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Cybersecurity vulnerabilities are often due to human users acting according to their own ethical priorities. With the goal of providing tailored training to cybersecurity professionals, the authors conducted a study to uncover profiles of human factors that influence which ethical principles are valued highest following exposure to ethical dilemmas presented in a cybersecurity game.

The authors’ game first sensitises players (cybersecurity trainees) to five cybersecurity ethical principles (beneficence, non-maleficence, justice, autonomy and explicability) and then allows the player to explore their application in multiple cybersecurity scenarios. After playing the game, players rank the five ethical principles in terms of importance. A total of 250 first-year cybersecurity students played the game. To develop profiles, the authors collected players' demographics, knowledge about ethics, personality, moral stance and values.

The authors built models to predict the importance of each of the five ethical principles. The analyses show that, generally, the main driver influencing the priority given to specific ethical principles is cultural background, followed by the personality traits of extraversion and conscientiousness. The importance of the ingroup was also a prominent factor.

Cybersecurity professionals need to understand the impact of users' ethical choices. To provide ethics training, the profiles uncovered will be used to build artificially intelligent (AI) non-player characters (NPCs) to expose the player to multiple viewpoints. The NPCs will adapt their training according to the predicted players’ viewpoint.

Following the surge of documents laying out organizations' ethical principles for their use of artificial intelligence (AI), there is a growing demand for translating ethical principles to practice through AI governance (AIG). AIG has emerged as a rapidly growing, yet fragmented, research area. This paper synthesizes the organizational AIG literature by outlining research themes and knowledge gaps as well as putting forward future agendas.

The authors undertake a systematic literature review on AIG, addressing the current state of its conceptualization and suggesting future directions for AIG scholarship and practice. The review protocol was developed following recommended guidelines for systematic reviews and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).

The results of the authors’ review confirmed the assumption that AIG is an emerging research topic with few explicit definitions. Moreover, the authors’ review identified four themes in the AIG literature: technology, stakeholders and context, regulation and processes. The central knowledge gaps revealed were the limited understanding of AIG implementation, lack of attention to the AIG context, uncertain effectiveness of ethical principles and regulation, and insufficient operationalization of AIG processes. To address these gaps, the authors present four future AIG agendas: technical, stakeholder and contextual, regulatory, and process. Going forward, the authors propose focused empirical research on organizational AIG processes, the establishment of an AI oversight unit and collaborative governance as a research approach.

To address the identified knowledge gaps, the authors present the following working definition of AIG: AI governance is a system of rules, practices and processes employed to ensure an organization's use of AI technologies aligns with its strategies, objectives, and values, complete with legal requirements, ethical principles and the requirements set by stakeholders. Going forward, the authors propose focused empirical research on organizational AIG processes, the establishment of an AI oversight unit and collaborative governance as a research approach.

For practitioners, the authors highlight training and awareness, stakeholder management and the crucial role of organizational culture, including senior management commitment.

For society, the authors review elucidates the multitude of stakeholders involved in AI governance activities and complexities related to balancing the needs of different stakeholders.

By delineating the AIG concept and the associated research themes, knowledge gaps and future agendas, the authors review builds a foundation for organizational AIG research, calling for broad contextual investigations and a deep understanding of AIG mechanisms. For practitioners, the authors highlight training and awareness, stakeholder management and the crucial role of organizational culture, including senior management commitment.

This study aims to explore how Russian-origin immigrant entrepreneurs manage to adapt their business-to-business (B2B) relationship management practices and moral concerns to the business ethics of their country of origin and of the host country via the prism of ethical relativism. By focusing on the ethical values of immigrant entrepreneurs in a business relationship context, the study aims to extend the currently limited understanding of these issues in the B2B marketing field.

A qualitative approach is applied to provide findings from eight in-depth interviews with first-generation Russian entrepreneurs living and doing business in Finland. A narrative approach to the data analysis is used, in particular by applying a thematic analysis of the collected interviews because of the focus on the personal experiences of the interviewees.

The results illustrate how the immigrant entrepreneurs adapt to ethical values and norms in Russia and Finland and how they enact those values in B2B relationship management in the countries. Immigrant entrepreneurs share several national and ethical backgrounds, which may influence their interaction in international markets, helping them adapt to country-specific business ethics.

The results imply that managers should acquire knowledge on ethical norms at the global level and at the national level, where they aim to expand their business. Productive business relationships involve the premises of honesty, transparency, fairness toward business partners and minimizing opportunism. However, business relations between developed and emerging markets may demand relativism when addressing ethical behavior.

This is one of the few studies that explore the ethical values of immigrant entrepreneurs in the context of international business relationships. The study contributes to the limited literature on ethics in the fields of B2B marketing and immigrant entrepreneurship. The authors encourage further research on ethical values adoption by immigrant entrepreneurs, which is an essential topic in times of increased workforce immigration.

The purpose of this paper is clearly illustrate this convergence and the prescriptive recommendations that such documents entail. There is a significant amount of research into the ethical consequences of artificial intelligence (AI). This is reflected by many outputs across academia, policy and the media. Many of these outputs aim to provide guidance to particular stakeholder groups. It has recently been shown that there is a large degree of convergence in terms of the principles upon which these guidance documents are based. Despite this convergence, it is not always clear how these principles are to be translated into practice.

In this paper, the authors move beyond the high-level ethical principles that are common across the AI ethics guidance literature and provide a description of the normative content that is covered by these principles. The outcome is a comprehensive compilation of normative requirements arising from existing guidance documents. This is not only required for a deeper theoretical understanding of AI ethics discussions but also for the creation of practical and implementable guidance for developers and users of AI.

In this paper, the authors therefore provide a detailed explanation of the normative implications of existing AI ethics guidelines but directed towards developers and organisational users of AI. The authors believe that the paper provides the most comprehensive account of ethical requirements in AI currently available, which is of interest not only to the research and policy communities engaged in the topic but also to the user communities that require guidance when developing or deploying AI systems.

The authors believe that they have managed to compile the most comprehensive document collecting existing guidance which can guide practical action but will hopefully also support the consolidation of the guidelines landscape. The authors’ findings should also be of academic interest and inspire philosophical research on the consistency and justification of the various normative statements that can be found in the literature.

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.

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。

Research into the interpretability and explainability of data analytics and artificial intelligence (AI) systems is on the rise. However, most recent studies either solely promote the benefits of explainability or criticize it due to its counterproductive effects. This study addresses this polarized space and aims to identify opposing effects of the explainability of AI and the tensions between them and propose how to manage this tension to optimize AI system performance and trustworthiness.

The author systematically reviews the literature and synthesizes it using a contingency theory lens to develop a framework for managing the opposing effects of AI explainability.

The author finds five opposing effects of explainability: comprehensibility, conduct, confidentiality, completeness and confidence in AI (5Cs). The author also proposes six perspectives on managing the tensions between the 5Cs: pragmatism in explanation, contextualization of the explanation, cohabitation of human agency and AI agency, metrics and standardization, regulatory and ethical principles, and other emerging solutions (i.e. AI enveloping, blockchain and AI fuzzy systems).

As in other systematic literature review studies, the results are limited by the content of the selected papers.

The findings show how AI owners and developers can manage tensions between profitability, prediction accuracy and system performance via visibility, accountability and maintaining the “social goodness” of AI. The results guide practitioners in developing metrics and standards for AI explainability, with the context of AI operation as the focus.

This study addresses polarized beliefs amongst scholars and practitioners about the benefits of AI explainability versus its counterproductive effects. It poses that there is no single best way to maximize AI explainability. Instead, the co-existence of enabling and constraining effects must be managed.

Multinational enterprises (MNEs) are increasingly compelled to consider the United Nation’s sustainable development goals (SDGs). These goals are complex and may cause internal goal conflicts for companies. To stay the course, MNEs will benefit from an ethical compass enabling them to take on leading roles in driving change towards a better future. We argue that ethical leadership in this new business landscape is bolstered by virtue ethics. MNEs with genuine ethical groundings will be equipped to make decisions in complex situations where the needs of a variety of stakeholders must be considered. The purpose of this chapter is to conceptually and empirically explore an MNE’s implementation of a particular SDG, through an ethical leadership lens. We contribute to international management and international business literature by offering a framework to analyse MNEs’ pursuit of SDGs.

This study aims to analyze the relationship between companies’ business ethics (BE) and corporate social responsibility (CSR), with particular reference to policies toward employees, with the aim of understanding if and how the two concepts are linked and to foster a better management of the company-employee relationship through BE and CSR policies.

Through a content analysis, the authors study three issues related to employees disclosed in Code of Ethics (CE) and CSR report of a sample of Italian companies. Next, using a multivariate regression model, the authors examine the relation between the BE and CSR initiatives, related to employees.

The findings show that CE and CSR initiatives are negatively related. They are distinct concepts, but since the authors find that they are connected, they must also be considered in terms of their mutual dependence. To standardize practices toward employees in a code may induce the need to establish additional corporate social responsibility initiatives that elicit legitimate stakeholder satisfaction.

The analysis focuses on employees, whereas several other CSR aspects that can be explored. Furthermore, additional investigation (through questionnaires or interviews) could deepen this analysis. Furthermore, it might be interesting to consider different countries or more variables, such as cultural differences or different regulations.

The results of this research reveal that BE and CSR initiatives require precise and personalized observations to be properly understood; however, as they are linked, they must also be studied in their mutual interdependencies; this can be very useful to define governance bodies and organizational procedures devoted to BE and CSR issues.

This research provides a tool for evaluating and monitoring CSR and BE principles and can be adapted to many business contexts and refer to different stakeholders.

The existing literature on BE and CSR presents opportunities for further study, as these concepts are often studied without insights into their mutual impacts.

At Embry-Riddle Aeronautical University, an annual short-term, research abroad non-credit program was created in 2012 as a core component of the undergraduate research initiative that achieves learning outcomes in a meaningful way. The paper aims to discuss this issue.

In order to describe, and analyze the short-term research abroad activity, an instrumental case study design was created. The instrumental case study was chosen as a means of allowing the facilitators/authors to communicate how they attempted to assure that the program was educative. In order to determine if the program was in fact educative and that it met its goal of being an effective research experience the authors utilized two additional research methods. The first was a document analysis of the participant’s research artifacts. Each participant was required to communicate their findings by writing a paper that was submitted for publication to an applicable research journal.

The study found that an experiential education as a pedagogical framework coupled with a short-term research abroad activity can lead to a substantive educative experience, where the authors described and analyzed attempts to ensure that the short-term research abroad program was educative, it also describes the educational assessment findings which describe what was found when the authors tested whether they, in fact, met this goal.

During the design phase of the short-term research abroad program, the authors turned to experiential education as a principle for how they would ensure that the program was grounded in an acceptable educational theory. Experiential education is a widely accepted educational practice used in experiences such as co-ops and internships, study abroad, undergraduate research and service learning.

To frame the short-term cultural research abroad program as something from which student could learn the authors utilized the National Society of Experiential Education’s (2013) list of eight principles of good practice. In order to safeguard that an activity is educative, an assessment or an evaluation of a demonstrative artifact is essential. In assessing the final artifact against a rubric or some other non-biased or less biased criteria, an educator can ensure that the student has gained new knowledge in the form of student learning outcomes (SLOs). In addition, the educator can use the results of this assessment to modify many different aspects of the experience ranging from the timing, the modality, the pre-work, even the learning outcomes themselves.

Given financial and curriculum inflexibility of some students, Universities and faculty could achieve attainment of research-based, program agnostic, SLOs by offering short-term study abroad alternatives to the traditional semester or year-long experiences. With graduates looking to enter the job market where businesses are more globalized and executive’s recognition of a need for more international experience, carefully constructed short-term study abroad programs are meaningful avenues to build those credentials.

Such offerings can be constructed as customized experiences to achieve highly integrated skills across all degree programs.