First, we offer some examples and features of implicit biases. Second, we clarify what it means to have an epistemic duty, and discuss the kind of epistemic duties we might have regarding implicit bias. Third, we argue that we have an epistemic duty (...) to eradicate implicit biases that have negative epistemic impact. Finally, we defend this view against the objection that we lack the relevant control over implicit bias that’s required for such a duty. We argue that we have a kind of reflective control over the implicit biases that we are duty-bound to eradicate. And since, as we show, we have this control over a wide variety of implicit biases, there are a lot of implicit biases that we have epistemic duties to eradicate. (shrink)

This paper investigates the connection between temporal attitudes (attitudes characterised by a concern (or lack thereof) about future and past events), beliefs about temporal ontology (beliefs about the existence of future and past events) and temporal preferences (preferences regarding where in time events are located). Our aim is to probe the connection between these preferences, attitudes, and beliefs, in order to better evaluate the normative status of these preferences. We investigate the hypothesis that there is a three-way association between (...) (a) being present-biased (that is, preferring that positive events are located in the present, and negative events are located in the non-present), (b) believing that past and future events do not exist and (c) tending to have present-focused rather than non-present-focused temporal attitudes. We find no such association. This suggests that insofar as temporal preferences and temporal attitudes are connected to the ways we represent time, they are not connected to the ways we represent temporal ontology; rather, they are more likely connected to the ways we represent relative movement in, or of, time. This has important consequences for, first, explaining why we exhibit these preferences and, second, for their normative evaluation. (shrink)

In this paper, we consider three competing explanations of the empirical finding that people’s causal attributions are responsive to normative details, such as whether an agent’s action violated an injunctive norm—the intervention view, the bias view, and the responsibility view. We then present new experimental evidence concerning a type of case not previously investigated in the literature. In the switch version of the trolley problem, people judge that the bystander ought to flip the switch, but they also judge (...) that she is more responsible for the resulting outcome when she does so than when she refrains. And, as predicted by the responsibility view, but not the intervention or bias views, people are more likely to say that the bystander caused the outcome when she flips the switch. (shrink)

A challenge we face in a world that has been shaped by, and continues to be shaped by, racist attitudes and institutions is that the evidence is often stacked in favor of racist beliefs. As a result, we may find ourselves facing the following conflict: what if the evidence we have supports something we morally shouldn’t believe? For example, it is morally wrong to assume, solely on the basis of someone’s skin color, that they’re a staff member. But, what if (...) you’re in a context where, because of historical patterns of discrimination, someone’s skin color is a very good indicator that they’re a staff member? When this sort of normative conflict looms, a conflict between moral considerations on the one hand and what you epistemically ought to believe given the evidence on the other, what should we do? It might be unfair to assume that they’re a staff member, but to ignore the evidence would mean risking inaccurate beliefs. Some, notably Tamar Gendler (2011), have suggested that we simply face a tragic irresolvable dilemma. In this chapter, I consider how these cases of conflict arise and I canvass the viability of suggested resolutions of the conflict. In the end, I argue that there’s actually no conflict here. Moral considerations can change how we epistemically should respond to the evidence. (shrink)

I argue that evidentialism should be rejected because it cannot be reconciled with empirical work on bias in cognitive and social psychology.

Some artificial intelligence systems can display algorithmic bias, i.e. they may produce outputs that unfairly discriminate against people based on their social identity. Much research on this topic focuses on algorithmic bias that disadvantages people based on their gender or racial identity. The related ethical problems are significant and well known. Algorithmic bias against other aspects of people’s social identity, for instance, their political orientation, remains largely unexplored. This paper argues that algorithmic bias against people’s political (...) orientation can arise in some of the same ways in which algorithmic gender and racial biases emerge. However, it differs importantly from them because there are strong social norms against gender and racial biases. This does not hold to the same extent for political biases. Political biases can thus more powerfully influence people, which increases the chances that these biases become embedded in algorithms and makes algorithmic political biases harder to detect and eradicate than gender and racial biases even though they all can produce similar harm. Since some algorithms can now also easily identify people’s political orientations against their will, these problems are exacerbated. Algorithmic political bias thus raises substantial and distinctive risks that the AI community should be aware of and examine. (shrink)

Liberals often view religion chiefly as "a problem" for democratic discourse in modern pluralistic societies and propose an allegedly neutral solution in the form of philosophical distinctions between "the right" and "the good" or populist invocations of a "right to choose." Drawing on cultural theory and ethnographic research among activists in the Oregon debates over the legalization of physician-assisted suicide, I demonstrate that liberal "neutrality" harbors its own cultural bias, flattens the complexity of public debates, and undermines liberalism's own (...) commitments to equality. I conclude that the praiseworthy liberal goal of impartiality in policy decisions would best be met not by the inaccessible norm of neutrality but by a norm of inclusivity, which intentionally solicits multiple cultural perspectives. (shrink)

Feminist philosophers are often concerned with rejecting Cartesian notions of objectivity which eliminate all subjectivity on the part of knowers. However, this rejection of a notion of pure (non-subjective) neutrality has led the dilemma that Louise Antony calls the “bias paradox” (Antony 1993, 188-90). At the heart of this paradox lies the seeming choice between objectivism and relativism. It has two fundamental commitments that clearly focus this dilemma: (1) the explicit rejection of the concept of impartial objectivity and (2) (...) the desire to assert the reality of women’s oppression. The problem is that in the absence of impartiality (at least as an ideal), there appears to be a lack of principled, normative criteria for evaluating beliefs across differing epistemic perspectives. While this tension is dealt with most straightforwardly in discussions of naturalized feminist epistemology and feminist philosophy of science, the bias paradox, nonetheless, is not merely a problem for feminists. Any view that rejects the Cartesian ideals of pure objectivity and value-neutrality will ultimately be forced to confront the dilemma that seemingly results from the paradox; namely, to either endorse pure impartiality or accept an “anything goes” relativism. (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)

Our understanding of implicit bias and how to measure it has yet to be settled. Various debates between cognitive scientists are unresolved. Moreover, the public’s understanding of implicit bias tests continues to lag behind cognitive scientists’. These discrepancies pose potential problems. After all, a great deal of implicit bias research has been publicly funded. Further, implicit bias tests continue to feature in discourse about public- and private-sector policies surrounding discrimination, inequality, and even the purpose of science. (...) We aim to do our part by reconstructing some of the recent arguments in ordinary language and then revealing some of the operative norms or values that are often hidden beneath the surface of these arguments. This may help the public learn more about the science of implicit bias. It may also help both laypeople and scientists reflect on the values, interests, and stakeholders involved in establishing, justifying, and communicating scientific research. (shrink)

Peer reviews of 84 organic farming grant applications from Sweden were analyzed to determine whether the reviewers’ affiliation to one of two types of agriculture (i.e., organic and conventional) influenced their reviews. Fifteen reviewers were divided into three groups: (1) scientists with experience in organic farming research; (2) scientists with no experience in organic farming research; and (3) users of organic farming research. The two groups of scientists assessed the societal relevance and scientific quality of the grant applications based on (...) three criteria (i.e., presentation, methodology, qualifications), whereas the user group only assessed societal relevance. The analysis showed that the two groups of scientists provided very different reviews. Scientist reviewers with experience in organic farming research agreed more with the user group on research relevance than did scientist reviewers without such experience, and the assessment of relevance was closely correlated to the assessment of scientific quality within both scientific groups. As both scientific groups did not clearly distinguish between societal relevance and scientific quality, the idea of an objective science is challenged. The contextual values associated with the norms of good agriculture were not clearly distinguished from the constitutive values of science associated with the traditional norms of good science. This raises the question of whether organic and conventional grant applications should be mixed for review regardless of the reviewers. (shrink)

In this paper I argue that some examples of what we label ‘algorithmic bias’ would be better understood as cases of institutional bias. Even when individual algorithms appear unobjectionable, they may produce biased outcomes given the way that they are embedded in the background structure of our social world. Therefore, the problematic outcomes associated with the use of algorithmic systems cannot be understood or accounted for without a kind of structural account. Understanding algorithmic bias as institutional (...) class='Hi'>bias in particular (as opposed to other structural accounts) has at least two important upshots. First, I argue that the existence of bias that is intrinsic to certain institutions (whether algorithmic or not) suggests that at least in some cases, the algorithms now substituting as pieces of institutional norms or rules are not “fixable” in the relevant sense, because the institutions they help make up are not fixable. Second, I argue that in other cases, changing the algorithms being used within our institutions (rather than getting rid of them entirely) is essential to changing the background structural conditions of our society. (shrink)

Philosophers working on time-biases assume that people are hedonically biased toward the future. A hedonically future-biased agent prefers pleasurable experiences to be future instead of past, and painful experiences to be past instead of future. Philosophers further predict that this bias is strong enough to apply to unequal payoffs: people often prefer less pleasurable future experiences to more pleasurable past ones, and more painful past experiences to less painful future ones. In addition, philosophers have predicted that future-bias is (...) restricted to first-person preferences, and that people’s third-person preferences are time-neutral. Philosophers disagree vigorously about the normative status of these preferences—i.e., they disagree about whether first-person future-bias is rationally permissible. Time-neutralists, for example, have appealed to the predicted asymmetry between first- and third-person preferences to argue for the rational impermissibility of future-bias. We empirically tested these predictions, and found that while people do prefer more past pain to less future pain, they do not prefer less future pleasure to more past pleasure. This was so in both first and third-person conditions. This suggests that future-bias is typically non-absolute, and is more easily outweighed in the case of positive events. We connect this result to the normative debate over future-bias. (shrink)

In many spheres, the law takes the legal concept of causation to correspond to the folk concept (the correspondence assumption). Courts, including the US Supreme Court, tend to insist on the "common understanding" and that which is "natural to say" (Burrage v. United States) when it comes to expressions relating to causation, and frequently refuse to clarify the expression to juries. As recent work in psychology and experimental philosophy has uncovered, lay attributions of causation are susceptible to a great number (...) of unexpected factors, some of which seem rather peripheral to causation. One of those is the norm effect (Knobe & Fraser, 2008): Agents who, in acting as they do, break a salient norm, are more likely to be considered as having caused a certain consequence than when they do not violate a norm. According to some (e.g., Alicke, 1992) this constitutes a bias. According to others (e.g., Sytsma, 2020), the folk concept of causation is sensitive to normative factors, and there’s nothing wrong with that. In this paper, we explore the question whether the norm effect should be considered a bias from the legal perspective on the one hand, and from the psychological perspective on the other. To do this, we test whether norms which are nonpertinent to the consequences or outright silly also impact causation judgements. The data from two preregistered experiments (total N=593) clearly show they do. This, we argue, makes the bias interpretation plausible from the psychological perspective, and both plausible and problematic from the legal perspective. It also shows that the law should abstain from unreflectively assuming conceptual correspondence between legal and ordinary language concepts. (shrink)

The spatial composition of human portraits obeys historically changing cultural norms. We show that it is also affected by cognitive factors that cause greater spontaneous attention to what is in front rather in the back of an agent. Scenes with more space in front of a directed object are both more often produced and judged as more aesthetically pleasant. This leads to the prediction that, in profile‐oriented human portraits, compositions with more space in front of depicted agents (a “forward (...) class='Hi'>bias”) should be over‐represented. By analyzing a large dataset (total N of 1,831 paintings by 582 unique identified European painters from the 15th to the 20th century), we found evidence of this forward bias: Painters tended to put more free space in front of, rather than behind, the sitters. Additionally, we found evidence that this forward bias became stronger when cultural norms of spatial composition favoring centering became less stringent. (shrink)

While rapid advances in artificial intelligence hiring tools promise to transform the workplace, these algorithms risk exacerbating existing biases against marginalized groups. In light of these ethical issues, AI vendors have sought to translate normative concepts such as fairness into measurable, mathematical criteria that can be optimized for. However, questions of disability and access often are omitted from these ongoing discussions about algorithmic bias. In this paper, I argue that the multiplicity of different kinds and intensities of people’s (...) disabilities and the fluid, contextual ways in which they manifest point to the limits of algorithmic fairness initiatives. In particular, existing de-biasing measures tend to flatten variance within and among disabled people and abstract away information in ways that reinforce pathologization. While fair machine learning methods can help mitigate certain disparities, I argue that fairness alone is insufficient to secure accessible, inclusive AI. I then outline a disability justice approach, which provides a framework for centering disabled people’s experiences and attending to the structures and norms that underpin algorithmic bias. (shrink)

The vegan ideal is entailed by arguments for ethical veganism based on traditional moral theory (rights and/or utilitarianism) extended to animals. The most ideal lifestyle would abjure the use of animals or their products for food since animals suffer and have rights not to be killed. The ideal is discriminatory because the arguments presuppose a male physiological norm that gives a privileged position to adult, middle-class males living in industrialized countries. Women, children, the aged, and others have substantially different nutritional (...) requirements and would bear a greater burden on vegetarian and vegan diets with respect to health and economic risks, than do these males. The poor and many persons in Third World nations live in circumstances that make the obligatory adoption of such diets, where they are not already a matter of sheer necessity, even more risky.Traditional moral theorists (such as Evelyn Pluhar and Gary Varner whose essays appear in this issue) argue that those who are at risk would beexcused from a duty to attain the virtue associated with ethical vegan lifestyles. The routine excuse of nearly everyone in the world besides adult, middle-class males in industrialized countries suggests bias in the perspective from which traditional arguments for animal rights and (utilitarian) animal welfare are formulated. (shrink)

Exponential discounted utility theory provides the normative standard for future discounting as it is employed throughout the social sciences. Tracing the justification for this standard through economics, philosophy and psychology, I’ll make what I believe is the best case one can for it, showing how a non-arbitrariness assumption and a dominance argument together imply that discounting ought to be exponential. Ultimately, however, I don’t find the case compelling, as I believe it is deeply flawed. Non-exponential temporal discounting is often (...) rational–indeed, the paragon of rationality. If this is correct, it’s an important point when considering policy interventions. Instead of trying to “fix” non-exponetial discounting because it is irrational and associated with negative life outcomes, we might instead focus attention on why the conditions obtain that make such discounting rational. (shrink)

The ratio bias––according to which individuals prefer to bet on probabilities expressed as a ratio of large numbers to normatively equivalent or superior probabilities expressed as a ratio of small numbers––has recently gained momentum, with researchers especially in health economics emphasizing the policy importance of the phenomenon. Although the bias has been replicated several times, some doubts remain about its economic significance. Our two experiments show that the bias disappears once order effects are excluded, and once salient (...) and dominant incentives are provided. This holds true for both choice and valuation tasks. Also, adding context to the decision problem does not change this outcome. No ratio bias could be found in between-subject tests either, which leads us to the conclusion that the policy relevance of the phenomenon is doubtful at best. (shrink)

Epistemologists have recently proposed a number of norms governing rational inquiry. My aim in this paper is to unify and explain recently proposed norms of inquiry by developing a general account of the conditions under which inquiries are rational, analogous to theories such as evidentialism and reliabilism for rational belief. I begin with a reason-responsiveness conception of rationality as responding correctly to possessed normative reasons. I extend this account with a series of claims about the normative reasons for (...) inquiry that we possess. I apply the account to shed light on two classes of norms that have featured prominently in recent discussions: norms of clutter avoidance forbidding agents from engaging in trivial inquiries, and norms of logical non-omniscience governing properties such as the deductive closure and consistency of an agent's belief state. I conclude with a discussion of the sense in which norms of inquiry should be regarded as epistemic norms. (shrink)