Pluralism about scientific method is more-or-less accepted, but the consequences have yet to be drawn out. Scientists adopt different methods in response to different epistemic situations: depending on the system they are interested in, the resources at their disposal, and so forth. If it is right that different methods are appropriate in different situations, then mismatches between methods and situations are possible. This is most likely to occur due to method bias: when we prefer a particular kind (...) of method, despite that method clashing with evidential context or our aims. To explore these ideas, we sketch a kind of method pluralism which turns on two properties of evidence, before using agent-based models to examine the relationship between methods, epistemic situations, and bias. Based on our results, we suggest that although method bias can undermine the efficiency of a scientific community, it can also be productive through preserving a diversity of evidence. We consider circumstances where method bias could be particularly egregious, and those where it is a potential virtue, and argue that consideration of method bias reveals that community standards deserve a central place in the epistemology of science. (shrink)

Publication date: 30 August 2017 Source: Author: Ghulam Abid, Tahira Hassan Butt Employees are the building blocks and valuable assets in an organization. Organizational researchers and practitioners have shown a burgeoning attention to satisfy and retain key performer as the cost of leaving a job is very high for the employing organizations. Discovering turnover intention in its formation stages is very crucial, not only to resist its’ piled up effect but also to control the actual turnover in the future. Most (...) of the times, management is not aware of the employee’s quit intention because employees don’t show their intention explicitly until they actually leave the organization. However, majority of the times employees share their feeling with their colleagues or other close work mates. Based on positive relationship at work, we argued that the individuals who work together normally share their feelings with their close colleagues regarding their decision of leaving or staying with the current employer. Therefore, the objective of the current study is to investigate the relationship between turnover intention and expressed turnover intention. Furthermore, we offer a new perspective to data collection from other sources, which will assist us in shortening the questionnaire, also minimizing the common method bias and knowing the quit intention from other source. Finally, theoretical and practical implications along with direction for future studies are also discussed. (shrink)

Case methods of reasoning are persuasive, but we need to address problems of bias in order to use them to reach morally justifiable conclusions. A bias is an unwarranted inclination or a special perspective that disposes us to mistaken or one-sided judgments. The potential for bias arises at each stage of a case method of reasoning including in describing, framing, selecting and comparing of cases and paradigms. A problem of bias occurs because to identify the (...) relevant features for such purposes, we must use general views about what is relevant; but some of our general views are biased, both in the sense of being unwarranted inclinations and in the sense that they are one of many viable perspectives. This reliance upon general views to determine relevancy creates additional difficulties for defenders who maintain that case methods of moral reasoning are not only useful, but more basic, reliable or prior to other forms of moral reasoning. If we cannot identify the case's relevant features and issues independently of our general views or biases, we need further explanation about why a case method or casuistry should be viewed as prior to or more basic or reliable than other forms of moral reasoning. Problems of bias also arise for other methods of reasoning. In medical science, case reviews are regarded as an unreliable way to form generalizations, and methods such as clinical trials are used to address bias. (shrink)

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

_Anthropic Bias_ explores how to reason when you suspect that your evidence is biased by "observation selection effects"--that is, evidence that has been filtered by the precondition that there be some suitably positioned observer to "have" the evidence. This conundrum--sometimes alluded to as "the anthropic principle," "self-locating belief," or "indexical information"--turns out to be a surprisingly perplexing and intellectually stimulating challenge, one abounding with important implications for many areas in science and philosophy. There are the philosophical thought experiments and paradoxes: (...) the Doomsday Argument; Sleeping Beauty; the Presumptuous Philosopher; Adam & Eve; the Absent-Minded Driver; the Shooting Room. And there are the applications in contemporary science: cosmology ; evolutionary theory ; the problem of time's arrow ; quantum physics ; game-theory problems with imperfect recall ; even traffic analysis. _Anthropic Bias_ argues that the same principles are at work across all these domains. And it offers a synthesis: a mathematically explicit theory of observation selection effects that attempts to meet scientific needs while steering clear of philosophical paradox. (shrink)

_Anthropic Bias_ explores how to reason when you suspect that your evidence is biased by "observation selection effects"--that is, evidence that has been filtered by the precondition that there be some suitably positioned observer to "have" the evidence. This conundrum--sometimes alluded to as "the anthropic principle," "self-locating belief," or "indexical information"--turns out to be a surprisingly perplexing and intellectually stimulating challenge, one abounding with important implications for many areas in science and philosophy. There are the philosophical thought experiments and paradoxes: (...) the Doomsday Argument; Sleeping Beauty; the Presumptuous Philosopher; Adam & Eve; the Absent-Minded Driver; the Shooting Room. And there are the applications in contemporary science: cosmology ; evolutionary theory ; the problem of time's arrow ; quantum physics ; game-theory problems with imperfect recall ; even traffic analysis. _Anthropic Bias_ argues that the same principles are at work across all these domains. And it offers a synthesis: a mathematically explicit theory of observation selection effects that attempts to meet scientific needs while steering clear of philosophical paradox. (shrink)

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

The term 'publication bias' usually refers to the tendency for a greater proportion of statistically significant positive results of experiments to be published and, conversely, a greater proportion of statistically significant negative or null results not to be published. It is widely accepted in the fields of healthcare and psychological research to be a major threat to the validity of systematic reviews and meta-analyses. Some methodological work has previously been undertaken, by the author and others, in the field of (...) educational research to investigate the extent of the problem. This paper describes the problem of publication bias with reference to its history in a number of fields, with special reference to the area of educational research. Informal methods for detecting publication bias in systematic reviews and meta-analyses of controlled trials are outlined and retrospective and prospective methods for dealing with the problem are suggested. (shrink)

ABSTRACT: The term ‘publication bias’ usually refers to the tendency for a greater proportion of statistically significant positive results of experiments to be published and, conversely, a greater proportion of statistically significant negative or null results not to be published. It is widely accepted in the fields of healthcare and psychological research to be a major threat to the validity of systematic reviews and meta-analyses. Some methodological work has previously been undertaken, by the author and others, in the field (...) of educational research to investigate the extent of the problem. This paper describes the problem of publication bias with reference to its history in a number of fields, with special reference to the area of educational research. Informal methods for detecting publication bias in systematic reviews and meta-analyses of controlled trials are outlined and retrospective and prospective methods for dealing with the problem are suggested. (shrink)

Political fact-checkers evaluate the truthfulness of politicians’ claims. This paper contributes to an emerging scholarly debate on whether fact-checkers treat political parties differently in a systematic manner depending on their ideology (bias). We first examine the available approaches to analyze bias and then present a new approach in two steps. First, we propose a logistic regression model to analyze the outcomes of fact-checks and calculate how likely each political party will obtain a truth score. We test our model (...) with a sample of fact-checks from Newtral, a major Spanish fact-checker. Our model would signal bias under two assumptions: a) all political parties are on average equally accurate in their statements; b) the verification method gives precise instructions and is implemented systematically. We investigate this second assumption with a series of interviews with Newtral fact-checkers. We show that standard verification protocols are so loosely implemented that fact-checks reflect a set of journalistic decisions, rather than a bias in the statistical sense. We call for a more rigorous definition of verification methods as a pre-requisite for an unbiased assessment of politician’s claims. (shrink)

In recent decades, economists have developed methods for measuring the country-wide level of inequality of opportunity. The most popular method, called the ex-ante method, uses data on the distribution of outcomes stratified by groups of individuals with the same circumstances, in order to estimate the part of outcome inequality that is due to these circumstances. I argue that these methods are potentially biased, both upwards and downwards, and that the unknown size of this bias could be large. (...) To argue that the methods are biased, I show that they ought to measure causal or counterfactual quantities, while the methods are only capable of identifying correlational information. To argue that the bias is potentially large, I illustrate how the causal complexity of the real world leads to numerous non-causal correlations between circumstances and outcomes and respond to objections claiming that such correlations are nonetheless indicators of unfair disadvantage, that is, inequality of opportunity. (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)

Ecological validity is key in science and laboratory experiments alone cannot fully explain complex real-world phenomena. Yet the three flaws Cesario proposes do not characterize the field and are not “methodological trickery,” designed to intentionally mislead practitioners. In school discipline alone, these alleged flaws are indeed addressed and laboratory experimentation has contributed to mitigation of a real-world problem.

Across the world, artificial intelligence (AI) technologies are being more widely employed in public sector decision-making and processes as a supposedly neutral and an efficient method for optimizing delivery of services. However, the deployment of these technologies has also prompted investigation into the potentially unanticipated consequences of their introduction, to both positive and negative ends. This paper chooses to focus specifically on the relationship between gender bias and AI, exploring claims of the neutrality of such technologies and how (...) its understanding of bias could influence policy and outcomes. Building on a rich seam of literature from both technological and sociological fields, this article constructs an original framework through which to analyse both the perpetuation and mitigation of gender biases, choosing to categorize AI technologies based on whether their input is text or images. Through the close analysis and pairing of four case studies, the paper thus unites two often disparate approaches to the investigation of bias in technology, revealing the large and varied potential for AI to echo and even amplify existing human bias, while acknowledging the important role AI itself can play in reducing or reversing these effects. The conclusion calls for further collaboration between scholars from the worlds of technology, gender studies and public policy in fully exploring algorithmic accountability as well as in accurately and transparently exploring the potential consequences of the introduction of AI technologies. (shrink)

There is an active debate within the field of phonology concerning the cognitive status of substantive phonetic factors such as ease of articulation and perceptual distinctiveness. A new framework is proposed in which substance acts as a bias, or prior, on phonological learning. Two experiments tested this framework with a method in which participants are first provided highly impoverished evidence of a new phonological pattern, and then tested on how they extend this pattern to novel contexts and novel (...) sounds. Participants were found to generalize velar palatalization (e.g., the change from [k] as in keep to [t⌢∫S] as in cheap) in a way that accords with linguistic typology, and that is predicted by a cognitive bias in favor of changes that relate perceptually similar sounds. Velar palatalization was extended from the mid front vowel context (i.e., before [e] as in cape) to the high front vowel context (i.e., before [i] as in keep), but not vice versa. The key explanatory notion of perceptual similarity is quantified with a psychological model of categorization, and the substantively biased framework is formalized as a conditional random field. Implications of these results for the debate on substance, theories of phonological generalization, and the formalization of similarity are discussed. (shrink)

Aims: Attentional bias, alcohol craving, and anxiety have important implications in the development and maintenance of alcohol use disorder. The current study aims to test the effectiveness of a Virtual Reality Cue-Exposure Therapy to reduce levels of alcohol craving and anxiety and prompt changes in AB toward alcohol content.Method: A 49-year-old male participated in this study, diagnosed with severe AUD, who also used tobacco and illicit substances on an occasional basis and who made several failed attempts to cease (...) substance misuse. The protocol consisted of six VR-CET booster sessions and two assessment sessions over the course of 5 weeks. The VR-CET program consisted of booster therapy sessions based on virtual reality exposure to preferred alcohol-related cues and contexts. The initial and final assessment sessions were focused on exploring AB, alcohol craving, and anxiety using paper-and-pencil instruments and the eye-tracking and VR technologies at different time points.Results: Pre and post assessment sessions indicated falls on the scores of all instruments assessing alcohol craving, anxiety, and AB.Conclusions: This case report, part of a larger project, demonstrates the effectiveness of the VR-CET booster sessions in AUD. In the post-treatment measurements, a variety of instruments showed a change in the AB pattern and an improvement in craving and anxiety responses. As a result of the systematic desensitization, virtual exposure gradually reduced the responses to significant alcohol-related cues and contexts. The implications for AB, anxiety and craving are discussed. (shrink)

Fundamentalism has been widely reckoned as one among many other watchful social phenomena currently. There are two general approaches to it. The first is from those who perceive fundamentalism as a movement of militant piety found almost in any religion, and therefore fundamentalism cannot necessarily be identified with a violent movement. The second is from those who categorize fundamentalism as a political movement with an objective of worldly power, and therefore it is susceptible to turning into a violent movement. In (...) investigating the two views closely, I attempt to put forward a couple of hypothetical inquiries. Is fundamentalism a common phenomenon and common feature found in almost any religion? The answer is yes. Is fundamentalism identical to violent movement? The answer is no. Is fundamentalism then impossibly and utterly unrelated to violent movements? The answer is no. If fundamentalism is unidentical with violent movements but not a few fundamentalists can also turn to be perpetrators of what is called religious violence or violence in the name of religion, then what arguments can be set forth to ensure that fundamentalism cannot be overlooked anymore as one among many other major social problems of our age? This article aims to examine fundamentalism through epistemological and axiological criticism, and to investigate that to a certain range fundamentalism is a form of religious cognitive and behavioral bias, and both as a militant piety and as a political movement fundamentalism should at best be approached from their interplayed relation. (shrink)

According to major cognitive theories of emotional disorders cognitive biases are partly responsible for their onset and maintenance. The direct test of this assumption is possible only if experimental method capable of altering a given form of cognitive bias is available. The purpose of the study was to examine the effectiveness of a novel implicit memory bias training procedure based on the emotional version of the classical Sternberg’s short-term memory task with negative, neutral and positive words. 108 (...) participants, who completed the PANAS and the CES-D questionnaires, were randomly assigned to the control group, the No-Negative group, in which the target words in the Sternberg’s task were either positive or neutral but never negative or the Negative-New group in which the negative target words in the modified Sternberg’s task were always new. This training was followed by the recollection stage. Only one of the training protocols resulted in significant effects at the recall stage - individuals in the No-Negative group recalled more positive words and fewer negative words than those in the control group. These results show that it may be possible to experimentally induce memory bias characteristic of non-depressed individuals. (shrink)

Many philosophical thought experiments and arguments involve unusual cases. We present empirical reasons to doubt the reliability of intuitive judgments and conclusions about such cases. Inferences and intuitions prompted by verbal case descriptions are influenced by routine comprehension processes which invoke stereotypes. We build on psycholinguistic findings to determine conditions under which the stereotype associated with the most salient sense of a word predictably supports inappropriate inferences from descriptions of unusual (stereotype-divergent) cases. We conduct an experiment that combines plausibility ratings (...) with pupillometry to document this “salience bias.” We find that under certain conditions, competent speakers automatically make stereotypical inferences they know to be inappropriate. (shrink)

Background: Facial attractiveness influences our perceptions of others, with beautiful faces reaping societal rewards and anomalous faces encountering penalties. The purpose of this study was to determine associations of visual attention with bias and social dispositions toward people with facial anomalies. -/- Methods: Sixty subjects completed tests evaluating implicit bias, explicit bias, and social dispositions before viewing publicly available images of preoperative and postoperative patients with hemifacial microsomia. Eye-tracking was used to register visual fixations. -/- Results: Participants (...) with higher implicit bias scores fixated significantly less on the cheek and ear region preoperatively (P = 0.004). Participants with higher scores in empathic concern and perspective taking fixated more on the forehead and orbit preoperatively (P = 0.045) and nose and lips (P = 0.027) preoperativel. -/- Conclusions: Participants with higher levels of implicit bias spent less visual attention on anomalous facial anatomy, whereas participants with higher levels of empathic concern and perspective taking spent more visual attention on normal facial anatomy. Levels of bias and social dispositions such as empathy may predict layperson gaze patterns toward those with facial anomalies and provide insights to neural mechanisms underlying the "anomalous is bad" paradigm. (shrink)

ABSTRACTNew methods of calculating indices from the dot-probe task measure temporal dynamics in attention bias or fluctuations in attention bias towards and away from emotional stimuli over time. H...

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

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

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)

Building on past constructive criticism, the present study provides further methodological development focused on the elimination of bias that may occur during first-person observation. First, various sources of errors that may accompany introspection are distinguished based on previous critical literature. Four main errors are classified, namely attentional, attributional, conceptual, and expressional error. Furthermore, methodological recommendations for the possible elimination of these errors have been determined based on the analysis and focused excerpting of introspective scientific literature. The following groups of (...) methodological recommendations were determined: 1) a better focusing of the subject’s attention to their mental processes, 2) providing suitable stimuli, and 3) the sharing of introspective experience between subjects. Furthermore, the potential of adjustments in introspective research designs for eliminating attentional, attributional, conceptual, and expressional error is discussed. (shrink)

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

The twin goals of this essay are: to investigate a family of cases in which the goal of guaranteed convergence to the truth is beyond our reach; and to argue that each of three strands prominent in contemporary epistemological thought has undesirable consequences when confronted with the existence of such problems. Approaches that follow Reichenbach in taking guaranteed convergence to the truth to be the characteristic virtue of good methods face a vicious closure problem. Approaches on which there is a (...) unique rational doxastic response to any given body of evidence can avoid incoherence only by rendering epistemology a curiously limited enterprise. Bayesian approaches rule out humility about one’s prospects of success in certain situations in which failure is typical. (shrink)

In the late 20th century theorists within the radical feminist tradition such as Haraway highlighted the impossibility of separating knowledge from knowers, grounding firmly the idea that embodied bias can and does make its way into argument. Along a similar vein, Moulton exposed a gendered theme within critical thinking that casts the feminine as toxic ‘unreason’ and the ideal knower as distinctly masculine; framing critical thinking as a method of masculine knowers fighting off feminine ‘unreason’. Theorists such as (...) Burrow have picked up upon this tradition, exploring the ways in which this theme of overly masculine, or ‘adversarial’, argumentation is both unnecessary and serves as an ineffective base for obtaining truth. Rooney further highlighted how this unnecessarily gendered context results in argumentative double binds for women, undermining their authority and stifling much-needed diversity within philosophy as a discipline.These are damning charges that warrant a response within critical thinking frameworks. We suggest that the broader critical thinking literature, primarily that found within contexts of critical pedagogy and dispositional schools, can and should be harnessed within the critical thinking literature to bridge the gap between classical and feminist thinkers. We highlight several methods by which philosophy can retain the functionality of critical thinking while mitigating the obstacles presented by feminist critics and highlight how the adoption of such methods not only improves critical thinking, but is also beneficial to philosophy, philosophers and feminists alike. (shrink)

We simulate trial data to test speculative claims about research methods, such as the impact of publication bias.

Objectives: To investigate whether different methods of obtaining informed consent affected recruitment to a study of delirium in older, medically ill hospital inpatients.Design: Open randomised study.Setting: Acute medical service for older people in an inner city teaching hospital.Participants: Patients 70 years or older admitted to the unit within three days of hospital admission randomised into two groups.Intervention: Attempted recruitment of subjects to a study of the natural history of delirium. This was done by either a formal test of capacity, followed (...) by either a request for consent or an attempt at obtaining assent from a proxy, or a combined informal capacity/consent process.Main outcome measures: Prevalence and severity of delirium, and, as case mix measures, length of hospital stay and destination on discharge.Results: Recruitment of subjects through establishing formal capacity and then informed consent was less successful and, compared with those recruited through the usual combined capacity/consent approach, yielded a sample with less cognitive impairment, lower severity of delirium, lower probability of case note diagnosis of delirium and lower rate of entering a care home.Conclusions: Methods of obtaining informed consent may significantly influence the case mix of subjects recruited to a study of delirium. Stringent testing of capacity may exclude patients with delirium from studies, thus rendering findings less generalisable. A different method is necessary to achieve an ethical balance between respecting autonomy through obtaining adequate informed consent and avoiding sample bias. (shrink)

In this paper we investigate risk prediction of criminal re-offense among juvenile defendants using general-purpose machine learning algorithms. We show that in our dataset, containing hundreds of cases, ML models achieve better predictive power than a structured professional risk assessment tool, the Structured Assessment of Violence Risk in Youth, at the expense of not satisfying relevant group fairness metrics that SAVRY does satisfy. We explore in more detail two possible causes of this algorithmic bias that are related to biases (...) in the data with respect to two protected groups, foreigners and women. In particular, we look at the differences in the prevalence of re-offense between protected groups and the influence of protected group or correlated features in the prediction. Our experiments show that both can lead to disparity between groups on the considered group fairness metrics. We observe that methods to mitigate the influence of either cause do not guarantee fair outcomes. An analysis of feature importance using LIME, a machine learning interpretability method, shows that some mitigation methods can shift the set of features that ML techniques rely on away from demographics and criminal history which are highly correlated with sensitive features. (shrink)

While it seems unlikely that any method of guaranteeing human-friendliness on the part of advanced Artificial General Intelligence systems will be possible, this doesn’t mean the only alternatives are throttling AGI development to safeguard humanity, or plunging recklessly into the complete unknown. Without denying the presence of a certain irreducible uncertainty in such matters, it is still sensible to explore ways of biasing the odds in a favorable way, such that newly created AI systems are significantly more likely than (...) not to be Friendly. Several potential methods of effecting such biasing are explored here, with a particular but non-exclusive focus on those that are relevant to open-source AGI projects, and with illustrative examples drawn from the OpenCog open-source AGI project. Issues regarding the relative safety of open versus closed approaches to AGI are discussed and then nine techniques for biasing AGIs in favor of Friendliness are presented: 1. Engineer the capability to acquire integrated ethical knowledge.2. Provide rich ethical interaction and instruction, respecting developmental stages.3. Develop stable, hierarchical goal systems.4. Ensure that the early stages of recursive self-improvement occur relatively slowly and with rich human involvement.5. Tightly link AGI with the Global Brain.6. Foster deep, consensus-building interactions between divergent viewpoints.7. Create a mutually supportive community of AGIs.8. Encourage measured co-advancement of AGI software and AGI ethics theory.9. Develop advanced AGI sooner not later. In conclusion, and related to the final point, we advise the serious co-evolution of functional AGI systems and AGI-related ethical theory as soon as possible, before we have so much technical infrastructure that parties relatively unconcerned with ethics are able to rush ahead with brute force approaches to AGI development. (shrink)

Social psychologists often describe “implicit” racial biases as entirely unconscious, and as mere associations between groups and traits, which lack intentional content, e.g., we associate “black” and “athletic” in much the same way we associate “salt” and “pepper.” However, recent empirical evidence consistently suggests that individuals are aware of their implicit biases, albeit in partial, inarticulate, or even distorted ways. Moreover, evidence suggests that implicit biases are not “dumb” semantic associations, but instead reflect our skillful, norm-sensitive, and embodied engagement with (...) social reality. This essay draws on phenomenological and hermeneutic methods and concepts to better understand what social-psychological research has begun to reveal about the conscious access individuals have to their own racial attitudes, as well as the intentional contents of the attitudes themselves. -/- First, I argue that implicit racial biases form part of the “background” of social experience. That is, while they exert a pervasive influence on our perceptions, judgments, and actions, they are frequently felt but not noticed, or noticed but misinterpreted. Second, I argue that our unreflective racial attitudes are neither mere associations nor fully articulated, propositionally structured beliefs or emotions. Their intentional contents are fundamentally indeterminate. For example, when a white person experiences a “gut feeling” of discomfort during an interaction with a black person, there is a question about the meaning or nature of that discomfort. Is it a fear of black people? Is it anxiety about appearing racist? There is, I argue, no general, determinate answer to such questions. The contents of our unreflective racial attitudes are fundamentally vague and open-ended, although I explain how they nevertheless take on particular shapes and implications—that is, their content can become determinate—depending on context, social meaning, and structural power relations. (If, for example, a perceived authority figure, such as a politician, parent, or scientist, encourages you to believe that your uncomfortable gut feeling is a justified fear of other social groups, then that is what your gut feeling is likely to become.). (shrink)

In Instrumental Variables (IV) estimation, the effect of an instrument on an endogenous variable may vary across the sample. In this case, IV produces a local average treatment effect (LATE), and if monotonicity does not hold, then no effect of interest is identified. In this paper, I calculate the weighted average of treatment effects that is identified under general first-stage effect heterogeneity, which is generally not the average treatment effect among those affected by the instrument. I then describe a simple (...) set of data-driven approaches to modeling variation in the effect of the instrument. These approaches identify a Super-Local Average Treatment Effect (SLATE) that weights treatment effects by the corresponding instrument effect more heavily than LATE. Even when first-stage heterogeneity is poorly modeled, these approaches considerably reduce the impact of small-sample bias compared to standard IV and unbiased weak-instrument IV methods, and can also make results more robust to violations of monotonicity. In application to a published study with a strong instrument, the preferred approach reduces error by about 19% in small (N ≈ 1, 000) subsamples, and by about 13% in larger (N ≈ 33, 000) subsamples. (shrink)

This article centres on two distinct but intersecting questions: does it matter if we cannot definitively answer the question ‘what is philosophy?’ and do philosophers exhibit bias? The article will answer ‘yes’ to both questions for the following reasons. First because the uncertainty has allowed some answers to dominate. Second, because the answers necessarily demonstrate biases, and these have led to a lack of diversity in the discipline. Following this, the article will consider why philosophers have been slow or (...) reluctant to accept that bias plays a role in what we do. This lack of recognition has, I suggest, limited opportunity for diverse approaches, methods, and standpoints to flourish. The discipline has suffered as a result, and so too have diverse philosophers. Many fields in science, technology, engineering and mathematics meanwhile have sought to tackle the lack of diversity head on, and philosophers would do well to heed their examples. (shrink)

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

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

We argue that abduction does not work in isolation from other inference mechanisms and illustrate this through an inference scheme designed to evaluate multiple hypotheses. We use game theory to relate the abductive system to actions that produce new information. To enable evaluation of the implications of this approach we have implemented the procedures used to calculate the impact of new information in a computer model. Experiments with this model display a number of features of collective belief-revision leading to consensus-formation, (...) such as the influence of bias and prejudice. The scheme of inferential calculations invokes a Peircian concept of ‘belief’ as the propensity to choose a particular course of action. (shrink)

Implicit bias is one of the most successful cases in recent memory of an academic concept being translated into practice. Its use in the National Science Foundation ADVANCE program—which seeks to promote gender equality in STEM careers through institutional transformation—has raised fundamental questions about organizational change. How do advocates translate theories into practice? What makes some concepts more tractable than others? What happens to theories through this translation process? We explore these questions using the ADVANCE program as a case (...) study. Using an inductive, theory-building approach and combination of computational and qualitative methods, we investigate how the concept of implicit bias was translated into practice through the ADVANCE program and identify five key features that made implicit bias useful as a change framework in the academic STEM setting. We find that the concept of implicit bias works programmatically because it is demonstrable, relatable, versatile, actionable, and impartial. While enabling the concept’s diffusion, these characteristics also limit its scope. We reflect on implications for gender theories of organizational change and for practitioners. (shrink)