Alexander V. Shenderuk-Zhidkov, Alexander E. Hramov
This article introduces and substantiates the concept of Neuro-Linguistic Integration (NLI), a novel paradigm for human-technology interaction where Large Language Models (LLMs) act as a key semantic interface between raw neural data and their social application. We analyse the dual nature of LLMs in this role: as tools that augment human capabilities in communication, medicine, and education, and as sources of unprecedented ethical risks to mental autonomy and neurorights. By synthesizing insights from AI ethics, neuroethics, and the philosophy of technology, the article critiques the inherent limitations of LLMs as semantic mediators, highlighting core challenges such as the erosion of agency in translation, threats to mental integrity through precision semantic suggestion, and the emergence of a new `neuro-linguistic divide' as a form of biosemantic inequality. Moving beyond a critique of existing regulatory models (e.g., GDPR, EU AI Act), which fail to address the dynamic, meaning-making processes of NLI, we propose a foundational framework for proactive governance. This framework is built on the principles of Semantic Transparency, Mental Informed Consent, and Agency Preservation, supported by practical tools such as NLI-specific ethics sandboxes, bias-aware certification of LLMs, and legal recognition of the neuro-linguistic inference. The article argues for the development of a `second-order neuroethics,' focused not merely on neural data protection but on the ethics of AI-mediated semantic interpretation itself, thereby providing a crucial conceptual basis for steering the responsible development of neuro-digital ecosystems.
Ao transcender os limites biomédicos e/ou biotecnológicos, a bioética desponta como um espaço de discussão política para os dilemas morais da atualidade. Assim, estreitam-se os laços de uma bioética interventiva e politizada e uma educação libertadora, pautada na defesa dos direitos humanos universais, defendidos pelo brasileiro Paulo Freire. Este estudo, realizado a partir de uma revisão narrativa da literatura, tem a pretensão de ampliar o debate sobre o “como” e o “quanto” a presença da bioética no ensino secundário do Brasil pode se constituir como um diferencial importante na construção de uma educação para a liberdade. Conclui-se que o sucesso do ensino da bioética no Brasil, no nível secundário, dependerá da decisão ética do Estado e das comunidades escolares, diante da árdua tarefa de superar a “educação bancária” e se comprometer com o “cultivo das humanidades” dos adolescentes, aqui considerados protagonistas históricos de suas trajetórias acadêmicas e projetos de vida.
Medical philosophy. Medical ethics, Business ethics
Ahmed Mamdouh, Riham Adel, Nevien Khourshed
et al.
This study investigates the multiple impacts of digital leadership, including visionary leadership, digital citizenship, and systemic improvement, on employee performance in the Egyptian petrochemicals sector. Furthermore, it investigates the mediating roles of digital self-efficacy and employee motivation within these interactions. A quantitative methodology was employed, gathering data from 391 valid responses out of 700 issued questionnaires to sector employees, resulting in a 55.9% response rate. Data analysis was conducted using Structural Equation Modeling (SEM) with AMOS software. The model exhibited a superior fit (χ2/DF = 2.659, RMSEA = 0.059, TLI = 0.925, CFI = 0.934). Research indicates that digital leadership has a substantial impact on employee performance, employee motivation, and digital self-efficacy. Both employee motivation and digital self-efficacy were found to significantly partially mediate the relationships between various dimensions of digital leadership and employee performance. Digital leadership dimensions explained 44.3% of the variance in employee motivation, 24.2% of the variance in digital self-efficacy, and jointly (via mediators) represented 28.5% of the variance in employee performance. These results highlight the essential need to cultivate digital leadership skills and improve employee digital readiness and motivation to optimize performance in digitally evolving sectors such as the Egyptian petrochemicals industry. The study offers both theoretical and practical contributions by integrating digital leadership into the dynamic capabilities framework and providing empirical evidence from the Egyptian petrochemicals sector. The findings highlight digital leadership’s critical role in fostering adaptability, innovation, and employee performance, enabling organizations to thrive during digital transformation.
Harry Yulianto, Iryanti Iryanti, Amiruddin Amrullah
This study examines the integration of Islamic values in the business model of educational startup in Indonesia and how these values contribute to the sustainability and competitive position of these businesses in a highly competitive market. The issue addressed was the challenge faced by educational startup in balancing profit with social impact while adhering to Islamic principles, such as justice, transparency, and community benefit. The research positions itself as an exploration of how Islamic values can strengthen the business model of educational startup, making them not only financially viable but also socially responsible. The question was discussed by analyzing the operational and strategic implications of applying Islamic ethics in the education sector, with a focus on inclusivity, fairness, and sustainable business practices. Using a qualitative descriptive approach, the paper reviews relevant literature on Islamic business ethics and its application in educational startup. The findings indicate that integrating Islamic values enhances trust, customer loyalty, and long-term sustainability, while offering a unique competitive advantage in the market. The research concludes that adopting Islamic principles in business models offers a viable path for educational startup to create a positive social impact while ensuring business success in the evolving educational landscape.
Artem Artyukhov, Nadiia Artyukhova, Dmytro Chumachenko
et al.
In recent years, Open Science (OS) and Open Access (OA) have become integral to European research policy, driven by the need for greater transparency, accessibility, and collaboration in knowledge production. Despite growing support from the European Commission and other supranational actors, national-level implementation remains fragmented and uneven across the continent. This study aims to compare the development and enforcement of OS&OA policies across 29 European countries and to identify clusters of nations with similar policy profiles. To achieve this, 15 binary and ordinal indicators were compiled from public datasets and policy reports. Using hierarchical clustering based on Manhattan distance and Ward’s D2 linkage, countries were grouped into three distinct clusters. Supporting analyses included descriptive statistics, PCA, and radar plot visualisation. The results show a high clustering tendency (Hopkins H = 0.988) and reveal three meaningful groups: (1) countries with limited or symbolic engagement in OS&OA (e.g., Italy, Ireland); (2) moderate adopters with partial institutionalisation (e.g., France, Czech Republic); and (3) leaders with comprehensive, formalised frameworks (e.g., Netherlands, Germany, Spain). Cluster 3 countries fully include FAIR principles, citizen science, and national mandates, while Cluster 1 countries largely lack these advanced elements. These findings underline the structural disparities in OS&OA policy maturity across Europe and support tailored policy support, peer-learning initiatives, and regional alignment efforts within the European Research Area.
Model cards are the primary documentation framework for developers of artificial intelligence (AI) models to communicate critical information to their users. Those users are often developers themselves looking for relevant documentation to ensure that their AI systems comply with the ethical requirements of existing laws, guidelines, and standards. Recent studies indicate inadequate model documentation practices, suggesting a gap between AI requirements and current practices in model documentation. To understand this gap and provide actionable guidance to bridge it, we conducted a thematic analysis of 26 guidelines on ethics and AI, three AI documentation frameworks, three quantitative studies of model cards, and ten actual model cards. We identified a total of 43 ethical requirements relevant to model documentation and organized them into a taxonomy featuring four themes and twelve sub-themes representing ethical principles. Our findings indicate that model developers predominantly emphasize model capabilities and reliability in the documentation while overlooking other ethical aspects, such as explainability, user autonomy, and fairness. This underscores the need for enhanced support in documenting ethical AI considerations. Our taxonomy serves as a foundation for a revised model card framework that holistically addresses ethical AI requirements.
Agentic artificial intelligence systems are autonomous technologies capable of pursuing complex goals with minimal human oversight and are rapidly emerging as the next frontier in AI. While these systems promise major gains in productivity, they also raise new ethical challenges. Prior research has examined how different populations prioritize Responsible AI values, yet little is known about how practitioners actually reason through the trade-offs inherent in designing these autonomous systems. This paper investigates the ethical reasoning of AI practitioners through qualitative interviews centered on structured dilemmas in agentic AI deployment. We find that the responses of practitioners do not merely reflect value preferences but rather align with three distinct reasoning frameworks. First is a Customer-Centric framework where choices are justified by business interests, legality, and user autonomy. Second is a Design-Centric framework emphasizing technical safeguards and system constraints. Third is an Ethics-Centric framework prioritizing social good and moral responsibility beyond compliance. We argue that these frameworks offer distinct and necessary insights for navigating ethical trade-offs. Consequently, providers of agentic AI must look beyond general principles and actively manage how these diverse reasoning frameworks are represented in their decision-making processes to ensure robust ethical outcomes.
This paper develops a rigorous mathematical framework for egalitarian ethics by integrating formal tools from economics and mathematics. We motivate the formalism by investigating the limitations of conventional informal approaches by constructing examples such as probabilistic variant of the trolley dilemma and comparisons of unequal distributions. Our formal model, based on canonical welfare economics, simultaneously accounts for total utility and the distribution of outcomes. The analysis reveals deficiencies in traditional statistical measures and establishes impossibility theorems for rank-weighted approaches. We derive representation theorems that axiomatize key inequality measures including the Gini coefficient and a generalized Atkinson index, providing a coherent, axiomatic foundation for normative philosophy.
Abstract A consensus and buying pattern regarding luxury brands has endured a paradigm shift from being envied to being questioned or entirely overlooked. The pandemic has led to a fair share of economic implications. Brands are forced to watch their product range fully, except for reserving a portion of merchandise optimistic for brand jingoism. The study aims to quantify the impacts of financial metrics utilized to gain goodwill amidst an average consumer’s mindset. A composite Corporate Social Responsibility (CSR) score represents the extent of a luxury brand’s efforts in contributing to social and environmental concerns. The CSR score is hypothesized against these brands’ financial and brand-value metrics. A Few Research questions are proposed on the same. A Panel-level analysis is undertaken to quantify the dependence and obtain insights. Relevant data is collected, with metrics identified from financial statements. The impacts of financial metrics and the firm’s age on the CSR score are determined. While the Profit Margin, firm size, Tobin’s Q, and Firm Age contribute positively to the CSR score, the firm’s Return on Assets has a surprising negative influence. The impact of net income accrued is negligible, as inferred.
Social responsibility of business, Business ethics
Tetiana Dotsenko, Sebastian Jarzębowski, Kateryna Chepel
et al.
This study investigates the role of local IT companies in driving digital progress in Ukrainian communities, highlighting the critical relationship between IT companies’ business leadership and regional digital transformation. The relevance of this topic is particularly significant given Ukraine’s ongoing efforts to digitally transform its regions in the context of post-war recovery and economic rebuilding. Local IT companies are pivotal in fostering economic growth and bridging the digital divide by promoting innovation, infrastructure, and digital services, especially in underserved areas. The methodology used in this study involved the development of an econometric model to evaluate the correlation between two integral indices. The Digital Transformation Index integrally reflects the region’s overall progress on the digital transformation path (institutional capacity, Internet development, ASC development, paperless mode, digital education, regional business cards, penetration of basic services, and sectoral digital transformation). IT Business Leadership Index is proposed to be described in this study by the following indicators: the number of operating local IT companies, their employees and recruited employees, and the volume of products sold, produced and added by local IT companies. Regression, correlation, canonical analysis (to determine the interdependencies between sets of factors, to define the canonical roots of the studied indices), and factor analysis (to build an integral indicator of IT companies’ business leadership under the influence of digital transformation), were used to determine the statistical dependencies between these indicators. The data across Ukraine’s regions were gathered from official government sources, covering 2020‒2022. The findings revealed a strong correlation between active IT company leadership and higher levels of digital progress in regions like Kyiv and Kharkiv. These areas have advanced in implementing digital services such as e-governance and digital education platforms. However, disparities were observed, with regions like Zaporizhia and Donetsk lagging behind due to weaker IT infrastructure and limited access to skilled labor. The analysis highlighted that not all factors contributed equally, with variables like production costs showing weaker correlations. This suggests the need for targeted policies and investments to ensure equitable digital transformation across all regions. This study underscores the importance of strengthening local IT ecosystems. It suggests that a multifaceted approach – encompassing policy support, infrastructure development, and education – is essential for achieving widespread and sustainable digital progress in Ukraine.
Louis Chislett, Louis JM Aslett, Alisha R Davies
et al.
Clinical prediction models are statistical or machine learning models used to quantify the risk of a certain health outcome using patient data. These can then inform potential interventions on patients, causing an effect called performative prediction: predictions inform interventions which influence the outcome they were trying to predict, leading to a potential underestimation of risk in some patients if a model is updated on this data. One suggested resolution to this is the use of hold-out sets, in which a set of patients do not receive model derived risk scores, such that a model can be safely retrained. We present an overview of clinical and research ethics regarding potential implementation of hold-out sets for clinical prediction models in health settings. We focus on the ethical principles of beneficence, non-maleficence, autonomy and justice. We also discuss informed consent, clinical equipoise, and truth-telling. We present illustrative cases of potential hold-out set implementations and discuss statistical issues arising from different hold-out set sampling methods. We also discuss differences between hold-out sets and randomised control trials, in terms of ethics and statistical issues. Finally, we give practical recommendations for researchers interested in the use hold-out sets for clinical prediction models.
Lars Ackermann, Martin Käppel, Laura Marcus
et al.
The rapid development of cutting-edge technologies, the increasing volume of data and also the availability and processability of new types of data sources has led to a paradigm shift in data-based management and decision-making. Since business processes are at the core of organizational work, these developments heavily impact BPM as a crucial success factor for organizations. In view of this emerging potential, data-driven business process management has become a relevant and vibrant research area. Given the complexity and interdisciplinarity of the research field, this position paper therefore presents research insights regarding data-driven BPM.
Information visualization plays a key role in business intelligence analytics. With ever larger amounts of data that need to be interpreted, using the right visualizations is crucial in order to understand the underlying patterns and results obtained by analysis algorithms. Despite its importance, defining the right visualization is still a challenging task. Business users are rarely experts in information visualization, and they may not exactly know the most adequate visualization tools or patterns for their goals. Consequently, misinterpreted graphs and wrong results can be obtained, leading to missed opportunities and significant losses for companies. The main problem underneath is a lack of tools and methodologies that allow non-expert users to define their visualization and data analysis goals in business terms. In order to tackle this problem, we present an iterative goal-oriented approach based on the i* language for the automatic derivation of data visualizations. Our approach links non-expert user requirements to the data to be analyzed, choosing the most suited visualization techniques in a semi-automatic way. The great advantage of our proposal is that we provide non-expert users with the best suited visualizations according to their information needs and their data with little effort and without requiring expertise in information visualization.
Purpose – This article aims to review critical thinking (CT) as a future skill in business. Design/methodology/approach – The study employed two research methods: science mapping analysis based on bibliometric keyword co-occurrence data and systematic literature review following PRISMA guidelines. The application of two distinctive research methods meant that we could obtain a broad picture thematic overview as well as a detailed, fine-grained insight into the content of CT business research. Findings – Research in CT in business studies is dominated by themes related to education, university and learning that far outweigh CT business application, which focuses on three research axes. These are specific business functions (e.g. accounting, marketing, human resources and identifying business opportunities), certain skills used in business (e.g. decision-making and creativity) and other business-related topics (including ethics, stakeholder relations and individual employee performance). Practical implications – The article identifies new research gaps related to the link between CT and business performance, a firm’s ability to innovate and company characteristics. Moreover, the article highlights that CT positively influences business decision-making under the influence of cognitive biases and heuristics. Originality/value – The article provides the first literature review on CT in business research. It uses a novel method of science mapping analysis to show unbiased algorithmic-based insight into the structure of the research, followed by a systematic literature review.
The numerous deployed Artificial Intelligence systems need to be aligned with our ethical considerations. However, such ethical considerations might change as time passes: our society is not fixed, and our social mores evolve. This makes it difficult for these AI systems; in the Machine Ethics field especially, it has remained an under-studied challenge. In this paper, we present two algorithms, named QSOM and QDSOM, which are able to adapt to changes in the environment, and especially in the reward function, which represents the ethical considerations that we want these systems to be aligned with. They associate the well-known Q-Table to (Dynamic) Self-Organizing Maps to handle the continuous and multi-dimensional state and action spaces. We evaluate them on a use-case of multi-agent energy repartition within a small Smart Grid neighborhood, and prove their ability to adapt, and their higher performance compared to baseline Reinforcement Learning algorithms.
Hildegunn Mellesmo Aslaksen, Clare Hildebrandt, Hans Chr. Garmann Johnsen
Abstract This article adds to the discussion of the long-term transformation of CSR, presenting a perspective on the interplay between CSR debate and public discourse on business responsibility. 50 years after Milton Friedman’s provoking claim that the only responsibility for business is to seek profit, a broader debate has emerged aligning CSR with an increasingly comprehensive concept of sustainability. We trace this evolution of the concept during the last three decades focusing on the intersection of economic, social, and environmental responsibility. Based on discourse analysis of news articles and opinion pieces in the largest public newspaper in Norway from 1990 until 2018, the study confirms that discussions on CSR, sustainability and the social model often approach the same challenges. We argue that sustainability has become the dominating term in popular usage for describing the relationship between business and society. Based on our analysis of the public debate, CSR has become a more comprehensive term, transformed from being a term mainly related to internal business affairs to part of a broader societal discussion about sustainability.
Social responsibility of business, Business ethics
Lyon Salia Awuah, Kwame Oduro Amoako, Stephen Yeboah
et al.
Abstract This paper aims to explore the motivations and challenges of engaging host communities in CSR practices within the context of Newmont Ahafo Mines (NAM), a subsidiary of a Multinational Mining Enterprise (MNE) operating in Ghana’s mining sector. This paper draws insights from stakeholder theory and interviews conducted with internal stakeholders (management and employees) and stakeholders in host communities (traditional rulers and community members). The findings indicate that effective decision-making, gaining legitimacy, cost savings, management of risks, and accountability are some of the perceived motivations of NAM’s stakeholder engagement in CSR. Nonetheless, the most critical challenges to NAM in improving stakeholder engagement in CSR practices are the lack of community members’ support in CSR projects, communities’ high expectations of NAM on development projects and over-dependency on NAM on the part of host communities. Therefore, it is reasonable for MNEs in emerging economies to attune engagement practices to the host community’s context. This will enable CSR practices and policies to fully exploit the latent benefits of CSR in the mining sector.
Social responsibility of business, Business ethics
Is it possible to use natural language to intervene in a model's behavior and alter its prediction in a desired way? We investigate the effectiveness of natural language interventions for reading-comprehension systems, studying this in the context of social stereotypes. Specifically, we propose a new language understanding task, Linguistic Ethical Interventions (LEI), where the goal is to amend a question-answering (QA) model's unethical behavior by communicating context-specific principles of ethics and equity to it. To this end, we build upon recent methods for quantifying a system's social stereotypes, augmenting them with different kinds of ethical interventions and the desired model behavior under such interventions. Our zero-shot evaluation finds that even today's powerful neural language models are extremely poor ethical-advice takers, that is, they respond surprisingly little to ethical interventions even though these interventions are stated as simple sentences. Few-shot learning improves model behavior but remains far from the desired outcome, especially when evaluated for various types of generalization. Our new task thus poses a novel language understanding challenge for the community.
Islam is a comprehensive religion that covers not only the ritual worship aspect but also ethics and acts of business. The field of Islamic work ethics has been studied by many researchers in different study settings. However, the important role of Islamic work ethics has been underexplored in work commitment studies. Therefore, this study aims to examine the direct and indirect effect of Islamic work ethics in affecting employees work performance and turnover intention through work commitment. This study used the quantitative method as their main research design. Purposive sampling was applied as a sampling technique with a five-point Likert scale of the structured questionnaire as a measurement scale and data gathering method. The bootstrap method used to test the proposed hypotheses. This study concluded that Islamic work ethic positively affects work commitment, thus work commitment positively affects work performance. This study also found that there was an insignificant effect of Islamic work ethic on work performance and turnover intention, and work commitment on turnover intention. Fundamentally, the mediation role of work commitment failed to prove in this study as there were only significant indirect effects between Islamic work ethic and work performance. In other words, the higher individual beliefs on Islamic value, the more committed employee to do their job. Thus, the more committed and enthusiastic employees on their job, the higher their work performance will be.