Need For Fairness Research Articles

Advancements in MELD score and its impact in Hepatology.

There continues to be an ongoing need for fair and equitable organ allocation. The Model for End-stage Liver Disease (MELD) score has evolved as a calculated framework to evaluate and allocate patients for liver transplantation objectively. The original MELD score has undergone multiple modifications as it is continuously scrutinized for its accuracy in objectively representing the clinical context of patients with liver disease. Several refinements and iterations of the score have been developed, including the widely accepted MELD-Na score. In addition, the most recent updated iteration, MELD 3.0, has been created. The MELD 3.0 calculator incorporates new variables such as patient sex and serum albumin levels and assigns new weights for serum sodium, bilirubin, international normalized ratio, and creatinine levels. It is anticipated that the use of MELD 3.0 scores will reduce overall waitlist mortality and enhance access for female liver transplant candidates. However, despite the emergence of the MELD score as one of the most objective measures for fair organ allocation, various countries and healthcare systems employ alternative methods for stratification and organ allocation. This review article highlights the origins of the MELD score, its iterations, the current MELD 3.0, and future directions for managing liver transplantation organ allocation.

Investigating the Fairness of Deep Learning Models in Breast Cancer Diagnosis Based on Race and Ethnicity

Breast cancer is the leading cancer affecting women globally. Despite deep learning models making significant strides in diagnosing and treating this disease, ensuring fair outcomes across diverse populations presents a challenge, particularly when certain demographic groups are underrepresented in training datasets. Addressing the fairness of AI models across varied demographic backgrounds is crucial. This study analyzes demographic representation within the publicly accessible Emory Breast Imaging Dataset (EMBED), which includes de-identified mammography and clinical data. We spotlight the data disparities among racial and ethnic groups and assess the biases in mammography image classification models trained on this dataset, specifically ResNet-50 and Swin Transformer V2. Our evaluation of classification accuracies across these groups reveals significant variations in model performance, highlighting concerns regarding the fairness of AI diagnostic tools. This paper emphasizes the imperative need for fairness in AI and suggests directions for future research aimed at increasing the inclusiveness and dependability of these technologies in healthcare settings. Code is available at: https://github.com/kuanhuang0624/EMBEDFairModels.

Patient privacy and the need for private consultation areas in Kuwait’s polyclinic pharmacies

Abstract Introduction In Kuwait, pharmacists provide essential medication counseling and education. However, the open layout of polyclinic pharmacies often compromises patient privacy, deterring individuals from seeking necessary consultations. Objective This study aims to assess how patients perceive the level of privacy in Kuwait’s polyclinic pharmacies and evaluate patients’ need for a private consultation area. Method A cross-sectional study was conducted among patients at polyclinic pharmacies in Kuwait. Convenience sampling was used to select the polyclinics. Patients were approached after collecting their medications and invited to participate in the study. Those who consented completed a questionnaire that included sections on demographics, six items assessing the privacy construct, four items evaluating the need for a consultation area, and an open-ended question for additional comments. Ethical approval was obtained from the Human Ethical Committee, Health Sciences Center, Kuwait University. Results The study included 210 participants, with a majority residing in the Capital Governorate (55.2%), and being female (70%). The median age was 43 years old (IQR=29-55). Over two-thirds of the participants held a university degree (69%). Most participants were collecting medication for themselves (83.8%), and were exempt from fees (84.3%). When measuring patients’ privacy satisfaction, a score was calculated and a scale was divided into good to excellent (24 - 30), fair (18 - 23), and poor (6 -17). In addition, when measuring the need for a private consultation area score, a scale was divided into high need (16-20), fair need (12-15), and no need (4-11). Regarding perceived privacy, only 20% of participants had a good to excellent score, while 41.9% had a fair score and 38.1% had a poor score. When asked about the need for a private consultation room, 63.8% expressed a high need, while 15.2% believed it was unnecessary. Participants who had lower privacy scores reported a higher need for private consultation areas. Discussion The findings provide valuable insights into patient perspectives and highlight the necessity of improving pharmacy practices in Kuwait. Enhancing privacy in pharmacies could significantly improve the public’s perception of pharmacists as essential healthcare providers. However, several limitations should be noted. The sample is not representative of the population, as the proportion of non-Kuwaiti participants is less than the actual population ratio. Consequently, the results cannot be generalized to the entire population. Future studies should aim for a more representative sample and consider a longer data collection period to address these limitations. Conclusion The results of this study reveal that a significant number of patients perceive privacy in Kuwait's polyclinic pharmacies as fair, with many expressing a strong need for private consultation areas. These findings underscore the importance of enhancing privacy measures in these settings1. Implementing private consultation rooms in polyclinic pharmacies could greatly improve patient satisfaction and the overall quality of healthcare services provided by pharmacists. Reference 1. Waheedi S, Marshall V, Alharbia H, Farris KB. Patients’ perceptions of privacy and the need for a private consultation area in community pharmacy. Poster Abstracts. International Journal of Pharmacy Practice. 2016;24:33–60

A Systematic Literature Review on Transparency in Executive Remuneration Disclosures and Their Determinants

There are ongoing debates globally regarding excessive executive compensation, the perceived weak link between pay and performance, and the widening inequality gap. The South African corporate governance code King IV’s Principle 14 addresses the need for fair, responsible, and transparent remuneration. At the same time, the newly enacted Companies Amendment Act No. 16 of 2024 in South Africa emphasizes transparency in compensation, shareholder voting, and responding to shareholder feedback. This study conducts a systematic literature review of 30 articles on the transparency of executive remuneration disclosures and their determinants by analyzing Scopus-indexed articles published between 2010 and 2023, selected through specific keyword searches. The findings suggest an increasing focus on research regarding the disclosure of executive compensation, predominantly conducted in the Global North and primarily framed through agency theory. Studies exploring the factors influencing executive remuneration and the relationship between pay and performance are prevalent, with mixed results generally indicating a positive connection. Firm size emerges as a key factor in transparency, and many studies employ binary scoring to evaluate whether executive compensation disclosure is present. This paper provides valuable insights for investors, analysts, and policymakers and adds to the current understanding of executive remuneration transparency.

Multiple fairness criteria in decision tree learning

The use of algorithmic decision-making systems based on machine learning models has led to a need for fair (unbiased) and explainable classification outcomes. In particular, machine learning algorithms can encode biases, which might result in discriminatory decisions for certain groups such as gender, race, or age. Although a number of works on decision tree learning have been proposed to decrease the chance of discrimination, they usually focus on the use of a single fairness metric. In general, creating a model based on a single fairness metric is not a sufficient way to mitigate discrimination since bias can originate from various sources—e.g., the data itself or the optimization process. In this paper, we propose a novel decision tree learning process that utilizes multiple fairness metrics to address both group and individual discrimination. This is achieved by extending the attribute selection procedure to consider not only information gain but also gain in fairness. Computational experiments on fourteen different datasets with various sensitive features demonstrate that the proposed Fair-C4.5 models improve fairness without a loss in predictive accuracy when compared to the well-known C4.5 and the fairness-aware FFTree algorithms.

Poligami dalam Perspektif Filsafat Hukum Islam

Polygamy, a reality embedded in the teachings of the Koran, teaches that its implementation should not be done carelessly. Not just following lust, health considerations and material capacity, but more than that, polygamy must be accompanied by the intention to seek happiness in this world and the hereafter according to Islamic law. In certain contexts, polygamy can be an effective solution to resolve challenges in family life. However, its implementation must take into account various factors according to the situation and conditions of the individual who wishes to carry it out. Polygamy laws vary according to circumstances, emphasizing the need for fairness at every step. Research regarding Islamic legal philosophy in concrete situations of polygamy needs to be carried out. The results of this research describe the understanding of partners in Wonoasih Village, Wonoasih District, Probolinggo City regarding the principles of justice in polygamous marriages according to Islamic legal philosophy. This is a positive step in strengthening the basis of public understanding of the philosophical principles of Islamic law in the realm of polygamous marriages.

Fashion Design Classification Based on Machine Learning and Deep Learning Algorithms: A Review

Integration of machine learning algorithms in fashion design classification brought transformational change by allowing the automated analysis, categorization, and prediction of fashion items based on different attributes of the item. This paper reviews the state-of-the-art in fashion design classification through machine learning techniques. Review of literature, methodology, and challenges in this area indicate that an array of algorithms and methods, stretching from traditional machine learning algorithms to convolutional neural networks and further to transfer learning approaches, is being tried and tested. In this paper, I will discuss performance comparison among several machine learning algorithms, pinning their strengths, limitations, and possible applications in the fashion industry. We further elaborate on crucial challenges, such as touching on the issue of data variability, interpretability, and others on ethical consideration issues, all pointing to the need for fairness and sustainability with respect to the representation of reality in algorithmic decision-making. This paper aims to inform researchers, practitioners, and stakeholders of the opportunities and challenges brought about by the use of machine learning in a fast-paced world like fashion, hence demystifying current directions in landscape classification of fashion design.

Legalization of Community Organizations in Indonesia from the Perspective of Legal Protection: A Problematic Legal Choice

The research examines the legalization of community organizations in Indonesia, focusing on Law Number 17 of 2013. Using legal dogmatic research, the study finds that while legalizing community organizations provides greater legal certainty and protection, it also leads to issues like leadership dualism and internal conflicts due to differing views on legal status. Additionally, the law's digital registration system offers efficiency but causes conflicts over data validity as it lacks field verification. The findings highlight the need for fair, inclusive mechanisms to ensure equal participation in community development for all legally registered organizations.

Technological Transformation of Work: Navigating Automation Technologies and Skill Evolution on Employment

The relentless march of technology is fundamentally reshaping the world of work, with a profound impact on job roles across all industries. This paper delves into the multifaceted influence of technology on job design, encompassing automation, skill requirements, job creation, and ethical considerations. It examines the rise of automation and its potential for job displacement, highlighting the challenges faced by workers in adapting to these changes. The paper further analyses how technology is transforming existing job roles and the emergence of new skillsets critical for success in the digital era. It emphasizes the importance of upskilling and reskilling to ensure job sustainability. Additionally, the paper explores the potential for technology to create new job opportunities and foster innovation and entrepreneurship. Furthermore, it addresses the ethical considerations surrounding technology-driven job roles, emphasizing the need for fairness, transparency, and data privacy. Finally, the paper analyses the future outlook of technology's role in job design and the challenges in balancing automation with human workforce integration.

Ethics in international HRD: examining conversational AI and HR chatbots

PurposeThe integration of artificial intelligence (AI) technologies like conversational AI and HR chatbots in international human resource development (HRD) presents both productivity benefits and ethical challenges. This study aims to examine the ethical dimensions of AI-driven HR chatbots, emphasizing the need for fairness, autonomy and nondiscrimination. It discusses inherent biases in AI systems and addresses linguistic, cultural and accessibility issues. The paper advocates for a comprehensive risk assessment approach to guide ethical integration, proposing a “risk management by design” framework. By embracing ethical principles and robust risk management strategies, organizations can navigate AI-driven HR technologies while upholding fairness and equity in global workforce management.Design/methodology/approachSystematic literature review.FindingsThe paper advocates for a comprehensive risk assessment approach to guide ethical integration, proposing a “risk management by design” framework.Practical implicationsBy embracing ethical principles and robust risk management strategies, organizations can navigate AI-driven HR technologies while upholding fairness and equity in global workforce management.Originality/valueThis study explores the intricate ethical landscape surrounding AI-driven HR chatbots, spotlighting the imperatives of fairness, autonomy, and nondiscrimination. Uncovering biases inherent in AI systems, it addresses linguistic, cultural, and accessibility concerns. Proposing a pioneering “risk management by design” framework, the study advocates for a holistic approach to ethical integration, ensuring organizations navigate the complexities of AI-driven HR technologies while prioritizing fairness and equity in global workforce management.

Towards Fairness in Online Service with K Servers and Its Application on Fair Food Delivery

The k-SERVER problem is one of the most prominent problems in online algorithms with several variants and extensions. However, simplifying assumptions like instantaneous server movements and zero service time has hitherto limited its applicability to real-world problems. In this paper, we introduce a realistic generalization of k-SERVER without such assumptions – the k-FOOD problem, where requests with source-destination locations and an associated pickup time window arrive in an online fashion, and each has to be served by exactly one of the available k servers. The k-FOOD problem offers the versatility to model a variety of real-world use cases such as food delivery, ride sharing, and quick commerce. Moreover, motivated by the need for fairness in online platforms, we introduce the FAIR k-FOOD problem with the max-min objective. We establish that both k-FOOD and FAIR k-FOOD problems are strongly NP-hard and develop an optimal offline algorithm that arises naturally from a time-expanded flow network. Subsequently, we propose an online algorithm DOC4FOOD involving virtual movements of servers to the nearest request location. Experiments on a real-world food-delivery dataset, alongside synthetic datasets, establish the efficacy of the proposed algorithm against state-of-the-art fair food delivery algorithms.

The decisive role of the principles of administrative procedure in ensuring effective regulation of administrative acts

This article reveals the importance of the principles of administrative procedure in regulating the process of adoption of administrative acts. The article provides an in-depth analysis of how adherence to these principles is essential to promoting fairness, transparency, and accountability in government decision-making.
 Thearticle aims to provide an understanding of the principles of administrative law, emphasizing their application in regulating administrative procedures for fair and efficient public administration.
 The article highlights the impact of administrative acts on individuals and organizations, emphasizing the need for fair and accountable governance. The article examines the basic principles underlying administrative procedures, including due process, legality, fairness, and impartiality. Highlighting their importance, the article illustrates how these principles act as vital checks and balances, protecting citizens' rights and preventing abuse of power.
 In addition, the article sheds light on the positive effects of transparent and accessible administrative procedures. By promoting public participation and engagement, it highlights the potential for greater collaboration between government and its constituents. The introduction of these principles not only strengthens the legitimacy of administrative acts, but also contributes to the formation of citizens' sense of ownership and responsibility.
 The language of the article strikes a balance between legal rigor and accessibility, making it relevant for policymakers, legal practitioners, and the general public alike. Advocating for the integration and implementation of administrative- procedural principles, the author emphasizes their importance in improving the quality of management and strengthening democratic values.
 Overall, this article is informative for those who seek to understand the indispensable role of principles of administrative procedure in creating a fair, transparent and accountable administrative system. Through his persuasive arguments and comprehensive analysis, he encourages a wider commitment to these principles, ultimately strengthening administrative processes and regulation.

Fairness-oriented multicast routing for distributed interactive applications

Facing the challenges of network services on the edge, such as routing considering Quality of Service, is a crucial issue for current networking research efforts. Multicast routing is an essential technique for delivering routing services at a high level of optimization from the perspective of operators and application providers when there are user groups. Furthermore, routing that considers latency constraints has obstacles when it comes to merging different conditions in the solution, particularly when there is a need for fairness in the users’ communication. This work addresses this fairness requirement in multicasting, showing an efficient solution to increase the balance in routing by choosing better options for fair group interaction.

Vaping in mental health inpatient units: A qualitative study of consumer and staff views on electronic nicotine delivery systems.

The aim of this qualitative study was to explore the subjective experiences of consumers and staff members regarding the availability of electronic nicotine delivery systems (ENDS) in inpatient mental health units. Mental health consumers and staff members (n = 16) from rehabilitation and forensic inpatient units were interviewed in 2022. Thematic analysis of the transcripts was undertaken. Our study identified four themes: The high salience of nicotine use in inpatient units, delivering nicotine in a resource scarce environment, weighing up the harms of ENDS as a smoking cessation tool, and a need for fair and consistent policy. The main positive aspects identified were recognition of rights of consumers, a relative harm reduction compared to tobacco use, and ENDS as a positive factor in the therapeutic relationship. The main challenges identified were resourcing issues, ENDS being a potential source of tension and conflict and a lack of overarching policy guiding their use.

Blind to the perils of pursuing food: Behaviors of individuals with Smith-Magenis Syndrome

PurposeDiscrepancies exist between the need to lock food away and satiety scores in the Smith-Magenis syndrome (SMS) population. This study sought to uncover food-related behaviors within this unique group of individuals. MethodsCaregivers (N = 24) representing 21 individuals with SMS, recruited from the Parents and Researchers Interested in SMS national meeting and social media platforms, participated in semistructured interviews. Interviews were digitally recorded, transcribed verbatim, coded, and analyzed using hybrid thematic analysis. ResultsThis study identified a global theme of “Blind to the perils while pursuing their goals,” supported by 5 organizing themes: (1) Biology-impacting behaviors, (2) Need for personalized strategies, (3) Controlling food experiences, (4) Need for parents to orchestrate life, and (5) Surprising resourcefulness. Subthemes within these organizing themes highlighted that individuals with SMS have unique food-related behaviors and often fixate on certain types of foods. Their constant obsession with food for many of them is driven by hunger, obsessive characteristics, a need for autonomy, and a need for fairness. Caregivers must put multiple guardrails in place and remain constantly vigilant to prevent overeating in these individuals. ConclusionIndividuals with SMS often perseverate on food and display unique food-related behaviors. Treating obesity in this population is likely to be ineffective without multicomponent, individualized strategies. Additionally, research in this population will likely require targeted instruments for the SMS population to more clearly define the underlying etiologies and to track changes over time in therapeutic trials.

Ethical Implications of Discriminatory Economic Policies of the Nigerian Government

Ideally, the government of any nation is in a contract with the citizens for protection of life, property and freedom while the citizens are obliged to obey government laws. Moreso, the government is to discharge her duties without discriminating against any person or group. In Nigeria there are economic and administrative policies that discriminate against the Igbo nation resulting in dire consequences. Since economic policies make or mar the wellbeing of citizens especially in business, the need for fairness, equity, and justice in the formulation and execution of policies is unquestionable. The Igbo of South East Nigeria, who are very active in business and entrepreneurship, suffer untold disadvantages and massive economic losses due to the lopsided and discriminatory economic policies churned out by successive Nigerian governments. Here we examine and argue against such policies based on their ethical implications and effects on individual and national development.

Generative Artificial Intelligence: Implications and Considerations for Higher Education Practice

Generative Artificial Intelligence (GAI) has emerged as a transformative force in higher education, offering both challenges and opportunities. This paper explores the multifaceted impact of GAI on academic work, with a focus on student life and, in particular, the implications for international students. While GAI, exemplified by models like ChatGPT, has the potential to revolutionize education, concerns about academic integrity have arisen, leading to debates on the use of AI detection tools. This essay highlights the difficulties in reliably detecting AI-generated content, raising concerns about potential false accusations against students. It also discusses biases within AI models, emphasizing the need for fairness and equity in AI-based assessments with a particular emphasis on the disproportionate impact of GAI on international students, who already face biases and discrimination. It also highlights the potential for AI to mitigate some of these challenges by providing language support and accessibility features. Finally, this essay acknowledges the disruptive potential of GAI in higher education and calls for a balanced approach that addresses both the challenges and opportunities it presents by emphasizing the importance of AI literacy and ethical considerations in adopting AI technologies to ensure equitable access and positive outcomes for all students. We offer a coda to Ng et al.’s AI competency framework, mapped to the Revised Bloom’s Taxonomy, through a lens of cultural competence with AI as a means of supporting educators to use these tools equitably in their teaching.

Genetic and Genomic Researchers' Perspectives on Biological Sample Sharing in Collaborative Research in Uganda: A Qualitative Study.

Numerous ethical, legal, and social issues arise with biological sample sharing. The study explored the perspectives of genetic and genomic researchers on the sharing of biological samples in international collaborative research. Qualitative in-depth interviews were conducted with 15 researchers. Participants expressed positive attitudes towards biobanking and appreciated the benefits of cross-border sharing of biological samples but noted that this practice had adversely affected local capacity building efforts. There was limited understanding of the ethical and regulatory frameworks governing sample sharing. Researchers emphasized the importance of respecting cultural values in biobanking research. Issues concerning poor governance and inequitable benefit sharing were also raised. There is a need for fair and equitable international collaborations where all researchers are treated with respect and as equal partners.

Connecting ethics and epistemology of AI

The need for fair and just AI is often related to the possibility of understanding AI itself, in other words, of turning an opaque box into a glass box, as inspectable as possible. Transparency and explainability, however, pertain to the technical domain and to philosophy of science, thus leaving the ethics and epistemology of AI largely disconnected. To remedy this, we propose an integrated approach premised on the idea that a glass-box epistemology should explicitly consider how to incorporate values and other normative considerations, such as intersectoral vulnerabilities, at critical stages of the whole process from design and implementation to use and assessment. To connect ethics and epistemology of AI, we perform a double shift of focus. First, we move from trusting the output of an AI system to trusting the process that leads to the outcome. Second, we move from expert assessment to more inclusive assessment strategies, aiming to facilitate expert and non-expert assessment. Together, these two moves yield a framework usable for experts and non-experts when they inquire into relevant epistemological and ethical aspects of AI systems. We dub our framework ‘epistemology-cum-ethics’ to signal the equal importance of both aspects. We develop it from the vantage point of the designers: how to create the conditions to internalize values into the whole process of design, implementation, use, and assessment of an AI system, in which values (epistemic and non-epistemic) are explicitly considered at each stage and inspectable by every salient actor involved at any moment.

Regional energy futures as decision support in the transition to net zero emissions: North of Tyne case study

ABSTRACT Futures studies can fulfil a variety of purposes; for informing policy, developing investment or business strategies, and changing perceptions of what the future may hold. Futures can therefore be described as having transformative potential. This paper uses a participatory scenario approach to develop regional energy futures for a U.K. case study in the North of Tyne region. Two sets of futures are developed; pre-pandemic, and during the pandemic. This was for insights into the challenges for developing subnational scale futures, and how futures thinking may have been impacted by the pandemic. The North of Tyne energy future scenarios are based on discussions in two facilitated stakeholder workshops, pre and during the pandemic. It was found that the pandemic had resulted in shifts in practices and behaviours such as increased home working, and an appreciation of local environments and communities. However, there were commonalities too. In both settings, decarbonisation was a strong driver for change in the energy system, as was the need for fairness in the transition. There were barriers in futures thinking that had to be overcome, most notably was the presumption that meeting the net zero target was a certainty. This presented difficulties in imagining futures that didn’t achieve this target or did so but more slowly. The importance of being able to imagine living in all kinds of future worlds will be critical in a system undergoing such profound change so that strategic foresight is developed to minimise risks of missing the net zero target.