Subconscious Bias Research Articles

Unmasking the Subconscious Fallacies Within Critical Infrastructure Protection

Cybersecurity, a vital challenge in today’s ever-changing digital world, it has gained prominence with the global shift towards cyber-enabled critical infrastructures. Critical infrastructure protection efforts are fundamental for the continuation of essential services. Traditionally constituted as separate sectors, these infrastructures are increasingly interconnected, leading to potential domino effects during security breaches. For instance, failures within the power grid could have cascading effects on multiple sectors that depend on electricity for their operations, creating large-scale failures that affect functions on which society depends. The multidimensional nature of the infrastructures presents complex challenges for solutions, given their status as long-established legacy systems needing further development and enhancements to withstand the digital world. The lack of a concerted and focused infrastructure enhancement strategy has led to incremental approaches versus a comprehensive revamp to ensure a holistic cyber protection program. A lack of national focus has created inconsistencies that can lead to potentially catastrophic consequences. Understanding the decision-making processes within a complex environment is critical to the mission success. One significant risk is the cognitive roadblocks that have the potential to influence one’s judgements as this often outweighs balanced decisions. This study aims to investigate the subconscious biases that arise from a perceived resolution of the problem which can lead to de-prioritization within the decision-making processes. The study employs a convergent parallel mixed methods design to collect and analyse the data. The study then will compare the results allowing for the exploration of various aspects of the research. This approach is aligned to provide a thorough understanding of the challenges associated with protecting the infrastructures and the underlying subconscious fallacies in the digital age, thereby devising effective mitigation strategies, and fostering a more sustainable and resilient critical infrastructure that is useful for a variety of stakeholders, including policymakers, infrastructure owners and operators, cybersecurity professionals, and researchers

Satisficing in Dentistry. Who decides? Who benefits? Part 3

This series of articles challenges some popular myths about supposedly ‘ideal’ treatment plans and is designed to provoke reflection and stimulate debate. It explains the concept of ‘satisficing’ (as opposed to ‘maximizing’) in dentistry, and illustrates how subconscious bias and self-interests might lead supposed experts to promote arbitrary aspirational standards and confuse them with what the law expects (the Bolam Test standard) and what is genuinely in the best interests of an individual patient. It is argued that sound, patient-centred, pragmatic planning and treatment is equally valid, with wider applicability, than routinely defaulting to a self-serving ‘maximalist’ approach. CPD/Clinical Relevance: The ‘satisficing ‘concept has wide and profound application across many fields of clinical (and non-clinical) dentistry.

Developing Racially Ambiguous Job Candidate Avatars with Strong versus Ambiguous Job Candidate Backgrounds in Preparation for a Field Experiment for Enhancing Inclusive Hiring and Reducing Implicit Bias

This study explores the utilization of generative Artificial Intelligence (AI) to create racially ambiguous avatars for job candidate interviews, aiming to enhance inclusive hiring practices and reduce implicit bias. With diversity recognized for boosting organizational performance, addressing hiring discrimination becomes crucial. This research investigates how avatars can anonymize candidates’ racial identities, potentially transforming “blind” hiring to minimize subconscious biases. Through an iterative pilot process engaging 30 female experienced-in-hiring participants with information technology backgrounds, the avatars representing White, Asian, and race-neutral candidate females, and corresponding candidate job descriptions, were refined, setting the foundation for a follow-up field experiment. This experiment will examine avatars’ effects on hiring recommendations and decisions by managers, manipulating strong versus ambiguous candidate qualifications, contributing insights into overcoming implicit biases. The initial pilot findings here suggest promising directions for technology’s role in fostering equitable recruitment, providing a groundwork for future studies on technology-enhanced inclusive hiring strategies.

Satisficing in dentistry. Who decides? who benefits? part 2

This three-part series of articles challenges some popular myths about supposedly ‘ideal’ treatment plans and is designed to provoke reflection and stimulate debate. It explains the concept of ‘satisficing’, as opposed to ‘maximizing’, in dentistry, and illustrates how subconscious bias and self-interests might lead supposed experts to promote arbitrary aspirational standards and confuse them with what the law expects (the Bolam Test standard), and what is genuinely in the best interests of an individual patient. It is argued that sound, patient-centred pragmatic planning and treatment is equally valid, with wider applicability than routinely defaulting to a self-serving ‘maximalist’ approach. CPD/Clinical Relevance: The ‘satisficing’ concept has wide and profound application across many fields of dentistry.

‘Satisficing’ in dentistry: who decides? who benefits?

This series of articles challenges some popular myths about supposedly ‘ideal’ treatment plans, and is designed to provoke reflection and stimulate debate. It explains the concept of ‘satisficing’ (as opposed to ‘maximizing’) in dentistry, and illustrates how subconscious bias and self-interests might lead supposed experts to promote arbitrary aspirational standards and confuse them with what the law expects (the Bolam Test standard) and what is genuinely in the best interests of an individual patient. It is argued that sound, patient-centred pragmatic planning and treatment is equally valid, with wider applicability than routinely defaulting to a self-serving ‘maximalist’ approach, often on spurious grounds. CPD/Clinical Relevance: The ‘satisficing’ concept has wide and profound application across many fields of dentistry; this first part explains the basic principles and how and why it is relevant to various aspects of practical dentistry and also to our understanding of professionalism.

P25 TB or not TB? An unusual case of inflammatory arthritis in an anti-CCP positive patient

P25 TB or not TB? An unusual case of inflammatory arthritis in an anti-CCP positive patient

Exploring the utility of eye tracking for sociological research on race.

One part of the social construction of race is the symbolic association of given physical features with different races. This research note explores the utility of eye tracking for sociological research on racial perception, that is, for determining what race someone 'looks like.' Results reveal that participants gave greatest attention to targets' hair. This was especially so when targets of all races had straight hair or when a target identified as Black/White mixed-race. The mixed-race results in particular provide physiological evidence of the theory of multiracial dissection. We conclude by suggesting that eye tracking can be useful to sociologists by revealing subconscious tendencies and biases which, once identified, can be consciously addressed in service to reducing social disparities.

Deliberators’ Awareness of Attitude Transformation

The significance of deliberators’ awareness of attitude transformation can be derived directly from deliberative democracy theory, but the issue has received little attention in research. This paper is an attempt to synthesize literature on factors influencing this awareness into a heuristic that can guide further inquiry. Conceptualizing learning as a fundamental mechanism through which attitudes are influenced during deliberation, either consciously or subconsciously, this heuristic stipulates that the level of awareness of any transformation is enhanced by overt persuasion in accordance with communicative rationality, and lowered, first, by various subconscious biases prompted in dialogue settings, and, second, by certain forms of calculated manipulation of deliberators. For illustrative purposes, the paper also presents a few more tangible, if tentative, observations from two small Swedish citizen dialogues that exemplify how design of deliberation may interact with factors influencing awareness of attitude transformation in real-life settings. More specifically, the observations suggest that ‘hot’ dialogues addressing well-defined and conflictual policy choices may favor awareness, while ‘colder’ consensus-oriented dialogues on broader issues might make participants less aware.

Machine learning to predict curative multidisciplinary team treatment decisions in oesophageal cancer

BackgroundRising workflow pressures within the oesophageal cancer (OC) multidisciplinary team (MDT) can lead to variability in decision-making, and health inequality. Machine learning (ML) offers a potential automated data-driven approach to address inconsistency and standardize care. The aim of this experimental pilot study was to develop ML models able to predict curative OC MDT treatment decisions and determine the relative importance of underlying decision-critical variables. MethodsRetrospective complete-case analysis of oesophagectomy patients ± neoadjuvant chemotherapy (NACT) or chemoradiotherapy (NACRT) between 2010 and 2020. Established ML algorithms (Multinomial Logistic regression (MLR), Random Forests (RF), Extreme Gradient Boosting (XGB)) and Decision Tree (DT) were used to train models predicting OC MDT treatment decisions: surgery (S), NACT + S or NACRT + S. Performance metrics included Area Under the Curve (AUC), Accuracy, Kappa, LogLoss, F1 and Precision -Recall AUC. Variable importance was calculated for each model. ResultsWe identified 399 cases with a male-to-female ratio of 3.6:1 and median age of 66.1yrs (range 32–83). MLR outperformed RF, XGB and DT across performance metrics (mean AUC of 0.793 [±0.045] vs 0.757 [±0.068], 0.740 [±0.042], and 0.709 [±0.021] respectively). Variable importance analysis identified age as a major factor in the decision to offer surgery alone or NACT + S across models (p < 0.05). ConclusionsML techniques can use limited feature-sets to predict curative UGI MDT treatment decisions. Explainable Artificial Intelligence methods provide insight into decision-critical variables, highlighting underlying subconscious biases in cancer care decision-making. Such models may allow prioritization of caseload, improve efficiency, and offer data-driven decision-assistance to MDTs in the future.

A Review of The Neurological Basis of Maladaptation

In Freudian terms, stupidity is a defense mechanism which keeps culturally forbidden desires at a subconscious level. It is bad enough that the mechanism for informing us about our envi- ronment is disrupted, but stupidity also isolates us from ourselves. All we are likely to know about our society and ourselves is that which is culturally acceptable. Consequently, much conscious knowledge is only obliquely related to a restricted reality, being limited by subconscious biases and thus often irrelevant to the solution of existing problems.

Multimodal assessment of effects of urban environments on psychological wellbeing

The built environment is a ubiquitous factor of modern human life, which fundamentally affects human wellbeing. Most existing research on the psychological effects of urban environments is predominantly based on subjective self-report measures, which provide valuable insights into subjective experiences, but are also affected by conscious and subconscious bias. In the current study, we evaluate a multimodal approach to capturing wellbeing by employing objective mobile physiological and neurophysiological measurement technologies alongside self-reports to capture the impact of two different urban environments. Moreover, we endeavoured to comprehensively measure and, when possible, control the physical aspects of the environment. Our study specifically aimed to discover differences between psychological wellbeing indicators in adults across low-density vs. moderate-density urban environments. Data collection took place in two urban outdoor locations in Australia. Statistical comparison of the two locations indicated that low urban density led to comparatively higher levels of psychological wellbeing compared to moderate urban density. Self-reports indicated that the low-density environment led to higher levels of subjective feelings of comfort and safety and reduced levels of negative mood. In line with the subjective reports, in the low-density environment compared to the moderate-density environment, individuals showed higher levels of EEG theta activity, while EEG beta and heart rate measures were lower. The research outcome provides insights into how urban density affects people's wellbeing and showcases the benefits of employing ecologically-valid multimodal psychological-environmental measurement approaches to effectively evaluate the psychological impacts of built environments.

Falling Prey to Bias? The Influence of Advisors on the Manifestation of Cognitive Biases in the Pre-M&amp;A Phase of Organizations

Our study demonstrates that the pre-M&amp;A phase provides breeding ground for irrational behavior in the form of cognitive biases. These biases not only arise within acquiring and acquired firms, but M&amp;A advisors themselves are also prone to effort-saving techniques and subconscious biases, which may be reflected in the client’s M&amp;A decision-making process. Cognitive biases stem from the contractual client–advisor relationship that elicits time pressure, standardization, and emotionality—that is, circumstances that favor the employment of effort-saving techniques. These biases lead to complex decisions based on the selective collection, framing and evaluation of data, the overestimation of one’s rationality, ability and deal likelihood, the illusion of control, and one-sided views. Such a biased evaluation of information is likely to induce the selection of a non-optimal target or acquirer or simply forcing a deal that should not be made in the first place. Hence, these cognitive biases can be seen as a source for consequent M&amp;A failure. With the identification of cognitive biases and bias-fostering circumstances, our study allows for awareness and consequent mitigation of such blind spots, thereby improving decision-making processes in the pre-M&amp;A phase via the introduction of “debiasing” strategies and the creation of favorable conditions for rational reasoning.

Examining the Effectiveness of Gender Equity Initiatives to Support Women in Engineering

Globally, women are a minority in the engineering profession. Various initiatives are adopted by employers to support women’s career progression and retention in the profession. This paper examines the effectiveness of the common initiatives. Focus groups were conducted with 25 New Zealand based female engineers to explore their experiences and perceptions of women in engineering initiatives. Women discussed the effectiveness, and unintended consequences, of the initiatives. Their responses were coded using the NVivo software to identify key themes, which were then categorized using the universal/selective/indicated model. The findings show that universal initiatives which encompass men and women are well supported with few unintended consequences. These initiatives (e.g., subconscious bias training) focus less on changing or supporting women and more on changing the environment. In contrast, selective initiatives (e.g., female leadership programs) which focus on women, had mixed support and more unintended consequences. Specifically, they emphasize societal stereotypes that men are a better fit for the role of engineer and that women need help to adapt to the male-dominated environment. This study concludes with recommendations for employers to implement that will increase the participation and advancement of women in engineering.

Confirmation Bias in Our Opinions on Social Media: A Qualitative Approach

Personal opinions are shaped by several factors, such as social, political, and economic issues. Subconscious bias is caused by factors such as the socioeconomic environment in which a person was raised, information gleaned from a network of friends, acquaintances, co-workers, as well as information from all other information sources. Confirmation bias is the propensity to look for evidence that supports one's preconceived notions rather than contradicts them. Due to its pressure on influencing personal opinions, confirmation bias has recently come back into focus as a topic of discussion, and social media today seems to have the biggest impact on the creation of confirmation bias in personal opinions on a variety of issues. Owing to social media's immense fame and popularity today, it has turned into a source of confirmation bias. Therefore, what are the factors that contribute to confirmation bias in our opinions on social media? How does confirmation bias shape our opinions on social media? A semi-structured interview was conducted with six (6) informants to seek answers to what and how confirmation bias shapes our opinions on social media. This study produced four themes, which are education level, algorithm, conformity, and self-control. Briefly, social media does shape confirmation bias in internet users' personal opinions. Finally, the current study has a limitation in that it only looks at social media, personal opinions, and confirmation bias.

A Machine Learning approach to identifying key decision variables within the Oesophageal Cancer MDT

Background: The drivers behind the Upper Gastrointestinal (UGI) multidisciplinary team (MDT) treatment decisions are not always explicit. National guidelines steer these decisions however human decision-making is vulnerable to subconscious biases. Machine-Learning (ML) may let us uncover these potential biases using simple, explainable AI solutions. This study is the first application of ML which examines decision-making within the oesophageal cancer (OC) MDT.

Talent management errors in recruiting - Case study approach

The fundamental goal of every organization is to provide quality products and services, be a pioneer in the corporate market, and achieve maximum customer satisfaction. The current concern pertains to how organizations can effectively implement these goals within a practical working environment. This study focuses on improving quality in the recruitment process by highlighting means and mediums that contribute to biased or faulty recruitment, resulting in the loss of best-fit candidates. Faulty or biased recruitment mainly refers to the conscious and subconscious biases exhibited by recruiters toward the candidates. This descriptive study is based on a real case study, employing the observation method of data collection to shed light on the issues caused by recruitment biases within an organization. The study also demonstrates a set of key factors that cause faulty recruitment and suggests possible solutions. The findings elaborate that faulty recruitment is due to cognitive biases, unstructured interview methods, and human errors. The recommendations show further precautions to be considered to avoid biases in the recruitment process.

Barriers to Citizen Science and Dissemination of Knowledge in Healthcare

Citizen science goes by many names, especially when citizen science is applied to healthcare and biomedicine: There are patient researchers, patient-driven innovators, lead users, quantified self-trackers, and more. Citizen science in healthcare goes beyond data collection; citizen scientists themselves perform many stages of science and research all the way through to dissemination of their work. They may find themselves facing barriers similar to those facing traditional academic researchers in academic publishing; however, these challenges are exacerbated by the very nature of citizen science, which is often individually driven and unfunded. Additional barriers in dissemination, such as structural barriers of journal publication systems, conscious and subconscious biases of editors and reviewers, the financial and time costs associated with dissemination, and more, can challenge citizen scientists. Some of the barriers are concrete while others are perceived but may be no less challenging. This essay highlights the barriers of citizen science work in healthcare, with special attention to the challenges of dissemination, including those experienced by a citizen scientist who has been addressing these challenges for nearly a decade. I provide three potential strategies with relevant examples for addressing some of the dissemination challenges, and provide additional dissemination advice—and encouragement—for citizen scientists in biomedicine and healthcare.

Is There Gender Bias in Radiology Job Postings?

BackgroundWords can convey subtle cultural stereotypes and perpetuate subconscious gender biases. Wording in job advertisements that appeals to 1 gender and deters others may unintentionally skew the applicant pool and affect the early phase of the recruitment process. “Masculine” tone can lead to decreased interest among women applicants while ‘feminine’ wording may not affect a man's decision to apply for the job. In this study, we evaluated the presence and extent of subtle gender bias in job advertisements for radiology faculty positions. MethodsAll job postings for faculty radiologists were retrieved from the American College of Radiology Career Center website in July 2020. The complete job advertisement was analyzed using Gender Decoder, a publicly available web-based application, to determine number and percentage of female or male coded words and the overall tone of the ad. The job posts were also stratified by subspecialty, leadership positions and academic versus private practice environments. ResultsOf the 623 job postings reviewed, a little over half (52.0%) of job postings were feminine coded, 26.6% had a masculine tone and 21.3% had a neutral tone. Of the leadership (division director) positions, 50.0% (4/8) had a masculine tone, 37.5% had a feminine tone, and 12.5% had a neutral tone. Among various specialties, pediatric radiology had the lowest percentage of job posts with a masculine tone (10.5%) while nuclear medicine had the highest percentage (41.7%). The most commonly used feminine words were: “support,” “responsible,” “commitment” and the most common masculine words were: “competitive,” “leader,” “active.” ConclusionsMost of the imaging job advertisements were feminine coded, with masculine tone in overall 26.6% posts and neutral tone in about a fifth. Leadership posts had a higher percentage of masculine tone. Awareness of these biases is important to enable diversity in recruitment and to ensure a diverse applicant pool.

Putting a Social and Cultural Framework on the Evidence Act

What follows are presentations to a seminar on the Supreme Court decision in Deng v Zheng (2022): guidance on bringing relevant social and cultural information to the court’s attention. The case concerned whether, despite a lack of formal documentation, the parties had entered into a legal partnership, of which they would be jointly responsible for the debts of the partnership. Two issues arose relating to the culture of the parties: namely, whether the meaning to be ascribed to 公司 (gingsi) went beyond ‘company’ and could extend to ‘firm’ or ‘enterprise’ and the significance of 关系 (guanxi). Both parties are Chinese and their business relationship appeared to have been conducted in Mandarin. Justice Goddard was the presiding judge in Zheng v Deng (2020), the Court of Appeal judgment appealed to the Supreme Court. Mai Chen appeared with two other lawyers on behalf of the intervenor, the New Zealand Law Society.&#x0D; Keywords: social and cultural framework; Evidence Act; expert evidence; translations; interpreters; adjudicative facts; social facts; legislative facts; stereotyping; subconscious bias; judicial notice; reliable published documents.

A framework for analyst economic incentives and cognitive biases: Origination of the walk-down in earnings forecasts

This paper discusses potential mechanisms for a walk-down pattern in analysts’ earnings forecasts attributable to economic incentives signalling favour from managers. We put forward that impression management tactics exploiting analysts’ subconscious cognitive biases influence judgements and forecasting processes. Hence, we suggest a framework addressing the interplay of analysts’ economic incentives and subconscious cognitive biases yielding forecast walk-downs. This paper is an important step toward enhancing the understanding of how forecasting processes are subject to subconscious cognitive biases and explicit incentives to please managers. Finally, we provide signposts for future research using experimental settings on the interplay of analysts’ incentives and cognitive biases, helping unpack the biases at play