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Nurses face several challenges in providing care for patients with coronavirus disease in 2019 (COVID-19). The study aimed to explain the nurses' perception of ethical challenges in this regard. The qualitative study was carried out using a content analysis method. Individual and semi-structured interviews were conducted with 24 nurses. Inductive content analysis was used to categorize the data. Nurses' narratives indicated that ethical challenges in caring for patients with COVID-19 included threats to professional values ​​and the absence of a holistic COVID-19 care approach. The first category was subcategorized into the risk of declining quality of patient care and a stigmatized public image about COVID-19 care. The second category was divided into poor spiritual care, poor compassionate care, and lack of family-centered care. Health care managers must develop protocols for nurses that address these issues to alleviate the ethical challenges of COVID-19 care.

This paper’s overall objective is to identify the opportunities, challenges, and effects of artificial intelligence in advertising agencies. The theoretical approach of the key concept of artificial intelligence - its definition, typologies and effects, is followed by a particularization of the term in the advertising sector, based on a synthetic review, through a secondary analysis of statistical data, of the main trends in the AI use in current Romanian and international advertising. Subsequently, the paper focuses on the applied approach, based on qualitative research carried out through interviews with both employees from advertising agencies without management positions and managers of departments and advertising agencies where the former work, in order to identify the advantages and disadvantages of working with AI, but also positive and negative effects of using AI in advertising organizations, proposals for improving activities in which AI is used and, not least, ethical challenges related to working with AI. The integration of artificial intelligence in the advertising industry presents remarkable potential for innovation and efficiency, but also the need for a responsible approach to emerging challenges. The research provided a solid foundation for understanding the complexity and dynamism of the relationship between AI and advertising, highlighting that long-term success depends on the industry's ability to navigate this ever-evolving technology landscape with caution. By fostering a harmonious collaboration between technology and creativity, the advertising sector can maximize the benefits of AI while ethically addressing the associated challenges.

Background The contemporary frameworks for clinical research require informed consent for research participation that includes disclosure of material information, comprehension of disclosed information and voluntary consent to research participation. There is thus an urgent need to test, and an ethical imperative, to test, modify or refine medications or healthcare plans that could reduce patient morbidity, lower healthcare costs or strengthen healthcare systems. Methods Conceptual review. Discussion Although some allocation principles seem better than others, no single moral principle allocates interventions justly, necessitating combining the moral principles into multiprinciple allocation systems. The urgency notwithstanding, navigating ethical challenges related to conducting corona virus disease (COVID-19) clinical trials is mandatory, in order to safeguard the safety and welfare of research participants, ensure autonomy of participants, reduce possibilities for exploitation and ensure opportunities for research participation. The ethical challenges to can be categorized as challenges in allocation of resources for research; challenges of clinical equipoise in relation to the research questions; challenges of understanding disclosed information in potential participants; and challenges in obtaining informed consent. Conclusion To navigate these challenges, stakeholders need a delicate balance of moral principles during allocation of resources for research. Investigators need to apply information processing theories to aid decision-making about research participation or employ acceptable modifications to improve the informed consent process. Research and ethics committees should strengthen research review and oversight to ensure rigor, responsiveness and transparency.

This paper conducts a systematic review and interdisciplinary analysis of the ethical challenges of generative AI technologies (N = 37), highlighting significant concerns such as privacy, data protection, copyright infringement, misinformation, biases, and societal inequalities. The ability of generative AI to produce convincing deepfakes and synthetic media, which threaten the foundations of truth, trust, and democratic values, exacerbates these problems. The paper combines perspectives from various disciplines, including education, media, and healthcare, underscoring the need for AI systems that promote equity and do not perpetuate social inequalities. It advocates for a proactive approach to the ethical development of AI, emphasizing the necessity of establishing policies, guidelines, and frameworks that prioritize human rights, fairness, and transparency. The paper calls for a multidisciplinary dialogue among policymakers, technologists, and researchers to ensure responsible AI development that conforms to societal values and ethical standards. It stresses the urgency of addressing these ethical concerns and advocates for the development of generative AI in a socially beneficial and ethically sound manner, contributing significantly to the discourse on managing AI’s ethical implications in the modern digital era. The study highlights the theoretical and practical implications of these challenges and suggests a number of future research directions.

In the management and business ethics literatures, stakeholder engagement has been demonstrated to lead to more ethical management practices. However, there may be limits on the extent to which stakeholder engagement can, as currently conceptualized, resolve some of the more difficult ethical challenges faced by managers. In this paper we argue that stakeholder engagement, when seen as a way of reducing five types of knowledge problems—risk, ambiguity, complexity, equivocality, and a priori irreducible uncertainty—can aid managers in resolving such ethical challenges. Using a practical illustration of the ethical challenges surrounding the development and application of genetic modification technologies, we demonstrate how stakeholder engagement enables managers to better address these knowledge problems, thereby to manage more ethically. In this way, we suggest that stakeholder engagement has an even more crucial role to play in business ethics research and practice.

Virtual assistants (VAs) have gained widespread popularity across a wide range of applications, and the integration of Large Language Models (LLMs), such as ChatGPT, has opened up new possibilities for developing even more sophisticated VAs. However, this integration poses new ethical issues and challenges that must be carefully considered, particularly as these systems are increasingly used in public services: transfer of personal data, decision-making transparency, potential biases, and privacy risks. This paper, an extension of the work presented at IberSPEECH 2022, analyzes the current regulatory framework for AI-based VAs in Europe and delves into ethical issues in depth, examining potential benefits and drawbacks of integrating LLMs with VAs. Based on the analysis, this paper argues that the development and use of VAs powered by LLMs should be guided by a set of ethical principles that prioritize transparency, fairness, and harm prevention. The paper presents specific guidelines for the ethical use and development of this technology, including recommendations for data privacy, bias mitigation, and user control. By implementing these guidelines, the potential benefits of VAs powered by LLMs can be fully realized while minimizing the risks of harm and ensuring that ethical considerations are at the forefront of the development process.

This paper reviews the advances, challenges, and approaches of artificial intelligence (AI) and machine learning (ML) in the banking sector. The use of these technologies is accelerating in various industries, including banking. However, the literature on banking is scattered, making a global understanding difficult. This study reviewed the main approaches in terms of applications and algorithmic models, as well as the benefits and challenges associated with their implementation in banking, in addition to a bibliometric analysis of variables related to the distribution of publications and the most productive countries, as well as an analysis of the co-occurrence and dynamics of keywords. Following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) framework, forty articles were selected for review. The results indicate that these technologies are used in the banking sector for customer segmentation, credit risk analysis, recommendation, and fraud detection. It should be noted that credit analysis and fraud detection are the most implemented areas, using algorithms such as random forests (RF), decision trees (DT), support vector machines (SVM), and logistic regression (LR), among others. In addition, their use brings significant benefits for decision-making and optimizing banking operations. However, the handling of substantial amounts of data with these technologies poses ethical challenges.

This paper investigates the integration of ChatGPT into educational environments, focusing on its potential to enhance personalized learning and the ethical concerns it raises. Through a systematic literature review, interest analysis, and case studies, the research scrutinizes the application of ChatGPT in diverse educational contexts, evaluating its impact on teaching and learning practices. The key findings reveal that ChatGPT can significantly enrich education by offering dynamic, personalized learning experiences and real-time feedback, thereby boosting teaching efficiency and learner engagement. However, the study also highlights significant challenges, such as biases in AI algorithms that may distort educational content and the inability of AI to replicate the emotional and interpersonal dynamics of traditional teacher–student interactions. The paper acknowledges the fast-paced evolution of AI technologies, which may render some findings obsolete, underscoring the need for ongoing research to adapt educational strategies accordingly. This study provides a balanced analysis of the opportunities and challenges of ChatGPT in education, emphasizing ethical considerations and offering strategic insights for the responsible integration of AI technologies. These insights are valuable for educators, policymakers, and researchers involved in the digital transformation of education.

One key element distinguishing family firms from non-family firms is the role of the family’s religious beliefs, with growing attention on understanding the fit between religion and family in shaping a business’s ethical conduct. A family firm’s behavior is embedded in an institutional context, and it is important to understand how multiple institutional logic shapes a family firm’s values and ethical behavior. While scholars agree on the central significance of family values and religion in shaping family firms’ values and ethical behavior, a definitive consensus on the influence of family values and religion in confronting ethical challenges and shaping ethical behavior has yet to be reached. We lack a theory explaining how family, family business, and religion shape a family firm’s ethical conduct. We conducted a qualitative study to investigate the role of family values and religion in shaping a family firm’s ethical conduct. The results reveal four themes, namely (a) ethical challenges faced by family firms, (b) family values shaping ethical behavior, (c) religion providing a rationale for family firms’ ethical decision-making, and (d) outcomes of ethical decision-making. The principal contribution of our study is clarifying the role of multiple institutional logics in the form of religion and family in explaining ethical behavior. Our findings suggest that the fit between religion, family, and business as an institution guides decision-making, helps family businesses earn a positive reputation in the community by displaying ethical behavior, and develops a positive workplace climate.

Purpose Artificial intelligence (AI) has sparked interest in various areas, including marketing. However, this exhilaration is being tempered by growing concerns about the moral and legal implications of using AI in marketing. Although previous research has revealed various ethical and legal issues, such as algorithmic discrimination and data privacy, there are no definitive answers. This paper aims to fill this gap by investigating AI’s ethical and legal concerns in marketing and suggesting feasible solutions. Design/methodology/approach The paper synthesises information from academic articles, industry reports, case studies and legal documents through a thematic literature review. A qualitative analysis approach categorises and interprets ethical and legal challenges and proposes potential solutions. Findings The findings of this paper raise concerns about ethical and legal challenges related to AI in the marketing area. Ethical concerns related to discrimination, bias, manipulation, job displacement, absence of social interaction, cybersecurity, unintended consequences, environmental impact, privacy and legal issues such as consumer security, responsibility, liability, brand protection, competition law, agreements, data protection, consumer protection and intellectual property rights are discussed in the paper, and their potential solutions are discussed. Research limitations/implications Notwithstanding the interesting insights gathered from this investigation of the ethical and legal consequences of AI in marketing, it is important to recognise the limits of this research. Initially, the focus of this study is confined to a review of the most important ethical and legal issues pertaining to AI in marketing. Additional possible repercussions, such as those associated with intellectual property, contracts and licencing, should be investigated more deeply in future studies. Despite the fact that this study gives various answers and best practices for tackling the stated ethical and legal concerns, the viability and efficacy of these solutions may differ depending on the context and industry. Thus, more research and case studies are required to evaluate the applicability and efficacy of these solutions in other circumstances. This research is mostly based on a literature review and may not represent the experiences or opinions of all stakeholders engaged in AI-powered marketing. Further study might involve interviews or surveys with marketing professionals, customers and other key stakeholders to offer a full knowledge of the practical difficulties and solutions. Because of the rapid speed of technical progress, AI’s ethical and regulatory ramifications in marketing are continually increasing. Consequently, this work should be a springboard for more research and continuing conversations on this subject. Practical implications This study’s findings have several practical implications for marketing professionals. Emphasising openness and explainability: Marketing professionals should prioritise transparency in their use of AI, ensuring that customers are fully informed about data collection and utilisation for targeted advertising. By promoting openness and explainability, marketers can foster customer trust and avoid the negative consequences of a lack of transparency. Establishing ethical guidelines: Marketing professionals need to develop ethical rules for the creation and implementation of AI-powered marketing strategies. Adhering to ethical principles ensures compliance with legal norms and aligns with the organisation’s values and ideals. Investing in bias detection tools and privacy-enhancing technology: To mitigate risks associated with AI in marketing, marketers should allocate resources to develop and implement bias detection tools and privacy-enhancing technology. These tools can identify and address biases in AI algorithms, safeguard consumer privacy and extract valuable insights from consumer data. Social implications This study’s social implications emphasise the need for a comprehensive approach to address the ethical and legal challenges of AI in marketing. This includes adopting a responsible innovation framework, promoting ethical leadership, using ethical decision-making frameworks and conducting multidisciplinary research. By incorporating these approaches, marketers can navigate the complexities of AI in marketing responsibly, foster an ethical organisational culture, make informed ethical decisions and develop effective solutions. Such practices promote public trust, ensure equitable distribution of benefits and risk, and mitigate potential negative social consequences associated with AI in marketing. Originality/value To the best of the authors’ knowledge, this paper is among the first to explore potential solutions comprehensively. This paper provides a nuanced understanding of the challenges by using a multidisciplinary framework and synthesising various sources. It contributes valuable insights for academia and industry.