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This study aims to identify and assess the key ethical challenges associated with integrating artificial intelligence (AI) in knowledge-sharing (KS) practices and their implications for decision-making (DM) processes within organisations.

The study employs a mixed-methods approach, beginning with a comprehensive literature review to extract background information on AI and KS and to identify potential ethical challenges. Subsequently, a confirmatory factor analysis (CFA) is conducted using data collected from individuals employed in business settings to validate the challenges identified in the literature and assess their impact on DM processes.

The findings reveal that challenges related to privacy and data protection, bias and fairness and transparency and explainability are particularly significant in DM. Moreover, challenges related to accountability and responsibility and the impact of AI on employment also show relatively high coefficients, highlighting their importance in the DM process. In contrast, challenges such as intellectual property and ownership, algorithmic manipulation and global governance and regulation are found to be less central to the DM process.

This research contributes to the ongoing discourse on the ethical challenges of AI in knowledge management (KM) and DM within organisations. By providing insights and recommendations for researchers, managers and policymakers, the study emphasises the need for a holistic and collaborative approach to harness the benefits of AI technologies whilst mitigating their associated risks.

In this chapter, we explore the ethical dilemmas commonly faced in community development projects, providing guidance for practitioners and policy makers. We delve into various challenges, from resource allocation to managing diverse stakeholder needs, using ethical theories and real-world case studies, including examples from the Ecuadorian Amazon Rainforest, Haiti Earthquake relief, and an Indigenous education program in Australia. We emphasize the importance of ethical decision-making, showcasing the potential impacts of choices on communities and individuals. Practical strategies are presented to maintain ethical integrity, such as transparent communication and accountability mechanisms, enabling stakeholders to navigate dilemmas with sensitivity and uphold ethical standards. This chapter serves as a valuable guide for those involved in community development, fostering sustainable and equitable initiatives that empower communities and drive positive transformation.

This paper aims to explore the common ethical decision-making challenges faced by financial advisers and how they meet these challenges. The purpose is to identify successful decision-making tools used by investment advisers in doing business ethically. Additionally, the authors uncover common challenges and offer decision-making tools to provide support for supplemental ethics training in the future.

Questions were analyzed through a qualitative approach using individual interviews to examine a range of experiences and attitudes of active financial advisers. The sample was represented by 11 practicing financial advisers affiliated with US independent broker-dealers: six women and five men, each with 10 or more years of experience, ranging in age from 35 to 75. Grounded in four ethical decision-making models, this research examines individual ethical decision-making using individual (internal, personal) and organizational (external, situational) factors.

The method used uncovered struggles and revealed strategies used in making ethical decisions. Two research questions were examined: what are the common ethical decision-making challenges faced by financial advisers in the US financial industry? How do financial advisers handle ethical decision-making challenges? Four themes emerged that impacted ethical decision-making: needs of the individual, needs of others, needs of the firm and needs of the marketplace. Financial advisers identified moral obligation, self-control and consulting with others as major considerations when they contemplate difficult decisions.

A limitation of this review is its small sample size. A more robust sample size from investment advisers with a broader range of experiences could have widened the findings from the study.

Investment advisers can use the findings of this study as a tool for improving their own ethical decision-making or designing training for their employees to be better decision-makers.

The study explores the decision-making experiences of investment advisers to reveal multifaceted, often private struggles that qualitative methods can uncover. The study provides support for the development of additional training in ethical decision-making specific to investment advisers.

This chapter explores the vital connection between ethics and community development, underlining the fundamental role of ethical considerations in shaping fair, just, and sustainable communities. It begins by emphasizing that community development is inherently ethical and delves into the concept of ethics, examining ethical theories like consequentialism, deontology, and virtue ethics in the context of community development. Real-world case studies from diverse countries, such as South Africa, Australia, and India, are interwoven throughout the chapter to provide practical insights. These case studies illustrate the complexities of ethical implementation in community development, from navigating power dynamics to addressing conflicts of interest and balancing immediate needs with long-term sustainability. The chapter also explores macro-level considerations, highlighting the need for systemic change to create a more just and equitable society. It guides practitioners on integrating ethics into their work, establishing a strong moral framework for community development. Continuous learning, reflective practice, and adaptability are underscored as essential in responding to evolving societal contexts, norms, and challenges.

This study aims to investigate how living lab (LL) activities align with responsible research and innovation (RRI) principles, particularly in artificial intelligence (AI)-driven digital transformation (DT) processes. The study seeks to define a framework termed “responsible living lab” (RLL), emphasizing transparency, stakeholder engagement, ethics and sustainability. This emerging issue paper also proposes several directions for future researchers in the field.

The research methodology involved a literature review complemented by insights from a workshop on defining RLLs. The literature review followed a concept-centric approach, searching key journals and conferences, yielding 32 relevant articles. Backward and forward citation analysis added 19 more articles. The workshop, conducted in the context of UrbanTestbeds.JR and SynAir-G projects, used a reverse brainstorming approach to explore potential ethical and responsible issues in LL activities. In total, 13 experts engaged in collaborative discussions, highlighting insights into AI’s role in promoting RRI within LL activities. The workshop facilitated knowledge sharing and a deeper understanding of RLL, particularly in the context of DT and AI.

This emerging issue paper highlights ethical considerations in LL activities, emphasizing user voluntariness, user interests and unintended participation. AI in DT introduces challenges like bias, transparency and digital divide, necessitating responsible practices. Workshop insights underscore challenges: AI bias, data privacy and transparency; opportunities: inclusive decision-making and efficient innovation. The synthesis defines RLLs as frameworks ensuring transparency, stakeholder engagement, ethical considerations and sustainability in AI-driven DT within LLs. RLLs aim to align DT with ethical values, fostering inclusivity, responsible resource use and human rights protection.

The proposed definition of RLL introduces a framework prioritizing transparency, stakeholder engagement, ethics and sustainability in LL activities, particularly those involving AI for DT. This definition aligns LL practices with RRI, addressing ethical implications of AI. The value of RLL lies in promoting inclusive and sustainable innovation, prioritizing stakeholder needs, fostering collaboration and ensuring environmental and social responsibility throughout LL activities. This concept serves as a foundational step toward a more responsible and sustainable LL approach in the era of AI-driven technologies.

However, while the benefits of adopting virtual work structures have been extensively discussed, ethical considerations have been largely ignored in the existing literature. To fill this gap, this study aims to investigate the key ethical issues associated with virtual workplaces. It also aimed to examine the various preventive measures that could be considered for effectively managing such challenges.

The study adopted an inductive research approach using qualitative methodology. Data was collected by executing the technique of dual moderator focus group discussion. By using the purposive sampling technique, the sample comprised 24 software professionals from emerging economies such as India. All sessions were transcribed, and the data were analysed using the content analysis method.

The study reports some interesting results related to various ethical issues and the preventive measures to handle such issues in virtual workplaces. The themes that emerged related to ethical issues have been categorised into three broad categories, i.e. People, Technology and Culture. In contrast, preventive measures have been reported in both contexts, i.e. pre-preventive and post-preventive measures. Furthermore, few recommendations have been made to improve virtual work experiences for remote work professionals. The identified themes and categories were classified and arranged in “Network View”, a feature embedded in Atlas.ti7 software, to analyse the conceptual relationships.

The findings may help managers regarding various ethical issues in virtual work settings. It may also provide an insight to the managers about the benefits of adopting preventive measures for handling ethical dilemmas in virtual workplaces in an emerging economy like India.

The study may be seen as one of the earliest attempts to consider the lingering debate on ethics in virtual workplaces. The findings of the study have implications for further theoretical research on the topic.

Artificial intelligence (AI) offers many benefits to improve predictive marketing practice. It raises ethical concerns regarding customer prioritization, market share concentration and consumer manipulation. This paper explores these ethical concerns from a contemporary perspective, drawing on the experiences and perspectives of AI and predictive marketing professionals. This study aims to contribute to the field by providing a modern perspective on the ethical concerns of AI usage in predictive marketing, drawing on the experiences and perspectives of professionals in the area.

The study conducted semistructured interviews for 6 weeks with 14 participants experienced in AI-enabled systems for marketing, using purposive and snowball sampling techniques. Thematic analysis was used to explore themes emerging from the data.

Results reveal that using AI in marketing could lead to unintended consequences, such as perpetuating existing biases, violating customer privacy, limiting competition and manipulating consumer behavior.

The authors identify seven unique themes and benchmark them with Ashok’s model to provide a structured lens for interpreting the results. The framework presented by this research is unique and can be used to support ethical research spanning social, technological and economic aspects within the predictive marketing domain.

La Inteligencia Artificial (IA) ofrece muchos beneficios para mejorar la práctica del marketing predictivo. Sin embargo, plantea preocupaciones éticas relacionadas con la priorización de clientes, la concentración de cuota de mercado y la manipulación del consumidor. Este artículo explora estas preocupaciones éticas desde una perspectiva contemporánea, basándose en las experiencias y perspectivas de profesionales en IA y marketing predictivo. El estudio tiene como objetivo contribuir a la literatura de este ámbito al proporcionar una perspectiva moderna sobre las preocupaciones éticas del uso de la IA en el marketing predictivo, basándose en las experiencias y perspectivas de profesionales en el área.

Para realizar el estudio se realizaron entrevistas semiestructuradas durante seis semanas con 14 participantes con experiencia en sistemas habilitados para IA en marketing, utilizando técnicas de muestreo intencional y de bola de nieve. Se utilizó un análisis temático para explorar los temas que surgieron de los datos.

Los resultados revelan que el uso de la IA en marketing podría tener consecuencias no deseadas, como perpetuar sesgos existentes, violar la privacidad del cliente, limitar la competencia y manipular el comportamiento del consumidor.

El estudio identifica siete temas y los comparan con el modelo de Ashok para proporcionar una perspectiva estructurada para interpretar los resultados. El marco presentado por esta investigación es único y puede utilizarse para respaldar investigaciones éticas que abarquen aspectos sociales, tecnológicos y económicos dentro del ámbito del marketing predictivo.

人工智能（AI）为改进预测营销实践带来了诸多益处。然而, 这也引发了与客户优先级、市场份额集中和消费者操纵等伦理问题相关的观点。本文从当代角度深入探讨了这些伦理观点, 充分借鉴了人工智能和预测营销领域专业人士的经验和观点。旨在通过现代视角提供关于在预测营销中应用人工智能时所涉及的伦理观点, 为该领域做出有益贡献。

本研究采用了目的性和雪球抽样技术, 与14位在人工智能营销系统领域具有丰富经验的参与者进行为期六周的半结构化访谈。研究采用主题分析方法, 旨在深入挖掘数据中显现的主要主题。

研究结果表明, 在营销领域使用人工智能可能引发一系列意外后果, 包括但不限于加强现有偏见、侵犯客户隐私、限制竞争以及操纵消费者行为。

本研究通过明确定义七个独特的主题, 并采用阿肖克模型进行基准比较, 为读者提供了一个结构化的视角, 以解释研究结果。所提出的框架具有独特之处, 可有效支持在跨足社会、技术和经济领域的预测营销中展开的伦理研究。

Nurse leaders are challenged by ethical issues in today’s complex health-care settings. The purpose of this study was to describe and analyze key elements of moral distress identified by nurse leaders from health-care systems in the USA, Germany, Austria and Switzerland. The aim was to develop an understanding of distressing ethical issues nurse leaders face in the USA and three German-speaking European countries.

This descriptive cross-sectional study surveyed a convenience sample of nurse leaders in the USA, Germany, Austria and Switzerland. The voluntary, anonymous survey also included qualitative questions and was distributed using the Qualtrics® platform. A thematic analysis of the qualitative data in each country was carried out and a comparative analysis identified similarities and differences between the groups of nurse leaders comparing the US data to that from three German-speaking European countries.

The survey was completed by 316 nurse leaders: Germany, Austria, and Switzerland (n = 225) and the USA (n = 91). Similar themes identified as causing all nurse leaders moral distress included a lack of individual and organizational integrity, hierarchical and interprofessional issues, lack of nursing professionalism, patient care/patient safety concerns, finances negatively impacting care and issues around social justice. Within these six themes, there were also differences between the USA and the three German-speaking European countries.

Understanding the experiences associated with distressing ethical situations can allow nurse leaders and organizations to focus on solutions and develop resilience to reduce moral distress in the USA and three German-speaking European countries.