We often show a greater inclination to assist and avoid harming people identified as those at high risk of great harm than to assist and avoid harming people who will suffer similar harm but are not identified (as yet). Call this the identified person bias. Some ethicists think such bias is justified; others disagree and claim that the bias is discriminatory against statistical people. While the issue is present in public policy and politics, perhaps the most notable examples can be (...) found in medical ethics such as in ICU triage decisions made during the COVID‐19 pandemic. The Rule of Rescue, as the application of the identified person bias is sometimes called, states that spending large amounts of resources rescuing identifiable individuals who are in imminent danger is justified. In this paper, I show that our distorted attitudes toward time play a role in identified person bias. I claim that ICU triage decisions are better explained by a preference to treat people sooner rather than later, which is at least partially due to near bias (positive events are to be preferred to be near rather than distant), than by a preference to treat identified lives over statistical lives. Thus, another bias, near bias, is involved in the reasoning behind the identified person bias and the Rule of Rescue. (shrink)

In this article, I cast doubt on an apparent truism, namely, that if evidence is available for gathering and use at a negligible cost, then it’s always instrumentally rational for us to gather that evidence and use it for making decisions. Call this ‘value of information’ (VOI). I show that VOI conflicts with two other plausible theses. The first is the view that an agent’s evidence can entail non-trivial propositions about the external world. The second is the view that epistemic (...) rationality requires us to update our credences by conditionalization. These two theses, given some plausible assumptions, make room for rationally biased inquiries where VOI fails. I go on to argue that this is bad news for defenders of VOI. (shrink)

Shared decision-making involves health professionals and patients/clients working together to achieve true person-centred health care. However, this goal is infrequently realized, and most barriers are unknown. Discussion between philosophers, clinicians, and researchers can assist in confronting the epistemic and moral basis of health care, with benefits to all. The aim of this paper is to describe what shared decision-making is, discuss its necessary conditions, and develop a definition that can be used in practice to support excellence in maternity (...) care. Discussion between the authors, with backgrounds in philosophy, clinical maternity care, health care management, and maternity care research, assisted the team to confront established norms in maternity care and challenge the epistemic and moral basis of decision-making for caesarean section. The team concluded that shared decision-making must start in pregnancy and continue throughout labour and birth, with equality in discourse facilitated by the clinician. Clinicians have a duty of care for the adequacy of women's knowledge, which can only be fulfilled when relevant knowledge is offered freely and when personal beliefs and biases that may impinge on decision-making (defeaters) are disclosed. Informed consent is not shared decision-making. Key barriers include existing cultural norms of “the doctor knows best” and “patient acquiescence” that prevent defeaters being acknowledged and discussed and can lead to legal challenges, overuse of medical intervention and, in some areas, obstetric violence. Shared decision-making in maternity care can thus be defined as an enquiry by clinician and expectant woman aimed at deciding upon a course of care or none, which takes the form of a dialogue within which the clinician fulfils their duty of care to the client's knowledge by making available their complete knowledge (based on all types of evidence) and expertise, including an exposition of any relevant and recognized potential defeaters. Research to develop measurement tools is required. (shrink)

This text provides an introduction to the topic of rational decision making as well as a brief overview of the most common biases in judgment and decision making. "Decision Making" is relatively short (300 pages) and richly illustrated with approximately 100 figures. It is suitable for both self-study and as the basis for an upper-division undergraduate course in judgment and decision making. The book is written to be accessible to anybody with minimum knowledge of mathematics (...) (high-school level algebra and some elementary notions of set theory and probability, which are reviewed in the book). At the end of each chapter there is a collection of exercises that are grouped according to that chapter’s sections. Complete and detailed answers for each exercise are given in the last section of each chapter. The book contains a total of 121 fully solved exercises. (shrink)

In this paper we discuss how Causal Decision Theory should be modified to handle a class of problematic cases involving deterministic laws. Causal Decision Theory, as it stands, is problematically biased against your endorsing deterministic propositions (for example it tells you to deny Newtonian physics, regardless of how confident you are of its truth). Our response is that this is not a problem for Causal Decision Theory per se, but arises because of the standard method for assessing (...) the truth of certain counterfactuals. The truth of deterministic laws is `modally fragile' on the standard semantics for counterfactuals: if determinism is true and you were to do otherwise, the laws would be different. We provide two ways of avoiding this problem: 1) supplement the standard semantics for counterfactuals with impossible worlds, or 2) introduce rigid designators into the description of problematic decision situations. We argue that both of these approaches are well-motivated and can be readily incorporated into Lewisian Causal Decision Theory. (shrink)

The use of AI algorithms in criminal trials has been the subject of very lively ethical and legal debates recently. While there are concerns over the lack of accuracy and the harmful biases that certain algorithms display, new algorithms seem more promising and might lead to more accurate legal decisions. Algorithms seem especially relevant for bail decisions, because such decisions involve statistical data to which human reasoners struggle to give adequate weight. While getting the right legal outcome is a (...) strong desideratum of criminal trials, advocates of the relational theory of procedural justice give us good reason to think that fairness and perceived fairness of legal procedures have a value that is independent from the outcome. According to this literature, one key aspect of fairness is trustworthiness. In this paper, I argue that using certain algorithms to assist bail decisions could increase three diferent aspects of judges’ trustworthiness: (1) actual trustworthiness, (2) rich trustworthiness, and (3) perceived trustworthiness. (shrink)

Collaborative filtering is being used within organizations and in community contexts for knowledge management and decision support as well as the facilitation of interactions among individuals. This article analyzes rhetorical and technical efforts to establish trust in the constructions of individual opinions, reputations, and tastes provided by these systems. These initiatives have some important parallels with early efforts to support quantitative opinion polling and construct the notion of “public opinion.” The article explores specific ways to increase trust in these (...) systems, albeit a “guarded trust” in which individuals actively seek information about system foibles and analyze the reputations of participants. (shrink)

The ecologist today finds scarce ground safe from controversy. Decisions must be made about what combination of data, goals, methods, and theories offers them the foundations and tools they need to construct and defend their research. When push comes to shove, ecologists often turn to philosophy to justify why it is their approach that is scientific. Karl Popper’s image of science as bold conjectures and heroic refutations is routinely enlisted to justify testing hypotheses over merely confirming them. One of the (...) most controversial theories in contemporary science is the Neutral Theory of Ecology. Its chief developer and proponent, Stephen Hubbell, presents the neutral theory as a bold conjecture that has so far escaped refutation. Critics of the neutral theory claim that it already stands refuted, despite what the dogmatic neutralists say. We see the controversy through a Popperian lens. But Popper’s is an impoverished philosophy of science that distorts contemporary ecology. -/- The controversy surrounding the neutral theory actually rests on a methodological fault. There is a strong but messy historical link between the concepts of being neutral and being null in biology, and Hubbell perpetuates this when he claims that the neutral theory is supplies the appropriate null for testing alternative theories. What method is being followed here? There are three contenders: -/- Null hypothesis testing tests for whether a there is a pattern to be explained. Null modeling tests for whether a process is causally relevant to a pattern. Baseline modeling apportions relative responsibility to multiple processes each relevant to a pattern. -/- Whether the neutral theory supplies an appropriate “null” depends upon whether null hypothesis, null modeling, or baseline model is intended. These methods prescribe distinct inference patterns. If they are null hypothesis testing or null modeling, the neutralists’s reasoning is invalid. If they are baseline modeling, the justification of a crucial assumption remains opaque. Either way, the neutral-null connection is being exploited rhetorically to privilege the neutral theory over its rivals. Clarifying the reasoning immunizes us against the rhetoric and foregrounds the underlying virtues of the neutralist approach to ecology. -/- The Popperian lens distorts theoretical development as dogmatism. Lakatos’s view of science as the development of research programmes clarifies the epistemology of the neutral theory. Focusing philosophical attention on the neutralist research programme illuminates (1) the synchronic uses of the neutral theory to make predictions and give descriptions and explanations; (2) its diachronic development in response to theoretical innovation and confrontation with data; (3) its complex relationships to alternative theories. For example, baseline modeling is now seen to be its primary explanatory heuristic. The justification for baseline modeling with the neutral theory, previously hidden from view, is seen in the logic of in the neutralist research programme. (shrink)

This is a very short textbook on probabilistic reasoning, expected utility decision-making, cognitive biases, and self-correction, especially in application to medical examples. It also includes a chapter on concepts of health.

Qualitative evidence concerning the relationship between QoL and a wide range of disabilities suggests that subjective judgments regarding other people’s QoL are wrong more often than not and that such judgments by medical practitioners in particular can be biased. Guided by their desire to do good and avoid harm, surgeons often rely on "the eyeball test" to decide whether a patient will or will not benefit from surgery. But the eyeball test can easily harbor a range of implicit judgments and (...) biases against patients with disabilities, including erroneous assumptions about QoL. We critique the use of the "eyeball" test and offer suggestions to reduce bias and ensure that patients’ values are more consistently prioritized in surgical decision-making. (shrink)

Social dimension of moral responsibility has started to gain more attention in moral philosophy, be it within the network of action theory, or any other meta-ethical domain. Although there are many social acts and therefore social dimensions of responsibility, I aim to indicate one aspect of sociality in our thinking and practice, particularly in our moral thinking, that is the thick concepts. In this work, I consider Vargas’s concept moral ecology (2015, 2018) as a tool to understand certain social aspects (...) of moral responsibility, while claiming to extend his line of thinking in moral ecology by giving a more active role to the individual agent within the ecology that she is engaged in. I claim that when we understand the relationships between the agent and her surrounding ecology in a more complex, and under certain circumstances in a rather reciprocal way, we can have a better and more nuanced understanding of non-ideal moral landscapes that we are engaged in, while maintaining a certain kind of responsibility to the agents in their social environments. I will use the term niche construction and niche selection – concept that are already at use within the similar biological line of thought within action – to refer to such situations where agents are actively shaping their environments. (shrink)

Nudge is a concept of policy intervention that originates in Thaler and Sunstein's (2008) popular eponymous book. Following their own hints, we distinguish three properties of nudge interventions: they redirect individual choices by only slightly altering choice conditions (here nudge 1), they use rationality failures instrumentally (here nudge 2), and they alleviate the unfavourable effects of these failures (here nudge 3). We explore each property in semantic detail and show that no entailment relation holds between them. This calls into question (...) the theoretical unity of nudge, as intended by Thaler and Sunstein and most followers. We eventually recommend pursuing each property separately, both in policy research and at the foundational level. We particularly emphasize the need of reconsidering the respective roles of decision theory and behavioural economics to delineate nudge 2 correctly. The paper differs from most of the literature in focusing on the definitional rather than the normative problems of nudge. (shrink)

Criminal juries make decisions of great importance. A key criticism of juries is that they are unreliable in a multitude of ways, from exhibiting racial or gendered biases, to misunderstanding their role, to engaging in impropriety such as internet research. Recently, some have even claimed that the use of juries creates injustice on a large-scale, as a cause of low conviction rates for sexual criminality. Unfortunately, empirical research into jury deliberation is undermined by the fact that researchers are unable (...) to study live juries. The indirect sources of evidence used by researchers suffer from various problems, the most important of which is dubious levels of ecological validity. Real jury research—studying live jury deliberation—is controversial. However, as I argue, the objections to it are unconvincing. There is in fact a moral imperative to facilitate real jury research. (shrink)

What factors affect judicial decision-making? The legal system is of utmost importance because of its impact on our lives. Judges appear to have the most power among any social workers seeing as the precedents set in their decisions are tantamount to written law. Nevertheless, judges may be subject to certain biases, moral and cognitive alike, which influence their rulings. Looking into how morality and cognitive biases affect judges may also reveal how we as individuals handle combining morals (...) with ethics- as well as whether any discrepancies among ourselves are justifiable. An investigation into relevant moral and jurisprudential theories revealed much about the inner workings of a judge’s mindset- whether he or she recognizes it or not. Coupling this with corroborated research on a select few heuristics present specifically for judges sets the foundation for an array of possible solutions in order to ensure the most impartial judicial proceedings. Plausible remedies include conducting premortems, implicit association tests, and a revised ruling procedure. (shrink)

Decisions in medical contexts have immediate and obvious consequences in terms of health and sometimes death or survival. Medical decisions also have less obvious and less immediate consequences, including effects on the long-term physical and mental well-being of patients, their families and of care-givers, as well as on the distribution of scarce medical resources. Some of these consequences are hard to measure and estimate. Even harder, perhaps, is the determination of the relative value of different consequences. How should consequences be (...) evaluated? How do uncertainties and biases affect our evaluations of consequences? What influence should our evaluations of consequences have on our actions? These questions are all philosophical in nature. (shrink)

Scientists have complained about the inconsistency and politics of academic publishing for hundreds of years. Among the explanations offered are that evaluators lack time and use shortcuts, that they lack the expertise to judge things properly, that they can't put aside personal biases and we must hide the names of authors, and that they are conscientious instead of creative and cannot judge new ideas. All of these are actually wrong. As a literary analyst, I spent the last ten years (...) independently studying this same problem in book and movie production. I've found that the human decision-making apparatus doesn't work the way we think, and the solutions based on this misunderstanding could never have solved the problem. In this paper, we present the first method that actually can, which is a technique adapted from computer hacking, as well as a new view of how our brains make choices. (shrink)

Background: Current practice frequently fails to provide care consistent with the preferences of decisionally-incapacitated patients. It also imposes significant emotional burden on their surrogates. Algorithmic-based patient preference predictors (PPPs) have been proposed as a possible way to address these two concerns. While previous research found that patients strongly support the use of PPPs, the views of surrogates are unknown. The present study thus assessed the views of experienced surrogates regarding the possible use of PPPs as a means to help make (...) treatment decisions for decisionally-incapacitated patients. -/- Methods: This qualitative study used semi-structured interviews to determine the views of experienced surrogates [n=26] who were identified from two academic medical centers and two community hospitals. The primary outcomes were respondents’ overall level of support for the idea of using PPPs and the themes related to their views on how a PPP should be used, if at all, in practice. -/- Results: Overall, 21 participants supported the idea of using PPPs. The remaining five indicated that they would not use a PPP because they made decisions based on the patient’s best interests, not based on substituted judgment. Major themes which emerged were that surrogates, not the patient’s preferences, should determine how treatment decisions are made, and concern that PPPs might be used to deny expensive care or be biased against minority groups. -/- Conclusions: Surrogates, like patients, strongly support the idea of using PPPs to help make treatment decisions for decisionally-incapacitated patients. These findings provide support for developing a PPP and assessing it in practice. At the same time, patients and surrogates disagree over whose preferences should determine how treatment decisions are made, including whether to use a PPP. These findings reveal a fundamental disagreement regarding the guiding principles for surrogate decision-making. Future research is needed to assess this disagreement and consider ways to address it. (shrink)

This article proposes a rigorous method to “map” the law on to the facts in the legal analysis of “sexual consent” using a series of mandatory questions of law designed to eliminate the legal errors often made by decision-makers who routinely rely on personal beliefs about and attitudes towards “normal sexual behavior” in screening and deciding cases. In Canada, sexual consent is affirmative consent, the communication by words or conduct of “voluntary agreement” to a specific sexual activity, with a (...) specific person. As in many jurisdictions, however, the sexual assault laws are often not enforced. Reporting is lowest and non-enforcement highest in cases involving the most common type of assailants, those who are not strangers but instead persons the complainant knows, often quite well -- acquaintances, supervisors or co-workers, and family members. Reliance on popular narratives about “seduction” and “stranger-danger” leads complainants, police, prosecutors, lawyers, and trial judges, to truncate legal analysis of the facts and leap to erroneous conclusions about “consent.” Wrongful convictions and perverse acquittals, questionable plea bargains and ill-considered decisions not to charge, result. This proposal is designed to curtail the impact of pre-judgments, assumptions, and biases in legal reasoning about voluntariness and affirmative agreement and produce decisions that are legally sound, based on the application of the rule of law to the material facts. Law has long had better tools than the age-old and popular tales of “ravishment” and “seduction.” Those tools can and should be used. (shrink)

An important problem for decision-makers in society deals with the efficient and equitable allocation of scarce resources to individuals and groups. The significance of this problem is rapidly growing since there is a rising demand for scarce resources all over the world. Such resource dilemmas belong to a conceptually broader class of situations known as social dilemmas. In this type of dilemma, individual choices that appear ‘‘rational’’ often result in suboptimal group outcomes. In this article we study how people (...) make monetary allocation decisions between the community where they live and a neighbouring community, with the aim of finding out to what extent these decisions are subject to biased over-weighting. The manuscript reports four experiments that deal with the way individuals make such allocation decisions when the potential beneficiaries are such communities. The specific goal of these experiments is to gauge the amount of bias in the weights that people assign to the various beneficiaries. Taken together, the results from all the four experiments suggest that making the gain of the neighbouring community prominent to a higher extent de-biases the outcomes (the prominence effect) compared to when own community gain is made prominent. Place identity is discussed as a potentially important factor in this connection. Hence, it may be argued that there seems to be some kind of a pro-self component that is able to explain a large part of the variance observed for the prominence effect. Connections between such a factor and in-group favouritism are discussed. A strength of the study was that these major results appeared to be quite robust when considered as task effects, as the salience of the manipulated context factors in the studies (in terms of reliable main or interaction effects) did not distort them. (shrink)

Future-biased individuals systematically prefer positively valenced events to be in the future (positive future-bias) and negatively valenced events to be in the past (negative future-bias). The most extreme form of future-bias is absolute future-bias, whereby we completely discount the value of past events when forming our preferences. Various authors have thought that we are absolutely future-biased (Sullivan (2018:58); Parfit (1984:173) and that future-bias (absolute or otherwise) is at least rationally permissible (Prior (1959), Hare (2007; 2008), Kauppinen (2018), Heathwood (2008)). The (...) permissibility of future-bias is often held to be grounded in the structure of the temporal dimension. In this paper I consider several proposals for grounding the permissibility of such preferences and evaluate these in the light of the preferences we would have, and judge that we should have, in various time-travel scenarios. I argue that what we learn by considering these scenarios is that these preferences really have nothing to do with temporal structure. So if something grounds their permissibility, it is not temporal structure. (shrink)

I submit that epistemic progress in key areas of contemporary academic philosophy has been compromised by politically correct ideology. First, guided by an evolutionary account of ideology, results from social and cognitive psychology and formal philosophical methods, I expose evidence for political bias in contemporary Western academia and sketch a formalization for the contents of beliefs from the PC worldview taken to be of core importance, the theory of social oppression and the thesis of anthropological mental egalitarianism. Then, aided by (...) discussions from contemporary epistemology on epistemic values, I model the problem of epistemic appraisal using the frameworks of multi-objective optimization theory and multi-criteria decision analysis and apply it to politically correct philosophy. I conclude that philosophy guided by politically correct values is bound to produce constructs that are less truth-conducive and that spurious values which are ideologically motivated should be abandoned. Objections to my framework stemming from contextual empiricism, the feminine voice in ethics and political philosophy are considered. I conclude by prescribing the epistemic value of empirical adequacy, the contextual value of political diversity and the moral virtue of moral courage to reverse unwarranted trends in academic philosophy due to PC ideology. (shrink)

Algorithms can now identify patterns and correlations in the (big) datasets, and predict outcomes based on those identified patterns and correlations with the use of machine learning techniques and big data, decisions can then be made by algorithms themselves in accordance with the predicted outcomes. Yet, algorithms can inherit questionable values from the datasets and acquire biases in the course of (machine) learning, and automated algorithmic decision-making makes it more difficult for people to see algorithms as biased. While (...) researchers have taken the problem of algorithmic bias seriously, but the current discussion on algorithmic fairness tends to conceptualize ‘fairness’ in algorithmic fairness primarily as a technical issue and attempts to implement pre-existing ideas of ‘fairness’ into algorithms. In this paper, I show that such a view of algorithmic fairness as technical issue is unsatisfactory for the type of problem algorithmic fairness presents. Since decisions on fairness measure and the related techniques for algorithms essentially involve choices between competing values, ‘fairness’ in algorithmic fairness should be conceptualized first and foremost as a political issue, and it should be (re)solved by democratic communication. The aim of this paper, therefore, is to explicitly reconceptualize algorithmic fairness as a political question and suggest the current discussion of algorithmic fairness can be strengthened by adopting the accountability for reasonableness framework. (shrink)

People increasingly form beliefs based on information gained from automatically filtered Internet ‎sources such as search engines. However, the workings of such sources are often opaque, preventing ‎subjects from knowing whether the information provided is biased or incomplete. Users’ reliance on ‎Internet technologies whose modes of operation are concealed from them raises serious concerns about ‎the justificatory status of the beliefs they end up forming. Yet it is unclear how to address these concerns ‎within standard theories of knowledge and justification. (...) To shed light on the problem, we introduce a ‎novel conceptual framework that clarifies the relations between justified belief, epistemic responsibility, ‎action, and the technological resources available to a subject. We argue that justified belief is subject to ‎certain epistemic responsibilities that accompany the subject’s particular decision-taking circumstances, ‎and that one typical responsibility is to ascertain, so far as one can, whether the information upon which ‎the judgment will rest is biased or incomplete. What this responsibility comprises is partly determined by ‎the inquiry-enabling technologies available to the subject. We argue that a subject’s beliefs that are ‎formed based on Internet-filtered information are less justified than they would be if she either knew how ‎filtering worked or relied on additional sources, and that the subject may have the epistemic ‎responsibility to take measures to enhance the justificatory status of such beliefs.‎. (shrink)

The thesis of instrumental convergence holds that a wide range of ends have common means: for instance, self preservation, desire preservation, self improvement, and resource acquisition. Bostrom contends that instrumental convergence gives us reason to think that "the default outcome of the creation of machine superintelligence is existential catastrophe". I use the tools of decision theory to investigate whether this thesis is true. I find that, even if intrinsic desires are randomly selected, instrumental rationality induces biases towards certain (...) kinds of choices. Firstly, a bias towards choices which leave less up to chance. Secondly, a bias towards desire preservation, in line with Bostrom's conjecture. And thirdly, a bias towards choices which afford more choices later on. I do not find biases towards any other of the convergent instrumental means on Bostrom's list. I conclude that the biases induced by instrumental rationality at best weakly support Bostrom's conclusion that machine superintelligence is likely to lead to existential catastrophe. (shrink)

In a recent article, Bernáth and Tőzsér (2021) defend what they call the Bias Argument, a new skeptical argument from expert peer disagreement. They argue that the best contrastive causal explanation for disagreement among leading experts in philosophy is that they adopt their positions in a biased way. But if the leading experts are biased, non-experts either are also biased or only avoid bias through epistemic inferiority. Recognizing this is expected to prompt one to decrease one‘s confidence in one‘s philosophical (...) beliefs. This paper argues that some beliefs are immune to a key premise of the Bias Argument. To show this, the paper develops the concepts of self-favoring theories, decisive support, and standing-incommensurable disagreements. A plausible example of a self-favoring theory, dubbed Mere Reformed Protestantism, is sketched. Many disagreements over self-favoring theories and over beliefs decisively supported by self-favoring theories are shown to be standing-incommensurable. It is then argued that when non-experts are in standing-incommensurable disagreements with experts, the standards of assessing expertise are themselves controverted. This result undercuts the move in the Bias Argument from expert bias to non-expert bias. Finally, a couple reservations about the role of self-favoring theories in philosophy are addressed. (shrink)

Abstract: Heart attacks, or myocardial infarctions, are a leading cause of mortality worldwide. Early prediction and accurate analysis of potential risk factors play a crucial role in preventing heart attacks and improving patient outcomes. In this study, we conduct a comprehensive review of datasets related to heart attack analysis and prediction. We begin by examining the various types of datasets available for heart attack research, encompassing clinical, demographic, and physiological data. These datasets originate from diverse sources, including hospitals, research institutions, (...) and public health agencies. Our analysis aims to identify common features, data quality, and potential biases in these datasets. Next, we explore the predictive modeling techniques employed in heart attack prediction. Machine learning algorithms, such as decision trees, support vector machines, and deep neural networks, have gained prominence in predicting heart attacks. We discuss the strengths and limitations of these methods and highlight recent advancements in predictive modeling. Furthermore, we delve into the critical risk factors associated with heart attacks. Factors such as age, gender, hypertension, diabetes, and cholesterol levels are examined for their significance in predicting cardiac events. We also investigate the role of lifestyle factors, including smoking, diet, and physical activity, in heart attack risk assessment. Additionally, this review addresses the importance of data preprocessing and feature engineering in improving prediction accuracy. Feature selection methods, missing data handling, and data scaling techniques are discussed to enhance the robustness of heart attack prediction models. In conclusion, this comprehensive dataset review provides valuable insights into the state of heart attack analysis and prediction. It serves as a resource for researchers and healthcare professionals seeking to better understand the datasets available for heart attack research and the methods employed for accurate prediction. Ultimately, our efforts in dataset analysis and predictive modeling contribute to the advancement of preventive cardiology and the reduction of heart attack-related morbidity and mortality. (shrink)

This chapter is centered around an apparent tension that research on implicit bias raises between virtue and social knowledge. Research suggests that simply knowing what the prevalent stereotypes are leads individuals to act in prejudiced ways—biasing decisions about whom to trust and whom to ignore, whom to promote and whom to imprison—even if they reflectively reject those stereotypes. Because efforts to combat discrimination obviously depend on knowledge of stereotypes, a question arises about what to do next. This chapter argues that (...) the obstacle to virtue is not knowledge of stereotypes as such, but the “accessibility” of such knowledge to the agent who has it. “Accessibility” refers to how easily knowledge comes to mind. Social agents can acquire the requisite knowledge of stereotypes while resisting their pernicious influence, so long as that knowledge remains, in relevant contexts, relatively inaccessible. (shrink)

The question of how democracy can deal with cultural diversity has become more central than ever. The increasing flow of people to many Western democratic countries indicates that our societies will become more and more multicultural. But what is the best way for democracy to deal with cultural diversity? It has been argued that, given its communicative core, the Habermasian model of deliberative democracy provides a platform where cultural groups can concur on peaceful agreements. In this paper, I show the (...) limits of this model of democracy in relation to diverse cultural traditions to public interactions. I will discuss the case of societies and ethnic groups of a Confucian heritage and show that Habermas’ account of public deliberation is not a neutral method for facilitating political decision making, but is culturally biased. (shrink)

The English language now dominates scientific communications. Yet, many scientists have English as their second language. Their English proficiency may therefore often be more limited than that of a ‘native speaker’, and their scientific contributions (e.g. manuscripts) in English may frequently contain linguistic features that disrupt the fluency of a reader’s, or listener’s information processing even when the contributions are understandable. Scientific gatekeepers (e.g. journal reviewers) sometimes cite these features to justify negative decisions on manuscripts. Such justifications may rest on (...) the prima facie plausible assumption that linguistic characteristics that hinder fast and easy understandability of scientific contributions are epistemically undesirable in science. I shall raise some doubts about this assumption by drawing on empirical research on processing fluency and its biasing effects. I also argue that directing scientists with English as a foreign language toward approaching ‘native-level’ English can have the negative consequence of reducing their potential to make scientific belief formation more reliable. These points suggest that one seemingly compelling justification for linguistically discriminating against scientific contributions in ‘non-native’ English is questionable and that the common insistence by scientific gatekeepers on ‘native-like’ English may be epistemically harmful to science. (shrink)

Nudge is a popular public policy tool that harnesses well-known biases in human judgement to subtly guide people’s decisions, often to improve their choices or to achieve some socially desirable outcome. Thanks to recent developments in artificial intelligence (AI) methods new possibilities emerge of how and when our decisions can be nudged. On the one hand, algorithmically personalized nudges have the potential to vastly improve human daily lives. On the other hand, blindly outsourcing the development and implementation of nudges (...) to “black box” AI systems means that the ultimate reasons for why such nudges work, that is, the underlying human cognitive processes that they harness, will often be unknown. In this paper, we unpack this concern by considering a series of examples and case studies that demonstrate how AI systems can learn to harness biases in human judgment to reach a specified goal. Drawing on an analogy in a philosophical debate concerning the methodology of economics, we call for the need of an interdisciplinary oversight of AI systems that are tasked and deployed to nudge human behaviours. (shrink)

To address the rising concern that algorithmic decision-making may reinforce discriminatory biases, researchers have proposed many notions of fairness and corresponding mathematical formalizations. Each of these notions is often presented as a one-size-fits-all, absolute condition; however, in reality, the practical and ethical trade-offs are unavoidable and more complex. We introduce a new approach that considers fairness—not as a binary, absolute mathematical condition—but rather, as a relational notion in comparison to alternative decisionmaking processes. Using US mortgage lending as an (...) example use case, we discuss the ethical foundations of each definition of fairness and demonstrate that our proposed methodology more closely captures the ethical trade-offs of the decision-maker, as well as forcing a more explicit representation of which values and objectives are prioritised. (shrink)

Several scholars have recently entertained proposals for "epistocracy," a political regime in which decision-making power is concentrated in the hands of a society's most informed and competent citizens. These proposals rest on the claim that we can expect better political outcomes if we exclude incompetent citizens from participating in political decisions because competent voters are more likely to vote "correctly" than incompetent voters. We develop what we call the objection from selection bias to epistocracy: a procedure that selects voters (...) on the basis of their observed competence---as epistocracy does---will often be "biased" in the sense that competent voters will be, on average, more likely than incompetent voters to possess certain attributes that reduce the probability of voting correctly. Our objection generalizes the "demographic objection" discussed in previous literature, showing that the range of realistic scenarios in which epistocracy is vulnerable to selection bias is substantially broader than previous discussions appreciate. Our discussion also shows that previous discussions have obscured the force of the threat of selection bias. Since we lack reasons to believe that epistocratic proposals can avoid selection bias, we have no reason to seriously entertain epistocracy as a practical proposal. (shrink)

According to one picture of the mind, decisions and actions are largely the result of automatic cognitive processing beyond our ability to control. This picture is in tension with a foundational principle in ethics that moral responsibility for behavior requires the ability to control it. The discovery of implicit attitudes contributes to this tension. According to the ability argument against moral responsibility, if we cannot control implicit attitudes, and implicit attitudes cause behavior, then we cannot be morally responsible for that (...) behavior. The purpose of this paper is to refute the ability argument. Drawing on both scientific evidence in cognitive science and philosophical arguments in ethics and action theory, I argue that it is invalid and unsound because current evidence is insufficient to establish the premises that implicit attitudes are uncontrollable, that they significantly cause behavior, that responsibility always requires ability, and that even if uncontrollable attitudes did fully cause behavior, this entails that the behavior they cause is uncontrollable. The rejection of the ability argument questions the priority of the unconscious over the conscious mind in cognitive science, deprioritizes ability in theories of moral responsibility in ethics, and provides a strong reason to uphold moral responsibility for implicitly biased behavior. (shrink)

Abstract: The COVID-19 pandemic has posed unprecedented challenges to global healthcare systems, necessitating accurate and timely forecasting of cases for effective mitigation strategies. In this research paper, we present a novel approach to predict COVID-19 cases using Artificial Neural Networks (ANNs), harnessing the power of machine learning for epidemiological forecasting. Our ANNs-based forecasting model has demonstrated remarkable efficacy, achieving an impressive accuracy rate of 97.87%. This achievement underscores the potential of ANNs in providing precise and data-driven insights into the dynamics (...) of the pandemic. However, this paper underscores the critical importance of a comprehensive evaluation beyond accuracy, including metrics such as sensitivity, specificity, and the area under the ROC curve (AUC-ROC), to assess the model's performance robustness. The research paper offers detailed insights into the architecture of the ANN model, encompassing critical hyperparameters, data preprocessing techniques, and regularization strategies employed to optimize model accuracy. Ethical considerations surrounding data privacy and potential biases within the COVID-19 dataset are also addressed. While the achieved accuracy is a significant milestone, this study underscores the dynamic and evolving nature of the pandemic, necessitating continuous model refinement and validation. Furthermore, it emphasizes the importance of considering false positives and false negatives in the context of public health decision-making. In conclusion, this research contributes to the arsenal of tools available for pandemic management by showcasing the potential of ANNs in COVID-19 case forecasting. It encourages ongoing exploration and adaptation of predictive models to enhance their applicability in real-world public health scenarios, ultimately contributing to more effective pandemic control and response efforts. (shrink)

Artificial intelligence (AI) systems are increasingly adopted to make decisions in domains such as business, education, health care, and criminal justice. However, such algorithmic decision systems can have prevalent biases against marginalized social groups and undermine social justice. Explainable artificial intelligence (XAI) is a recent development aiming to make an AI system’s decision processes less opaque and to expose its problematic biases. This paper argues against technical XAI, according to which the detection and interpretation of algorithmic (...) bias can be handled more or less independently by technical experts who specialize in XAI methods. Drawing on resources from feminist epistemology, we show why technical XAI is mistaken. Specifically, we demonstrate that the proper detection of algorithmic bias requires relevant interpretive resources, which can only be made available, in practice, by actively involving a diverse group of stakeholders. Finally, we suggest how feminist theories can help shape integrated XAI: an inclusive social-epistemic process that facilitates the amelioration of algorithmic bias. (shrink)

The Value-free ideal of science (VFI) is a view that claims that scientists should not use non-epistemic values when they are justifying their hypotheses, and is widely considered to be obsolete in the philosophy of science. I will defend the ideal by demonstrating that acceptance of non-epistemic values, prohibited by VFI, necessitates legitimizing certain problematic scientific practices. Such practices, including biased methodological decisions or Questionable Research Practices (QRP), significantly contribute to the Replication Crisis. I will argue that the realizability of (...) VFI is not a necessary condition for its validity. Then, I will show how some of the prominent proposals of value-laden science legitimize problematic scientific practices, provide real-world examples, and generalize the argument. Finally, I will show how value-laden methodological decisions contribute to the Replicability Crisis and discuss two strategies for realizing VFI. (shrink)

When people must either save a greater number of people from a smaller harm or a smaller number from a greater harm, do their choices reflect a reasonable moral outlook? We pursue this question with the help of an experiment. In our experiment, two-fifths of subjects employ a similarity heuristic. When alternatives appear dissimilar in terms of the number saved but similar in terms of the magnitude of harm prevented, this heuristic mandates saving the greater number. In our experiment, this (...) leads to choices that are inconsistent with all standard theories of justice. We argue that this demonstrates the untrustworthiness of distributive judgments in cases that elicit similarity-based choice. (shrink)

The elimination of gatekeepers for scientific publication has been represented as a means to promote the core moral values of open science, including democratic decision-making and inclusiveness. I argue that this framing ignores the reality that gatekeeping is a way of structuring prestige hierarchies, and that without gatekeeping, some other structuring would be needed: the flattening of prestige hierarchies is not possible given scientists’ need to navigate information overload. I consider two potential restructurings of prestige hierarchies, one based on (...) citation count and the other on search algorithm rank. These are shown to simply reintroduce status biases and hierarchies in ways that either do not further the open science ideals of democracy and inclusiveness, or else involve some de facto gatekeeping. Gatekeeper elimination should not be thought of as an intrinsic part of the open science movement. In fact, insofar as gatekeeping is guided by professional ideals of impartiality and diligence, it can be thought of as an ally of open science values. (shrink)

Capacity of conscious agents to perform genuine choices among future alternatives is a prerequisite for moral responsibility. Determinism that pervades classical physics, however, forbids free will, undermines the foundations of ethics, and precludes meaningful quantification of personal biases. To resolve that impasse, we utilize the characteristic indeterminism of quantum physics and derive a quantitative measure for the amount of free will manifested by the brain cortical network. The interaction between the central nervous system and the surrounding environment is shown (...) to perform a quantum measurement upon the neural constituents, which actualize a single measurement outcome selected from the resulting quantum probability distribution. Inherent biases in the quantum propensities for alternative physical outcomes provide varying amounts of free will, which can be quantified with the expected information gain from learning the actual course of action chosen by the nervous system. For example, neuronal electric spikes evoke deterministic synaptic vesicle release in the synapses of sensory or somatomotor pathways, with no free will manifested. In cortical synapses, however, vesicle release is triggered indeterministically with probability of 0.35 per spike. This grants the brain cortex, with its over 100 trillion synapses, an amount of free will exceeding 96 terabytes per second. Although reliable deterministic transmission of sensory or somatomotor information ensures robust adaptation of animals to their physical environment, unpredictability of behavioral responses initiated by decisions made by the brain cortex is evolutionary advantageous for avoiding predators. Thus, free will may have a survival value and could be optimized through natural selection. (shrink)

Should editors of scientific journals practice triple-anonymous reviewing? I consider two arguments in favor. The first says that insofar as editors’ decisions are affected by information they would not have had under triple-anonymous review, an injustice is committed against certain authors. I show that even well-meaning editors would commit this wrong and I endorse this argument. The second argument says that insofar as editors’ decisions are affected by information they would not have had under triple-anonymous review, it will negatively affect (...) the quality of published papers. I distinguish between two kinds of biases that an editor might have. I show that one of them has a positive effect on quality and the other a negative one, and that the combined effect could be either positive or negative. Thus I do not endorse the second argument in general. However, I do endorse this argument for certain fields, for which I argue that the positive effect does not apply. (shrink)

Sunstein argues that democratic theory has recently rested its normative claims on a vast but empirically uninformed optimism about the ability of collective deliberation to lead to morally and rationally better decisions. Once that question is considered empirically, he argues, deliberation turns out to be mixed at best, and a disaster at worst. I want to suggest that Sunstein exaggerates the claims of the deliberative democrats, and interprets the empirical literature against deliberation in a way that appears, even based on (...) his own descriptions of the studies, to be unfairly biased against the value of deliberation. (shrink)

An increasing vaccine hesitancy among parents, which has resulted in insufficient rates of immunization, provides reason to reconsider childhood vaccination practices. Studies suggest that parents’ decision-making process concerning whether to vaccinate their child is highly influenced by cognitive biases. These biases can be utilized to increase vaccination uptake via changes in the choice context. This article considers childhood vaccination programmes, which involve children being vaccinated in school or daycare unless their parents actively “opt out”. We suggest that (...) such programmes reconcile parents’ decisional authority and vaccination duties. First, opt-out childhood vaccination based in schools or daycare centres are not disrespectful of parental authority. Second, the programme aligns the default setting with a moral obligation to vaccinate one’s child that most parents have. (shrink)

Peer commentary on: Blumenthal-Barby, J. S. (2016). Biases and heuristics in decision making and their impact on autonomy. The American Journal of Bioethics, 16(5), 5-15.

This article advances two views on the role of evaluative judgment in clinical assessments of decision-making capacity. The first is that it is rationally impossible for such assessments to exclude judgments of the values a patient uses to motivate their decision-making. Predictably, and second, attempting to exclude such judgments sometimes yields outcomes that contain intractable dilemmas that harm patients. These arguments count against the prevailing model of assessment in common law countries—the four abilities model—which is often incorrectly advertised (...) as being value-neutral in respect of patient decision-making both by its proponents and in statute. A straightforward evaluative model of capacity assessment which wears its values on its sleeves and is biased against what are called ‘serious prudential mistakes’ avoids these rational and practical problems. (shrink)

The past four decades of research in the social sciences have shed light on two important phenomena. One is that human decision-making is full of predicable errors and biases that often lead individuals to make choices that defeat their own ends (i.e., the bad choice phenomenon), and the other is that individuals’ decisions and behaviors are powerfully shaped by their environment (i.e., the influence phenomenon). Some have argued that it is ethically defensible that the influence phenomenon be utilized (...) to address the bad choice phenomenon. They propose that “choice architects” learn about the various ways in which choices can be influenced and directed by the environment, and then work to design environments, broadly construed, that influence individuals towards choices that make them better off. Those who advocate intentionally creating choice environments that lead people to better choices believe that doing so is ethically permissible because (1) it makes people better off, and (2) it does so in a way that is entirely compatible with individual liberty. The evaluation of these two claims is the main focus of this paper. (shrink)

People seem more divided than ever before over social and political issues, entrenched in their existing beliefs and unwilling to change them. Empirical research on mechanisms driving this resistance to belief change has focused on a limited set of well-known, charged, contentious issues and has not accounted for deliberation over reasons and arguments in belief formation prior to experimental sessions. With a large, heterogeneous sample (N = 3,001), we attempt to overcome these existing problems, and we investigate the causes and (...) consequences of resistance to belief change for five diverse and less contentious socio-political issues. After participants chose initially to support or oppose a given socio-political position, they were provided with reasons favoring their chosen position (affirming reasons), reasons favoring the other, unchosen position (conflicting reasons), or all reasons for both positions (reasons for both sides). Our results indicate that participants are more likely to stick with their initial decisions than to change them no matter which reasons are considered, and that this resistance to belief change is likely due to a motivated, biased evaluation of the reasons to support their initial beliefs (prior-belief bias). More specifically, they rated affirming reasons more favorably than conflicting reasons—even after accounting for reported prior knowledge about the issue, the novelty of the reasons presented, and the reported strategy used to make the initial decision. In many cases, participants who did not change their positions tended to become more confident in the superiority of their positions after considering many reasons for both sides. (shrink)

According to cultural evolutionary theory in the tradition of Boyd and Richerson, cultural evolution is driven by individuals' learning biases, natural selection, and random forces. Learning biases lead people to preferentially acquire cultural variants with certain contents or in certain contexts. Natural selection favors individuals or groups with fitness-promoting variants. Durham (1991) argued that Boyd and Richerson's approach is based on a "radical individualism" that fails to recognize that cultural variants are often "imposed" on people regardless of their (...) individual decisions. Fracchia and Lewontin (2005) raised a similar challenge, suggesting that the success of a variant is often determined by the degree of power backing it. With power, a ruler can impose beliefs or practices on a whole population by diktat, rendering all of the forces represented in cultural evolutionary models irrelevant. It is argued here, based on work by Boehm (1999, 2012), that, from at least the time of the early Middle Paleolithic, human bands were controlled by powerful coalitions of the majority that deliberately guided the development of moral norms to promote the common good. Cultural evolutionary models of the evolution of morality have been based on false premises. However, Durham (1991) and Fracchia and Lewontin's (2005) challenge does not undermine cultural evolutionary modeling in nonmoral domains. (shrink)

This paper critically explores the ethical dimensions of Behavioral Public Policy (BPP), a domain grounded in the understanding that human rationality is bounded and that this limitation often leads to behaviors deemed irrational. By applying the behavioral lens, which posits that people operate under bounded rationality, BPP aims to craft interventions that safeguard individuals against their biases. However, this approach raises significant ethical concerns, both in the scientific underpinnings of BPP and its application through policy interventions. Accordingly, this paper (...) examines two distinct ethical dimensions of BPP, both as a scientific discipline and through its intervention methodologies. The analysis of the first dimension argues that, viewing bounded rationality as only instrumental in decision-making processes, risks oversimplifying ethical complexities. Such simplification may ignore the moral and value-based rationalities underlying decisions, potentially misattributing instances of immorality and akrasia (the failure to act according to one's judgment) to mere deficiencies in rational thinking. Secondly, the paper examines the impact of BPP on moral behavior and character development, addressing ethical concerns like the evidentiary basis of BPP research, the bounded rationality of choice architects themselves, and the morality of behavior changes induced by policy. Overall, this article provides a much-needed examination of the moral considerations associated with behavioral strategies in public policy and its epistemological foundations, contributing to a more comprehensive understanding of their ethical implications . (shrink)

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

This chapter analyses the behavioural economist Matthew Rabin's work on biases in decision-making. Rabin argues that these biases cause self-harm and that we should tax individuals to ensure that they do not give in to these biases. The chapter's core question is whether there is a soft-paternalistic justification for these taxes. The answer is nuanced. It argues that Rabin’s description of these biases as “irrational” is not always appropriate—sometimes, for example, they are merely a form (...) of preference change. When they are due to the latter, the behaviour is fully voluntary, and there exists no soft-paternalistic justification for coercive intervention. It also argues that even when these biases do lead to substantially non-voluntary choices, we should prefer policies that improve self-knowledge and self-control to taxes. However, the paper notes that Rabin’s analysis reveals circumstances under which these autonomy-enhancing strategies will not be effective. In such cases, and only in such cases, Rabin’s taxes have a soft paternalistic justification. (shrink)