Rahman Amri, Mahyuddin Reza, Nurhilaliyah Nurhilaliyah
et al.
The present study aims to describe the integration of religious values in sports activities and their impact on the physical fitness and mental health of students. The research was conducted at the Faculty of Sports Science and Health, University of Makassar, using a mixed methods sequential explanatory design, where quantitative analysis was conducted first and then reinforced with qualitative data. The sample comprised 32 students who were selected using purposive sampling based on their involvement in sports activities. Quantitative instruments included a religious value integration questionnaire, a physical fitness questionnaire (self-perception), and a mental health questionnaire. The qualitative instruments employed included interview guidelines for students and lecturers/coaches, observation sheets for sports activities, and documentation. The findings of the quantitative analysis demonstrated that the integration of religious values was in the highest category. The physical fitness of students is in the high to very high category. With respect to mental health, 16 students (50%) are in the very high category, 11 students (34.37%) are in the high category, and 5 students (15.63%) are in the moderate category. The qualitative stage of analysis is undertaken with a view to offering a more in-depth exploration of the quantitative findings, with students and lecturers placing particular emphasis on the assertion that sports should be regarded as a means of internalising religious, moral and spiritual values, rather than merely physical activities. The following practical examples are provided for consideration: group prayers prior to and following training, sportsmanship, cooperation, emotional control, and the application of dress code ethics in accordance with religious teachings. Nevertheless, deficiencies were identified in time management and spiritual reflection following training. The present study concludes that the integration of religious values in sports has a positive effect on students' physical fitness and mental health. The challenges experienced by coaches are frequently attributable to external factors, including competitive pressures, technical constraints related to clothing, and variations in coaches' understanding.
Purpose – This study explores how service quality and Sharia governance directly influence customer loyalty in Islamic banking. It moves beyond procedural interpretations of Sharia compliance by examining how operational performance and institutional religiosity jointly shape long-term customer commitments.
Methodology – An explanatory sequential mixed-method design was employed. In the quantitative phase, data were collected from 213 customers of the Bank Syariah Indonesia (BSI) in Jambi Province, Indonesia. The sample was selected using cluster random sampling, in which two of the three existing BSI branches were randomly chosen, and all customers from the selected branches participated as respondents. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The qualitative phase followed an Interpretative Phenomenological Analysis (IPA) involving in-depth interviews with four long-term loyal customers to uncover the emotional, spiritual, and value-based dimensions underpinning their loyalty.
Findings – Both service quality and Sharia governance significantly and directly affect customer loyalty, with Sharia governance exerting a stronger influence. The qualitative findings revealed four key loyalty-building patterns: spiritualized service experience, trust in Sharia supervisory structures, emotional connection with Islamic digital platforms, and personalized service grounded in ethics.
Implications – For Islamic banks, fostering loyalty requires more than efficient service delivery and demands visible Sharia credibility and alignment with customers’ religious values and expectations.
Originality – Departing from previous studies that examined operational or governance factors in isolation, this study integrates service quality and Sharia governance as parallel, mutually reinforcing drivers of customer loyalty. The developed loyalty framework captures the multidimensional interplay between faith, ethical congruence, and service experience in Muslim-majority banking context.
Wiebke Hutiri, Mircea Cimpoi, Morgan Scheuerman
et al.
Dataset transparency is a key enabler of responsible AI, but insights into multimodal dataset attributes that impact trustworthy and ethical aspects of AI applications remain scarce and are difficult to compare across datasets. To address this challenge, we introduce Trustworthy and Ethical Dataset Indicators (TEDI) that facilitate the systematic, empirical analysis of dataset documentation. TEDI encompasses 143 fine-grained indicators that characterize trustworthy and ethical attributes of multimodal datasets and their collection processes. The indicators are framed to extract verifiable information from dataset documentation. Using TEDI, we manually annotated and analyzed over 100 multimodal datasets that include human voices. We further annotated data sourcing, size, and modality details to gain insights into the factors that shape trustworthy and ethical dimensions across datasets. We find that only a select few datasets have documented attributes and practices pertaining to consent, privacy, and harmful content indicators. The extent to which these and other ethical indicators are addressed varies based on the data collection method, with documentation of datasets collected via crowdsourced and direct collection approaches being more likely to mention them. Scraping dominates scale at the cost of ethical indicators, but is not the only viable collection method. Our approach and empirical insights contribute to increasing dataset transparency along trustworthy and ethical dimensions and pave the way for automating the tedious task of extracting information from dataset documentation in future.
This paper introduces a checks-and-balances framework for ethical alignment of Large Language Models (LLMs), inspired by three-branch governmental systems. It implements three independent yet interacting components: LLMs as the executive branch for knowledge generation, DIKE as the legislative branch establishing ethical guardrails, and ERIS as the judicial branch for contextual interpretation. Beyond structural separation, we address a fundamental challenge: regulating emotion to shape behaviors. Drawing from psychological theories where managing emotional responses prevents harmful behaviors, we develop a self-supervised learning pipeline that maps emotions to linguistic behaviors, enabling precise behavioral modulation through emotional conditioning. By integrating this approach with adversarial testing, our framework demonstrates how DIKE and ERIS direct linguistic behaviors toward ethical outcomes while preserving independence throughout knowledge generation, ethical oversight, and contextual interpretation.
Calibrated trust in automated systems (Lee and See 2004) is critical for their safe and seamless integration into society. Users should only rely on a system recommendation when it is actually correct and reject it when it is factually wrong. One requirement to achieve this goal is an accurate trustworthiness assessment, ensuring that the user's perception of the system's trustworthiness aligns with its actual trustworthiness, allowing users to make informed decisions about the extent to which they can rely on the system (Schlicker et al. 2022). We propose six design guidelines to help designers optimize for accurate trustworthiness assessments, thus fostering ethical and responsible human-automation interactions. The proposed guidelines are derived from existing literature in various fields, such as human-computer interaction, cognitive psychology, automation research, user-experience design, and ethics. We are incorporating key principles from the field of pragmatics, specifically the cultivation of common ground (H. H. Clark 1996) and Gricean communication maxims (Grice 1975). These principles are essential for the design of automated systems because the user's perception of the system's trustworthiness is shaped by both environmental contexts, such as organizational culture or societal norms, and by situational context, including the specific circumstances or scenarios in which the interaction occurs (Hoff and Bashir 2015). Our proposed guidelines provide actionable insights for designers to create automated systems that make relevant trustworthiness cues available. This would ideally foster calibrated trust and more satisfactory, productive, and safe interactions between humans and automated systems. Furthermore, the proposed heuristics might work as a tool for evaluating to what extent existing systems enable users to accurately assess a system's trustworthiness.
Marianne Leineweber, Clara Victoria Keusgen, Marc Bubeck
et al.
Background: The use of social robotics in elderly care is increasingly discussed as one way of meeting emerging care needs due to scarce resources. While many potential benefits are associated with robotic care technologies, there is a variety of ethical challenges. To support steps towards a responsible implementation and use, this review develops an overview on ethical aspects of the use of social robots in elderly care from a decision-makers' perspective. Methods: Electronic databases were queried using a comprehensive search strategy based on the key concepts of "ethical aspects", "social robotics" and "elderly care". Abstract and title screening was conducted by two authors independently. Full-text screening was conducted by one author following a joint consolidation phase. Data was extracted using MAXQDA24 by one author, based on a consolidated coding framework. Analysis was performed through modified qualitative content analysis. Results: A total of 1,518 publications were screened, and 248 publications were included. We have organized our analysis in a scheme of ethical hazards, ethical opportunities and unsettled questions, identifying at least 60 broad ethical aspects affecting three different stakeholder groups. While some ethical issues are well-known and broadly discussed our analysis shows a plethora of potentially relevant aspects, often only marginally recognized, that are worthy of consideration from a practical perspective. Discussion: The findings highlight the need for a contextual and detailed evaluation of implementation scenarios. To make use of the vast knowledge of the ethical discourse, we hypothesize that decision-makers need to understand the specific nature of this discourse to be able to engage in careful ethical deliberation.
Saeid Jamshidi, Kawser Wazed Nafi, Arghavan Moradi Dakhel
et al.
The rapid advancement and adaptability of Large Language Models (LLMs) highlight the need for moral consistency, the capacity to maintain ethically coherent reasoning across varied contexts. Existing alignment frameworks, structured approaches designed to align model behavior with human ethical and social norms, often rely on static datasets and post-hoc evaluations, offering limited insight into how ethical reasoning may evolve across different contexts or temporal scales. This study presents the Moral Consistency Pipeline (MoCoP), a dataset-free, closed-loop framework for continuously evaluating and interpreting the moral stability of LLMs. MoCoP combines three supporting layers: (i) lexical integrity analysis, (ii) semantic risk estimation, and (iii) reasoning-based judgment modeling within a self-sustaining architecture that autonomously generates, evaluates, and refines ethical scenarios without external supervision. Our empirical results on GPT-4-Turbo and DeepSeek suggest that MoCoP effectively captures longitudinal ethical behavior, revealing a strong inverse relationship between ethical and toxicity dimensions (correlation rET = -0.81, p value less than 0.001) and a near-zero association with response latency (correlation rEL approximately equal to 0). These findings demonstrate that moral coherence and linguistic safety tend to emerge as stable and interpretable characteristics of model behavior rather than short-term fluctuations. Furthermore, by reframing ethical evaluation as a dynamic, model-agnostic form of moral introspection, MoCoP offers a reproducible foundation for scalable, continuous auditing and advances the study of computational morality in autonomous AI systems.
Clotilde Brayé, Aurélien Bricout, Arnaud Gotlieb
et al.
Medical Intelligent Systems (MIS) are increasingly integrated into healthcare workflows, offering significant benefits but also raising critical safety and ethical concerns. According to the European Union AI Act, most MIS will be classified as high-risk systems, requiring a formal risk management process to ensure compliance with the ethical requirements of trustworthy AI. In this context, we focus on risk reduction optimization problems, which aim to reduce risks with ethical considerations by finding the best balanced assignment of risk assessment values according to their coverage of trustworthy AI ethical requirements. We formalize this problem as a constrained optimization task and investigate three resolution paradigms: Mixed Integer Programming (MIP), Satisfiability (SAT), and Constraint Programming(CP).Our contributions include the mathematical formulation of this optimization problem, its modeling with the Minizinc constraint modeling language, and a comparative experimental study that analyzes the performance, expressiveness, and scalability of each approach to solving. From the identified limits of the methodology, we draw some perspectives of this work regarding the integration of the Minizinc model into a complete trustworthy AI ethical risk management process for MIS.
This paper establishes a formal framework, grounded in mathematical logic and order theory, to analyze the inherent limitations of radical transparency. We demonstrate that self-referential disclosure policies inevitably encounter fixed-point phenomena and diagonalization barriers, imposing fundamental trade-offs between openness and stability. Key results include: (i) an impossibility theorem showing no sufficiently expressive system can define a total, consistent transparency predicate for its own statements; (ii) a categorical fixed-point argument (Lawvere) for the inevitability of self-referential equilibria; (iii) order-theoretic design theorems (Knaster-Tarski) proving extremal fixed points exist and that the least fixed point minimizes a formal ethical risk functional; (iv) a construction for consistent partial transparency using Kripkean truth; (v) an analysis of self-endorsement hazards via Löb's Theorem; (vi) a recursion-theoretic exploitation theorem (Kleene) formalizing Goodhart's Law under full disclosure; (vii) an exploration of non-classical logics for circumventing classical paradoxes; and (viii) a modal $μ$-calculus formulation for safety invariants under iterative disclosure. Our analysis provides a mathematical foundation for transparency design, proving that optimal policies are necessarily partial and must balance accountability against strategic gaming and paradox. We conclude with equilibrium analysis and lattice-theoretic optimality conditions, offering a principled calculus for ethical disclosure in complex systems.
Angel Mary John, Aiswarya M. U., Jerrin Thomas Panachakel
Artificial intelligence (AI) has emerged as a ubiquitous concept in numerous domains, including the legal system. AI has the potential to revolutionize the functioning of the judiciary and the dispensation of justice. Incorporating AI into the legal system offers the prospect of enhancing decision-making for judges, lawyers, and legal professionals, while concurrently providing the public with more streamlined, efficient, and cost-effective services. The integration of AI into the legal landscape offers manifold benefits, encompassing tasks such as document review, legal research, contract analysis, case prediction, and decision-making. By automating laborious and error-prone procedures, AI has the capacity to alleviate the burden associated with these arduous tasks. Consequently, courts around the world have begun embracing AI technology as a means to enhance the administration of justice. However, alongside its potential advantages, the use of AI in the judiciary poses a range of ethical challenges. These ethical quandaries must be duly addressed to ensure the responsible and equitable deployment of AI systems. This article delineates the principal ethical challenges entailed in employing AI within the judiciary and provides recommendations to effectively address these issues.
Lalu Muhammad Zainul Ihsan, Abdul Rasyid Ridho, Mohd. Sham Kamis
This study discusses the interpretation uffin in the Qur'an as a form of sarcasm in response to the decline of morality ethics in social interaction between people or generations. The type of research used is analytical descriptive research with a qualitative approach, because it is a method used to analyze the contents of the message conveyed by the verses mentioned the word uffin in it based on the interpretation of ulama. The results found that the word uffin was used in different contexts, both as a prohibition on hurting parents, as an expression of anger and disapproval, and the uffin words as denial to God, parents and those who give religious advice or the message of kindness to others. According to the ulama interpretation, uffin expresses dissatisfaction, anger, even insult, which is considered linguistically rude or full of annoyance. These results provide insight into how the word uffin is used as sarcasm in social interaction. The implications of this research emphasize the need to understand the context of the use of sarcasm in everyday life and to develop the right attitude in responding to it, in order to maintain ethical and moral harmony in social interactions.
The existence of the environment is of paramount importance to all Africans. For an African the environment is a conglomeration of the physical made up of the air, water, human beings, animals, rocks, hills, mountains; the socio-cultural which comprises ethics, economic, aesthetics, and the spiritual which embodies the Supreme Being (creator), the deities, shrines, spirits among others. This goes to explain that for an African the world is not dichotomized but seen as a whole and so all exist to complement the other. In Nigeria, there are some experiences that are fighting against the environment which is the embodiment of the above-mentioned components thereby generating environmental crisis through flooding, erosion, desertification, pollution, climate change among others. All these forces destabilize the harmony that keeps the balance of the ecosystem. The aim of this paper is to bring out some environmental challenges African Traditional Religion proffers solution to so as to set a balance in the eco system. When the environment is in harmony with life will be better, to some extent, for all Nigerians. The study was carried out in Nigeria. The data was collected through interviews and analyzed by adopting the qualitative approach. The findings of this paper indicate that through the existence of sacred grooves, customary laws and environmental ethics like respect for rivers and streams as abode of the spirits and goddesses, totems, reverence for sacred lands, African Traditional Religion protects the environment from degeneration. The paper recommends that African Traditional Religious adherents and traditional rulers should sensitize the younger generation on the need to protect environment and take note of the danger of the climate change red alert.
ABSTRACTAdults in the United States are having fewer biological children in part due to worries about climate change and population growth, yet Christian environmental ethicists frequently avoid or dismiss these “eco‐reproductive” concerns. I argue that these avoidances lead to important limitations in the literature, which I address by employing a pragmatic approach for religious ethics. Learning from environmentalists who are critically engaging with their Christian inheritances, I find that informants draw upon religious repertoires to “kinnovate.” Namely, they expand notions of family beyond biological lineage by taking up vocations as godparents, youth mentors, foster parents, or chosen kin. I claim that these practices of Christian kinnovation are significant because they help to advance creative moral responses to eco‐reproductive concerns in religious contexts—interventions that currently remain underdeveloped in relevant ethical and theological literatures.
Lauren Olson, Tom P. Humbert, Ricarda Anna-Lena Fischer
et al.
Many modern software applications present numerous ethical concerns due to conflicts between users' values and companies' priorities. Intersectional communities, those with multiple marginalized identities, are disproportionately affected by these ethical issues, leading to legal, financial, and reputational issues for software companies, as well as real-world harm for intersectional users. Historically, the voices of intersectional communities have been systematically marginalized and excluded from contributing their unique perspectives to software design, perpetuating software-related ethical concerns. This work aims to fill the gap in research on intersectional users' software-related perspectives and provide software practitioners with a starting point to address their ethical concerns. We aggregated and analyzed the intersectional users' ethical concerns over time and developed a prioritization method to identify critical concerns. To achieve this, we collected posts from over 700 intersectional subreddits discussing software applications, utilized deep learning to identify ethical concerns in these posts, and employed state-of-the-art techniques to analyze their content in relation to time and priority. Our findings revealed that intersectional communities report \textit{critical} complaints related to cyberbullying, inappropriate content, and discrimination, highlighting significant flaws in modern software, particularly for intersectional users. Based on these findings, we discuss how to better address the ethical concerns of intersectional users in software development.
The burgeoning landscape of text-to-image models, exemplified by innovations such as Midjourney and DALLE 3, has revolutionized content creation across diverse sectors. However, these advancements bring forth critical ethical concerns, particularly with the misuse of open-source models to generate content that violates societal norms. Addressing this, we introduce Ethical-Lens, a framework designed to facilitate the value-aligned usage of text-to-image tools without necessitating internal model revision. Ethical-Lens ensures value alignment in text-to-image models across toxicity and bias dimensions by refining user commands and rectifying model outputs. Systematic evaluation metrics, combining GPT4-V, HEIM, and FairFace scores, assess alignment capability. Our experiments reveal that Ethical-Lens enhances alignment capabilities to levels comparable with or superior to commercial models like DALLE 3, ensuring user-generated content adheres to ethical standards while maintaining image quality. This study indicates the potential of Ethical-Lens to ensure the sustainable development of open-source text-to-image tools and their beneficial integration into society. Our code is available at https://github.com/yuzhu-cai/Ethical-Lens.
The adoption of artificial intelligence (AI) in retail has significantly transformed the industry, enabling more personalized services and efficient operations. However, the rapid implementation of AI technologies raises ethical concerns, particularly regarding consumer privacy and fairness. This study aims to analyze the ethical challenges of AI applications in retail, explore ways retailers can implement AI technologies ethically while remaining competitive, and provide recommendations on ethical AI practices. A descriptive survey design was used to collect data from 300 respondents across major e-commerce platforms. Data were analyzed using descriptive statistics, including percentages and mean scores. Findings shows a high level of concerns among consumers regarding the amount of personal data collected by AI-driven retail applications, with many expressing a lack of trust in how their data is managed. Also, fairness is another major issue, as a majority believe AI systems do not treat consumers equally, raising concerns about algorithmic bias. It was also found that AI can enhance business competitiveness and efficiency without compromising ethical principles, such as data privacy and fairness. Data privacy and transparency were highlighted as critical areas where retailers need to focus their efforts, indicating a strong demand for stricter data protection protocols and ongoing scrutiny of AI systems. The study concludes that retailers must prioritize transparency, fairness, and data protection when deploying AI systems. The study recommends ensuring transparency in AI processes, conducting regular audits to address biases, incorporating consumer feedback in AI development, and emphasizing consumer data privacy.
This paper addresses the ethical challenges of Artificial Intelligence in Neural Machine Translation (NMT) systems, emphasizing the imperative for developers to ensure fairness and cultural sensitivity. We investigate the ethical competence of AI models in NMT, examining the Ethical considerations at each stage of NMT development, including data handling, privacy, data ownership, and consent. We identify and address ethical issues through empirical studies. These include employing Transformer models for Luganda-English translations and enhancing efficiency with sentence mini-batching. And complementary studies that refine data labeling techniques and fine-tune BERT and Longformer models for analyzing Luganda and English social media content. Our second approach is a literature review from databases such as Google Scholar and platforms like GitHub. Additionally, the paper probes the distribution of responsibility between AI systems and humans, underscoring the essential role of human oversight in upholding NMT ethical standards. Incorporating a biblical perspective, we discuss the societal impact of NMT and the broader ethical responsibilities of developers, positing them as stewards accountable for the societal repercussions of their creations.
Zhipeng Yin, Sribala Vidyadhari Chinta, Zichong Wang
et al.
The integration of AI in education holds immense potential for personalizing learning experiences and transforming instructional practices. However, AI systems can inadvertently encode and amplify biases present in educational data, leading to unfair or discriminatory outcomes. As researchers have sought to understand and mitigate these biases, a growing body of work has emerged examining fairness in educational AI. These studies, though expanding rapidly, remain fragmented due to differing assumptions, methodologies, and application contexts. Moreover, existing surveys either focus on algorithmic fairness without an educational setting or emphasize educational methods while overlooking fairness. To this end, this survey provides a comprehensive systematic review of algorithmic fairness within educational AI, explicitly bridging the gap between technical fairness research and educational applications. We integrate multiple dimensions, including bias sources, fairness definitions, mitigation strategies, evaluation resources, and ethical considerations, into a harmonized, education-centered framework. In addition, we explicitly examine practical challenges such as censored or partially observed learning outcomes and the persistent difficulty in quantifying and managing the trade-off between fairness and predictive utility, enhancing the applicability of fairness frameworks to real-world educational AI systems. Finally, we outline an emerging pathway toward fair AI-driven education and by situating these technologies and practical insights within broader educational and ethical contexts, this review establishes a comprehensive foundation for advancing fairness, accountability, and inclusivity in the field of AI education.
Ni Made Suarningsih, I Nyoman Suwija, I Ketut Suar Adnyana
et al.
Balinese society is affluent in oral literature, among which there are satua or Balinese folk tales. Recently, it has been felt that the Masatua tradition has declined dramatically. The increasingly busy level of parents causes this. Entertainment on social media has defeated oral traditions. This research aims to analyze the function and value of the Death of Kedis Cangak for Its Greedy. This study uses a qualitative method. The data collection method for this research is the observation method using reading and note-taking techniques. The research results were analyzed using analytical descriptive methods and presented using informal processes. The research analysis uses the matching process. The research results show that the functions of the "Death of Kedis Cangak for Its Greedy" unit are entertainment, educational, and social sanctions or punishment functions. Values analysis, which focuses on religious values, found values such as tattwa (philosophy) and moral values (ethics). There is an entertainment function, an educational function, and a social sanction or punishment function. Values such as tattwa (philosophy) and moral values (ethics) are found in value analysis, which focuses on religious matters. Regarding philosophical issues, we found the application of the karma phala law, one of the Panca Sradha teachings. The law of karma befalls the character I Kedis Cangak. The value of morals is also reflected in the behavior of the main character, which is contrary to the teachings of morals.
Cucu Sutianah, Meita Annisa Nurhutami, Alfian Azhar Yamin
Learning in vocational education must be carried out with collaboration between educators, vocational schools, curriculum alignment, and learning in factories as miniature industries stakeholders to achieve assessment in the form of real assessment so that the achievement of learning objectives follows the needs of students and the world of work. Assessment in the form of assessment must be measured in real terms, with religious, character, moral, and cultural education values and work competencies following community expectations. The objectives to be achieved through this research are to produce a learning program that can improve student competence in Vocational High School (VHS), including identifying the current condition of learning implementation, obtaining learning planning findings, obtaining learning implementation findings, obtaining findings regarding the assessment of learning outcomes, identifying supporting and inhibiting factors, knowing students' perceptions of the implementation of the BMC-based teaching and learning factory model in improving student competence in the concentration of leather and imitation craft design and production expertise in VHS. With the implementation of a learning system using a block system as a teaching and learning factory, the implementation of learning must stimulate students to be more active in improving social skills, emotional skills, spiritual skills, scientific skills, mental skills, kinesthetic skills, as well as entrepreneurial skills, work ethics and safety, and work safety and the environment, which in turn can improve the competence and entrepreneurial character of students, following the vision and mission of the education unit.