Artificial Intelligence (AI) is transforming sectors such as healthcare, finance, and autonomous systems, offering powerful tools for innovation. Yet its rapid integration raises urgent ethical concerns related to data ownership, privacy, and systemic bias. Issues like opaque decision-making, misleading outputs, and unfair treatment in high-stakes domains underscore the need for transparent and accountable AI systems. This article addresses these challenges by proposing a modular ethical assessment framework built on ontological blocks of meaning-discrete, interpretable units that encode ethical principles such as fairness, accountability, and ownership. By integrating these blocks with FAIR (Findable, Accessible, Interoperable, Reusable) principles, the framework supports scalable, transparent, and legally aligned ethical evaluations, including compliance with the EU AI Act. Using a real-world use case in AI-powered investor profiling, the paper demonstrates how the framework enables dynamic, behavior-informed risk classification. The findings suggest that ontological blocks offer a promising path toward explainable and auditable AI ethics, though challenges remain in automation and probabilistic reasoning.
Large language models (LLMs) have been actively applied in the mental health field. Recent research shows the promise of LLMs in applying psychotherapy, especially motivational interviewing (MI). However, there is a lack of studies investigating how language models understand MI ethics. Given the risks that malicious actors can use language models to apply MI for unethical purposes, it is important to evaluate their capability of differentiating ethical and unethical MI practices. Thus, this study investigates the ethical awareness of LLMs in MI with multiple experiments. Our findings show that LLMs have a moderate to strong level of knowledge in MI. However, their ethical standards are not aligned with the MI spirit, as they generated unethical responses and performed poorly in detecting unethical responses. We proposed a Chain-of-Ethic prompt to mitigate those risks and improve safety. Finally, our proposed strategy effectively improved ethical MI response generation and detection performance. These findings highlight the need for safety evaluations and guidelines for building ethical LLM-powered psychotherapy.
We present an ethical decision-making framework that refines a pre-trained reinforcement learning (RL) model using a task-agnostic ethical layer. Following initial training, the RL model undergoes ethical fine-tuning, where human feedback is replaced by feedback generated from a large language model (LLM). The LLM embodies consequentialist, deontological, virtue, social justice, and care ethics as moral principles to assign belief values to recommended actions during ethical decision-making. An ethical layer aggregates belief scores from multiple LLM-derived moral perspectives using Belief Jensen-Shannon Divergence and Dempster-Shafer Theory into probability scores that also serve as the shaping reward, steering the agent toward choices that align with a balanced ethical framework. This integrated learning framework helps the RL agent navigate moral uncertainty in complex environments and enables it to make morally sound decisions across diverse tasks. Our approach, tested across different LLM variants and compared with other belief aggregation techniques, demonstrates improved consistency, adaptability, and reduced reliance on handcrafted ethical rewards. This method is especially effective in dynamic scenarios where ethical challenges arise unexpectedly, making it well-suited for real-world applications.
In the world of science new technology have opened up the possibility to rely on advanced computational methods and models to conduct and produce scientific research. An important aspect of scientific and business workflows is provenance - which refers to the information describing the production, history or lineage of an end product, which can also be data, digitalized processes and other not tangible artifacts. While there are already systems, tools and standards to capture provenance of data and workflows the provenance of adaptations/changes in workflows has not been addressed yet. In this paper we carry out a literature review to establish the state of the art on this topic and present our methodology and findings. Our findings confirm that provenance of adaptation has not been addressed adequately in the fields of business and scientific workflows. The two fields also have different motivation for recording the lineage of data or processes. While scientific workflows are interested in reproducibility and visualization, business workflows solutions are indirectly connected to compliance, exception handling and analysis. The adaptive nature of workflows in both fields is not reflected in the research on process provenance yet, as our results show. The use of standard provenance standards is also not wide spread.
Contemporary society, characterized by accelerated communications, intensive information exchange, and dynamic business processes, has induced a transformation of the business environment in recent decades. These transformations are reflected in the legislative framework, fundamental business principles, and ethical standards. The subject of this paper is the analysis of ethical aspects of business, with a particular focus on civil aviation as a strategically significant sector. Civil aviation, which emerged in the early 20th century, has experienced intensive expansion in the contemporary period, whereby ethical norms have become an indispensable condition for its sustainable development. Ethical business practices in this sector encompass legislative obligations, professional standards, and moral values, which manifest through the prioritization of safety, professional responsibility, transparency, and the protection of user rights. The international character of aviation, along with continuous oversight by regulatory bodies, underscores the necessity of strict adherence to ethical principles across all segments-from technical aircraft maintenance and personnel training to direct interactions with consumers. Particular importance is given to combating corruption and fostering a culture of trust, as human life, organizational reputation, and institutional legitimacy are directly linked to the ethical integrity of actors. Based on the Ethical Code as a key regulatory and value-based instrument, the primary paradigm of civil aviation business is respect for consumers and the pursuit of meeting their needs. Thus, ethics is positioned as a constitutive element of the safety and business system, confirming that the sustainability and success of civil aviation depend on the integration of legislative, professional, and ethical principles.
FELIPE FRÓES COUTO, ALEXANDRE DE PÁDUA CARRIERI, MÁRIO AQUINO ALVES
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Abstract How do discourses and practices of business ethics awards align, considering the plurality of ethical values and principles? To answer this question, we critically analyze the Brazilian empirical case “Pro-Ethics.” Pro-Ethics, a joint initiative led by the Brazilian Office of the Comptroller General (CGU) and Ethos Institute, is a symbolic action that promotes recognition of firms committed to preventing and combating corruption and that strive to make the corporate environment more integral, ethical, and transparent. We performed textual analysis through Fairclough’s critical discourse analysis. As a result, we identified that the national integrity and business ethics system was imported from big global economic nations without considering the local reality and the cultural and social particularities that permeate trust relationships in Brazil. We also identified a progressive emptying of ethical and moral meanings in human relations in the capitalist context and the substitution of its content to cost-benefit relationships. Our analysis brings two main contributions. First, it adds to the discussion on business ethics awards, a field that academia has not explored in Brazil and is underdeveloped worldwide, with very few papers focusing on this subject. Secondly, it questions business ethics management practices, demonstrating the instrumental nature of the subject.
Rebekah Rousi, Niko Makitalo, Hooman Samani
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The emergence of generative artificial intelligence (GAI) and large language models (LLMs) such ChatGPT has enabled the realization of long-harbored desires in software and robotic development. The technology however, has brought with it novel ethical challenges. These challenges are compounded by the application of LLMs in other machine learning systems, such as multi-robot systems. The objectives of the study were to examine novel ethical issues arising from the application of LLMs in multi-robot systems. Unfolding ethical issues in GPT agent behavior (deliberation of ethical concerns) was observed, and GPT output was compared with human experts. The article also advances a model for ethical development of multi-robot systems. A qualitative workshop-based method was employed in three workshops for the collection of ethical concerns: two human expert workshops (N=16 participants) and one GPT-agent-based workshop (N=7 agents; two teams of 6 agents plus one judge). Thematic analysis was used to analyze the qualitative data. The results reveal differences between the human-produced and GPT-based ethical concerns. Human experts placed greater emphasis on new themes related to deviance, data privacy, bias and unethical corporate conduct. GPT agents emphasized concerns present in existing AI ethics guidelines. The study contributes to a growing body of knowledge in context-specific AI ethics and GPT application. It demonstrates the gap between human expert thinking and LLM output, while emphasizing new ethical concerns emerging in novel technology.
This paper critically examines the ethical implications of integrating AI tools like GitHub Copilot and ChatGPT into the software development process. It explores issues such as code ownership, bias, accountability, privacy, and the potential impact on the job market. While these AI tools offer significant benefits in terms of productivity and efficiency, they also introduce complex ethical challenges. The paper argues that addressing these challenges is essential to ensuring that AI's integration into software development is both responsible and beneficial to society
This study explores the impact of spiritual intelligence (SI) on technostress, with a focus on the mediating role of the ethical environment. In an era where technological advancements continually reshape our work and personal lives, understanding the interplay between human intelligence, well-being, and ethics within organizations is increasingly significant. Spiritual intelligence, transcending traditional cognitive and emotional intelligences, emphasizes understanding personal meaning and values. This paper investigates how higher levels of SI enable individuals to integrate technology into their lives without undue stress, and how a robust ethical environment within organizations supports and amplifies these benefits. Through a comprehensive review of literature, empirical research, and detailed analysis, the study highlights the protective role of SI against technostress and the significant influence of an ethical climate in enhancing this effect. The findings offer valuable insights for organizational strategies aimed at promoting a harmonious, stress-free workplace environment.
Gerhard Zeisler, Tim Tobias Braunauer, Albert Fleischmann
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The widely adopted Business Process Model and Notation (BPMN) is a cornerstone of industry standards for business process modeling. However, its ambiguous execution semantics often result in inconsistent interpretations, depending on the software used for implementation. In response, the Process Specification Language (PASS) provides formally defined semantics to overcome these interpretational challenges. Despite its clear advantages, PASS has not reached the same level of industry penetration as BPMN. This feasibility study proposes using PASS as an intermediary framework to translate and execute BPMN models. It describes the development of a prototype translator that converts specific BPMN elements into a format compatible with PASS. These models are then transformed into source code and executed in a bespoke workflow environment, marking a departure from traditional BPMN implementations. Our findings suggest that integrating PASS enhances compatibility across different modeling and execution tools and offers a more robust methodology for implementing business processes across organizations. This study lays the groundwork for more accurate and unified business process model executions, potentially transforming industry standards for process modeling and execution.
We explore the nonlinear dynamics of a macroeconomic model with resource constraints. The dynamics is derived from a production function that considers capital and a generalized form of energy as inputs. Energy, the new variable, is depleted during the production process and has to be renewed, whereas capital grows with production and decreases from depreciation. Dependent on time scales and energy related control parameters, we obtain steady states of high or low production, but also sustained oscillations that show properties of business cycles. We also find conditions for the coexistence of stable fixed points and limit cycles. Our model allows to specify investment and saving functions for Kaldor's model of business cycles. We provide evidence for an endogenous origin of business cycles if depleting resources are taken into account.
The endeavor of interstellar exploration is a convergence of technical innovation and profound ethical inquiry, challenging humanity to extend its reach beyond the confines of our solar system while contemplating the moral implications of such a leap. This paper explores the multifaceted aspects of interstellar travel, exploring advancements in propulsion systems, habitat construction, and life support alongside the ethical, sociopolitical, and philosophical questions that arise as we consider colonizing extraterrestrial worlds. We underscore the imperative for an integrative framework harmonizing scientific achievements with a deep ethical commitment to responsible exploration, environmental stewardship, and respect for potential extraterrestrial life. Our analysis highlights the dual nature of interstellar exploration as both a technical endeavor and a philosophical journey, advocating for a future in which humanity's expansion into the cosmos is guided by foresight, equity, and the collective well-being of all sentient beings. This synthesis of science and ethics offers a blueprint for navigating the unknowns of space with wisdom and integrity, ensuring that our interstellar aspirations reflect the best of human values.
The rapid advancement of artificial intelligence (AI) is fundamentally transforming industrial sectors, driving the evolution of labor markets, and significantly reshaping economic structures. Within the paradigm of Industry 4.0, which is defined by the integration of AI, automation, and data analytics, substantial gains in operational efficiency, productivity, and innovation have been realized. However, the widespread deployment of AI technologies in workforce management raises pressing challenges, particularly in the realms of ethics, employment dynamics, and socio-economic impacts. This paper critically examines the ethical issues arising from AI adoption in Industry 4.0, with a focus on its implications for sustainable economic growth. The research delves into the pivotal role of AI in optimizing processes across manufacturing, logistics, and service industries, while also addressing critical concerns such as workforce displacement, data privacy, and algorithmic biases. The shift towards increased automation, though contributing to enhanced efficiency and competitiveness, necessitates a comprehensive reevaluation of labor market structures and the re-skilling of human capital. This paper underscores the importance of developing robust ethical frameworks that ensure AI deployment serves societal well-being, upholding human dignity and fostering equitable labor market opportunities. Beyond the technological challenges, the paper also explores the potential of AI to promote sustainable practices within Industry 4.0. It investigates how AI can be leveraged to reduce environmental impacts, optimize resource utilization, and drive innovation in sustainable technologies. Ethical dimensions such as transparency, accountability, and the mitigation of the digital divide are critically examined, ensuring that AI advancements are aligned with the broader goals of sustainable development. This study aims to provide a comprehensive analysis of the intersection between AI, labor markets, and ethical considerations within the context of Industry 4.0, offering valuable insights for policymakers, business leaders, and technologists to navigate the challenges of shaping a sustainable and inclusive future of work.
Pegadaian Syariah Digital Service (PSDS) is used to make it easier for customers to carry out transaction processes and make payments. This research aims to determine the influence of marketing strategies and the consumer environment on customers' decisions to use the Pegadaian Syariah Digital Service (PSDS) application at Pegadaian Syariah Bandar Lampung City, and to analyze transactions using the PSDS application from the perspective of Islamic Business Ethics. The sample for this research is customers who use the Pegadaian Syariah Digital Service (PSDS) application, totaling 89 respondents. The data collection technique uses a questionnaire via Google Form with multiple linear regression data analysis techniques using SPSS version 24 software. The results of this research show that marketing strategy and the consumer environment have a positive influence on customers' decisions to use the Pegadaian Syariah Digital Service (PSDS) application.
The decline in retail sales during the COVID-19 pandemic was driven by quarantine measures, household financial problems, social distancing norms and changes in consumer shopping behaviour. Shopping habits have been significantly transformed: customers refrained from visiting crowded and large stores where it was difficult to maintain social distancing, often preferred to shop online, made bulk purchases in one visit, reducing the need for frequent trips to the store, delegated a family member to do the shopping, avoided group visits to stores to minimize the impact of the virus on the family, etc. Therefore, the post-pandemic recovery of the retail sector is becoming an important task for many countries. The article systematizes the main problems of the retail sector after the COVID-19 pandemic in general and human resources issues in particular. It structures the scientific work of scholars from different countries on human resources management in retail in the post-pandemic period. During the pandemic crisis, the retail sector experienced a surge in job losses, wage cuts, and high staff turnover, and the pandemic created a problem of employees’ isolation from the team, as well as staff adaptability, as employees were forced to multitask and perform additional, non-standard functions. The rapid changes in quarantine restrictions during the pandemic left retailers’ management with limited time to consider and execute critical business decisions, including recruitment, which often resulted in either a shortage or overstaffing. As the economy has gradually recovered from the pandemic, this loss of human capital has proved irreversible, with many experienced employees having already adapted to other jobs or changed careers. The article explores the mechanisms for overcoming post-pandemic staff losses in retail through effective planning of human resource management policies, in particular, the bottom-up approach, trend analysis and the Delphi method, implementation of creative recruitment strategies in retail in the face of staff shortages, in particular, through digital technologies, with a focus on soft skills and adaptability of candidates, etc. The article also discusses the mechanisms for overcoming post-pandemic challenges in retail using effective methods for assessing the effectiveness of human resources (in particular, straight-ranking appraisals, grading, management by objectives and 360-degree appraisals), techniques to evaluate employee engagement, the integrated role of HR management and HR administration in this regard is substantiated. A separate part of the study is devoted to post-pandemic lessons for the human resource management system in ensuring safe working conditions and employee health and safety when retail workers still experience fear of large crowds and psychological distress about the transmission of viruses in the workplace through direct interaction with customers and objects. The next block of the study focuses on the changes in career planning requirements in the post-COVID-19 era, building appropriate strategies and scenarios.
In China, which in the past was dominated by state-owned and male-led ventures, female entrepreneurs are now increasingly popular. However, the specific pathways to internationalization for female-owned firms in China and their contribution to the country's economic growth remain unexplored. Based on the principles of the resource-based approach, the article explores the innovative strategies used by Chinese female-owned firms to overcome resource constraints, formal and informal institutional barriers to business internationalization (entering the global markets through indirect exports). The article puts forward and empirically tests 5 sets of hypotheses according to which Chinese female-owned firms are: 1) more efficient in internationalization through indirect export strategies; 2) more inclined to digital innovation; 3) not focused on innovation conversion, but rather on successful adaptation of existing offerings for international markets or efficiency gains; 4) do not prioritize innovation in communication technologies, focusing more on innovation to reach customers, build relationships and enter international markets; 5) use the female business ecosystem to obtain safer pathways to innovation, such as external partnerships or adapting existing technologies, rather than focusing on investing internal R&D with elevated risk. Within each block, 2 additional hypotheses were put forward. They consider the impact of the relevant factor (digital innovation, innovation conversion, communication innovation, internal innovation) on indirect exports and its role in mediating the relationship between female ownership and the success of business internationalization. The study is based on a sample of 2,700 Chinese firms surveyed from November 2011 to March 2013 using the World Bank Enterprise Surveys China 2012 (a comprehensive recoding was performed, adhering to established practices in quantitative research). The control variables are the location of the respondent company in the capital/province, city size and firm size. The study used two types of factor analysis - Exploratory (EFA, including Promax rotation, oblique rotation method) and Confirmatory (CFA, Alpha Cronbach test, full path analysis model, including both direct and indirect effects, Monte Carlo method). SPSS 29 software was used for the data sample and AMOS 26.0 for the modeling process. A direct positive relationship was found between female ownership and indirect exports in China and digital ecosystem innovations, as well as between communication innovations and indirect exports. A significant negative direct relationship was found between female ownership and communication innovations, between digital ecosystem innovations and indirect exports, and between internal innovations on indirect exports. It also reveals the absence of a significant direct impact of innovation conversion on indirect exports. Mediating effects were also confirmed for communication and digital ecosystem innovations; partially for internal innovations; not confirmed for innovation conversion.
Yifeng Philip Chen, Edward J. Oughton, Jakub Zagdanski
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Broadband connectivity is regarded as generally having a positive macroeconomic effect, but we lack evidence as to how it affects key economic activity metrics, such as firm creation, at a very local level. This analysis models the impact of broadband Next Generation Access (NGA) on new business creation at the local level over the 2011-2015 period in England, United Kingdom, using high-resolution panel data. After controlling for a range of factors, we find that faster broadband speeds brought by NGA technologies have a positive effect on the rate of business growth. We find that in England between 2011-2015, on average a one percentage increase in download speeds is associated with a 0.0574 percentage point increase in the annual growth rate of business establishments. The primary hypothesised mechanism behind the estimated relationship is the enabling effect that faster broadband speeds have on innovative business models based on new digital technologies and services. Entrepreneurs either sought appropriate locations that offer high quality broadband infrastructure (contributing to new business establishment growth), or potentially enjoyed a competitive advantage (resulting in a higher survival rate). The findings of this study suggest that aspiring to reach universal high capacity broadband connectivity is economically desirable, especially as the costs of delivering such service decline.
Simon Kolker, Louise Dennis, Ramon Fraga Pereira
et al.
We propose the use of the hypothetical retrospection argumentation procedure, developed by Sven Ove Hansson to improve existing approaches to machine ethical reasoning by accounting for probability and uncertainty from a position of Philosophy that resonates with humans. Actions are represented with a branching set of potential outcomes, each with a state, utility, and either a numeric or poetic probability estimate. Actions are chosen based on comparisons between sets of arguments favouring actions from the perspective of their branches, even those branches that led to an undesirable outcome. This use of arguments allows a variety of philosophical theories for ethical reasoning to be used, potentially in flexible combination with each other. We implement the procedure, applying consequentialist and deontological ethical theories, independently and concurrently, to an autonomous library system use case. We introduce a preliminary framework that seems to meet the varied requirements of a machine ethics system: versatility under multiple theories and a resonance with humans that enables transparency and explainability.
Marco Tulio Daza, Marco Tulio Daza, Usochi Joanann Ilozumba
et al.
Artificial intelligence is spreading rapidly in business products and processes, with innovations that bring great benefits to society; however, significant risks also arise. AI-enabled systems make decisions autonomously and influence users and the environment, presenting multiple ethical issues. This work focuses on the ethics of AI use in business. We conduct a survey of business journal articles published between 2000 and mid-2021 to identify the most influential journals, articles, and authors, the most influential ethical schools, and the main ethical issues of AI in business. It describes the state-of-the-art in the field and identifies trends in ethical issues arising from AI. Thus, we present maps and trends of the ethics in AI in business literature.