Iqbal H. Sarker, Helge Janicke, Ahmad Mohsin
et al.
Abstract Artificial Intelligence (AI) and Large Language Models (LLMs) are revolutionizing today’s business practices; however, their adoption within small and medium-sized enterprises (SMEs) raises serious trust, ethical, and technical issues. In this perspective paper, we introduce a structured, multi-phased framework, “SME-TEAM", positioning trust and ethics as a driving force for resilience, competitiveness, and sustainable innovation within the area of business analytics and SMEs.
Martina De Sanctis, Gianluca Filippone, Paola Inverardi
et al.
This paper addresses the challenge of operationalizing ethics in autonomous systems through runtime enforcement. It first conceptualizes the system's ethical space and outlines a structured ethics assurance process. Building on this foundation, it introduces an enforcement subsystem that operationalizes ethical rules, specifically social, legal, ethical, empathetic, and cultural (SLEEC) requirements, through the Abstract State Machine (ASM) formalism. The enforcement subsystem is built on the MAPE-K control-loop architecture for monitoring and controlling the system's ethical behavior, and it relies on an ASM-based runtime model of the ethical rules to enforce. This enables the dynamic evaluation, adaptation, and enforcement of ethical behavior within a runtime formal model. The overall approach, named SLEEC@run.time, is demonstrated on an assistive robot scenario, showcasing how both the robot's behavior and the governing ethical rules can dynamically adapt to contextual changes. By leveraging a flexible runtime model, SLEEC@run.time accommodates changes such as the addition or removal of SLEEC rules, ensuring a robust and evolvable approach to ethical assurance in autonomous systems. The evaluation of SLEEC@run.time shows that it effectively ensures the system's adherence to ethical principles with negligible execution time overhead.
Jukka Ruohonen, Jani Koskinen, Søren Harnow Klausen
et al.
Context: Dark patterns are user interface or other software designs that deceive or manipulate users to do things they would not otherwise do. Even though dark patterns have been under active research for a long time, including particularly in computer science but recently also in other fields such as law, systematic applied ethical assessments have generally received only a little attention. Objective: The present work evaluates ethical concerns in dark patterns and their research in software engineering and closely associated disciplines. The evaluation is extended to cover not only dark patterns themselves but also the research ethics and applied ethics involved in studying, developing, and deploying them. Method: A scenario analysis is used to evaluate six theoretical dark pattern scenarios. The ethical evaluation is carried out by focusing on the three main branches of normative ethics; utilitarianism, deontology, and virtue ethics. In terms of deontology, the evaluation is framed and restricted to the laws enacted in the European Union. Results: The evaluation results indicate that dark patterns are not universally morally bad. That said, numerous ethical issues with practical relevance are demonstrated and elaborated. Some of these may have societal consequences. Conclusion: Dark patterns are ethically problematic but not always. Therefore, ethical assessments are necessary. The two main theoretical concepts behind dark patterns, deception and manipulation, lead to various issues also in research ethics. It can be recommended that dark patterns should be evaluated on case-by-case basis, considering all of the three main branches of normative ethics in an evaluation. Analogous points apply to legal evaluations, especially when considering that the real or perceived harms caused by dark patterns cover both material and non-material harms to natural persons.
Mahamodul Hasan Mahadi, Md. Nasif Safwan, Souhardo Rahman
et al.
Developing AI systems capable of nuanced ethical reasoning is critical as they increasingly influence human decisions, yet existing models often rely on superficial correlations rather than principled moral understanding. This paper introduces Ethic-BERT, a BERT-based model for ethical content classification across four domains: Commonsense, Justice, Virtue, and Deontology. Leveraging the ETHICS dataset, our approach integrates robust preprocessing to address vocabulary sparsity and contextual ambiguities, alongside advanced fine-tuning strategies like full model unfreezing, gradient accumulation, and adaptive learning rate scheduling. To evaluate robustness, we employ an adversarially filtered "Hard Test" split, isolating complex ethical dilemmas. Experimental results demonstrate Ethic-BERT's superiority over baseline models, achieving 82.32% average accuracy on the standard test, with notable improvements in Justice and Virtue. In addition, the proposed Ethic-BERT attains 15.28% average accuracy improvement in the HardTest. These findings contribute to performance improvement and reliable decision-making using bias-aware preprocessing and proposed enhanced AI model.
Silvia Rodrigues dos Santos, Mirelle Finkler, Marta Verdi
A pandemia de covid-19 no Brasil contou com um número expressivo de mortes. Os marcadores sociais foram elementos indispensáveis na compreensão de seus desdobramentos. Esta pesquisa voltou seu olhar à população indígena, sabendo que ela enfrenta problemas significativos de cunho estrutural, tendo como objetivo compreender como se deu a garantia de acesso e proteção à saúde desta população em um período atravessado por evidente política anti-indígena. Para tanto, foram analisados documentos de março de 2020 a março de 2022, localizados em plataformas virtuais, incluindo as normativas publicadas pelo Poder Executivo. Com auxílio do software Atlas.Ti® realizamos Análise Temática de Conteúdo dos documentos selecionados. Os resultados evidenciaram as articulações de base dos povos originários como ponto fundamental para a proteção de suas vidas e identidades. Sob o escopo de uma Bioética Latino-americana, cunhamos possibilidades de leitura dos achados, possibilitando sua compreensão por um viés crítico-social.
Medical philosophy. Medical ethics, Business ethics
De siste årene har media tatt opp stadig flere saker der ledere i både private og offentlige virksomheter ikke har fremstått som gode rollemodeller. Dette har bidratt til at en nå i større grad etterspør en utdanning som fremmer etisk refleksjon og ansvarlighet hos fremtidige ledere. Likevel finnes det få studier som belyser undervisningspraksis i etikk i økonomisk-administrativ utdanning i en norsk kontekst. Studien som denne artikkelen bygger på, ønsker å bidra til diskusjon, utvikling og refleksjon om hva som påvirker undervisningspraksis i etikkundervisningen i økonomisk-administrativ utdanning.
Denne studien undersøker emneansvarliges perspektiver på egen undervisningsplanlegging og hva som påvirker den. Studien bygger på data fra 14 semistrukturerte intervjuer med emneansvarlige i etikkemner ved bachelorutdanninger i økonomi og administrasjon. Analysen viser et mangfold av ulike valg knyttet til planlegging av undervisning, oppfatninger av hensikten med etikkundervisning og konsekvenser av ulike rammevilkår. Videre viser analysen at emneansvarlige opplever institusjonenes prioriteringer som styrende for planleggingen, noe de mener hemmer en undervisning preget av dialog og refleksjon. Analysen viser også en diskrepans mellom nasjonale minimumskrav og undervisningen som planlegges, noe som vil kreve videre oppmerksomhet i fremtiden.
ENGLISH ABSTRACT
Course managers’ perspectives on teaching ethics in business education
In recent years, the media has increasingly taken up cases where business leaders have not appeared as good role models. This is one of the reasons the business community is now demanding an education that promotes ethical reflection and responsibility in future managers. Nevertheless, there are few studies that shed light on teaching practices in ethics in business education in a Norwegian context. The study on which this article is based wants to contribute to discussion, development and reflection on what affects teaching practices in ethics courses in business education.
This study examines course managers’ perspectives on their own teaching planning and what influences it. The study is based on data from 14 semi-structured interviews with course managers in ethics courses in bachelor’s programs in business education. The analysis shows a diversity of choices related to the planning of teaching, the perception of the purpose of ethics teaching and the consequences of different framework conditions. Furthermore, the analysis shows that the institutions’ priorities govern the planning, which inhibits a teaching approach that encourages students’ dialogue and reflection. The analysis also shows a discrepancy between the teaching planned and national minimum requirements, which will require further attention in the future.
This article uses the findings obtained from a study that delves into the perceptions of students on their relationship with their higher education (HE) lecturers and how it affects their academic success, to respond to the issue of decolonisation in South African HE, and to approach the question of decolonising HE in Africa. The article argues that it is essential to prioritise student well-being, amplify their voices, and promote a caring culture towards addressing the issue of decolonisation in African education systems. The study shows that African HE students hold higher expectations of their lecturers beyond being professionals. This expectation includes respect for students’ thoughts and incorporation of epistemology that aligns with fostering African development, culture and thoughts (without necessarily conforming to neoliberal norms). The four categories of the teacher’s role, which include academic development, respect and trust, social relationships, and ethics of care are highly demanded by HE students. Borrowing the study outcome, this article holds the view that students’ high expectations of their lecturers to foster social relationships should be channelled to incorporate the African student as a collaborator in the business of education and as a response to the demands of HE students to decolonise African education system. These four categories are not only institutional strategies for effective teaching and learning but also a way to address the non-inclusive impact of Western epistemology on historically racial institutions in Africa.
Contribution: This article proposes that adopting mainstream pedagogical relationships can be a powerful tool in incorporating the African students’ thoughts and a step towards liberating the HE system in Africa. It recommends these four cardinal themes as institutional strategies for restricting teaching and learning that relegate students to the receiving end thus systems that refute students as collaborators of knowledge sharing especially at historically racial institutions.
Abstract This study is to examine the translation of a reputable brand into equity and how consumers’ perceptions can trigger value creation from commitment and pursuit of CSR by an organization and adopting the same as a brand, lifestyle, and culture, while pointing attention to the stakeholder’s theory as well as pointing to brand interactions from consumer perceptions based on a mixed methods research approach from quantitative and qualitative analyses as presented with a sampling survey of 205 observations and respondents from Roma and neighbourhood. A CSR-based business model tied to the cultural and lifestyles of the people in brand context, while deciphering and delineating consumer behavior, even pointing significantly to the “black box models and rational choices,” would foster effectiveness and efficiency in the operational modules as well as impact on financial performance as unveiled from the qualitative data analysis and inferential statistics, thus emphasizing the significance of brand from the consumer side. It can be inferred that culture and traditional behavior play significant roles in brand perception considering the complexes, unpredictable trends, or patterns associated with consumers’ expressions and behavior in the context of a black box, rational and complex mixes, even justified by the result of the hypothesis testing of the composite attributes and evident from the ‘inference statistics and results, which gave a p–value exceeding 0.05. Conclusively, a CSR–based business model and structure can enhance change transitions from short– term to long– term goals, drive to sustainability, localized stabilization, and sustainable domains. Even brand interactions can be significantly enhanced by CSR, as ascertained by the relatively high R– squared value of 0.8826 and the justification of statistical significance from the factors as indicated by the ‘SEM results and analyses. Organizations can essentially adopt and apply the concept of bran translating to equity from CSR and consumer perceptions when embedded in their business model as a strategic tool in enhancing their performances and finances.
Social responsibility of business, Business ethics
This article presents a critique of ethics in the context of artificial intelligence (AI). It argues for the need to question established patterns of thought and traditional authorities, including core concepts such as autonomy, morality, and ethics. These concepts are increasingly inadequate to deal with the complexities introduced by emerging AI and autonomous agents. This critique has several key components: clarifying conceptual ambiguities, honestly addressing epistemic issues, and thoroughly exploring fundamental normative problems. The ultimate goal is to reevaluate and possibly redefine some traditional ethical concepts to better address the challenges posed by AI.
Eddie L. Ungless, Nikolas Vitsakis, Zeerak Talat
et al.
This whitepaper offers an overview of the ethical considerations surrounding research into or with large language models (LLMs). As LLMs become more integrated into widely used applications, their societal impact increases, bringing important ethical questions to the forefront. With a growing body of work examining the ethical development, deployment, and use of LLMs, this whitepaper provides a comprehensive and practical guide to best practices, designed to help those in research and in industry to uphold the highest ethical standards in their work.
Kaska Porayska-Pomsta, Wayne Holmes, Selena Nemorin
The transition of Artificial Intelligence (AI) from a lab-based science to live human contexts brings into sharp focus many historic, socio-cultural biases, inequalities, and moral dilemmas. Many questions that have been raised regarding the broader ethics of AI are also relevant for AI in Education (AIED). AIED raises further specific challenges related to the impact of its technologies on users, how such technologies might be used to reinforce or alter the way that we learn and teach, and what we, as a society and individuals, value as outcomes of education. This chapter discusses key ethical dimensions of AI and contextualises them within AIED design and engineering practices to draw connections between the AIED systems we build, the questions about human learning and development we ask, the ethics of the pedagogies we use, and the considerations of values that we promote in and through AIED within a wider socio-technical system.
Abstract Based on a total of 1,590 listed non-financial firms on the Taiwan Stock Exchange and the Taipei Exchanges covering the period of 2007 ~ 2020, this study examines whether a firm's capital structure is affected by its corporate social responsibility (CSR) performance. While existing research has explored the impact of a firm’s CSR performance on various financial and non-financial consequences, this study argues that firm engaging in CSR is putting greater emphasis on the financial and bankruptcy risks arising from the use of debt financing and to maintain firm’s sustainability, firm with better CSR performance tends to reduce the use of debt. Through descriptive statistics, correlation analysis and multiple regression estimation, principal outcome shows that firm with better CSR performance tends to use less debt financing and inter-temporally reduce the use of debt.
Social responsibility of business, Business ethics
This study is focused on the ethics of Artificial Intelligence and its application in the United States, the paper highlights the impact AI has in every sector of the US economy and multiple facets of the technological space and the resultant effect on entities spanning businesses, government, academia, and civil society. There is a need for ethical considerations as these entities are beginning to depend on AI for delivering various crucial tasks, which immensely influence their operations, decision-making, and interactions with each other. The adoption of ethical principles, guidelines, and standards of work is therefore required throughout the entire process of AI development, deployment, and usage to ensure responsible and ethical AI practices. Our discussion explores eleven fundamental 'ethical principles' structured as overarching themes. These encompass Transparency, Justice, Fairness, Equity, Non- Maleficence, Responsibility, Accountability, Privacy, Beneficence, Freedom, Autonomy, Trust, Dignity, Sustainability, and Solidarity. These principles collectively serve as a guiding framework, directing the ethical path for the responsible development, deployment, and utilization of artificial intelligence (AI) technologies across diverse sectors and entities within the United States. The paper also discusses the revolutionary impact of AI applications, such as Machine Learning, and explores various approaches used to implement AI ethics. This examination is crucial to address the growing concerns surrounding the inherent risks associated with the widespread use of artificial intelligence.
Aastha Pant, Rashina Hoda, Simone V. Spiegler
et al.
Ethics in AI has become a debated topic of public and expert discourse in recent years. But what do people who build AI - AI practitioners - have to say about their understanding of AI ethics and the challenges associated with incorporating it in the AI-based systems they develop? Understanding AI practitioners' views on AI ethics is important as they are the ones closest to the AI systems and can bring about changes and improvements. We conducted a survey aimed at understanding AI practitioners' awareness of AI ethics and their challenges in incorporating ethics. Based on 100 AI practitioners' responses, our findings indicate that majority of AI practitioners had a reasonable familiarity with the concept of AI ethics, primarily due to workplace rules and policies. Privacy protection and security was the ethical principle that majority of them were aware of. Formal education/training was considered somewhat helpful in preparing practitioners to incorporate AI ethics. The challenges that AI practitioners faced in the development of ethical AI-based systems included (i) general challenges, (ii) technology-related challenges and (iii) human-related challenges. We also identified areas needing further investigation and provided recommendations to assist AI practitioners and companies in incorporating ethics into AI development.
Researchers, practitioners, and policymakers with an interest in AI ethics need more integrative approaches for studying and intervening in AI systems across many contexts and scales of activity. This paper presents AI value chains as an integrative concept that satisfies that need. To more clearly theorize AI value chains and conceptually distinguish them from supply chains, we review theories of value chains and AI value chains from the strategic management, service science, economic geography, industry, government, and applied research literature. We then conduct an integrative review of a sample of 67 sources that cover the ethical concerns implicated in AI value chains. Building upon the findings of our integrative review, we recommend three future directions that researchers, practitioners, and policymakers can take to advance more ethical practices across AI value chains. We urge AI ethics researchers and practitioners to move toward value chain perspectives that situate actors in context, account for the many types of resources involved in co-creating AI systems, and integrate a wider range of ethical concerns across contexts and scales.
The emerging field of behavioral ethics has attracted much attention from scholars across a range of different disciplines, including social psychology, management, behavioral economics, and law. However, how behavioral ethics is situated in relation to more traditional work on business ethics within organizational behavior (OB) has not really been discussed yet. Our primary objective is to bridge the different literatures on ethics within the broad field of OB, and we suggest a full-fledged approach that we refer to as behavioral business ethics. To do so, we review the foundations and research foci of business ethics and behavioral ethics. We structure our review on three levels: the intrapersonal level, interpersonal level, and organizational level. For each level, we provide relevant research examples and outline where more research efforts are needed. We conclude by recommending future research opportunities relevant to behavioral business ethics and discuss its practical implications.
Katharina T. Paul, Bettina M. Zimmermann, Paolo Corsico
et al.
Vaccine uptake is essential to managing the ongoing COVID-19 pandemic, and vaccine hesitancy is a persistent concern. At the same time, both decision-makers and the general population have high hopes for COVID-19 vaccination. Drawing from qualitative interview data collected in October 2020 as part of the pan-European SolPan study, this study explores early and anticipatory expectations, hopes and fears regarding COVID-19 vaccination across seven European countries. We find that stances towards COVID-19 vaccines were shaped by personal lived experiences, but participants also aligned personal and communal interests in their considerations. Trust, particularly in expert institutions, was an important prerequisite for vaccine acceptance, but participants also expressed doubts about the rapid vaccine development process. Our findings emphasise the need to move beyond the study of factors driving vaccine hesitancy, and instead to focus on how people personally perceive vaccination in their particular social and political context.