AI Ethics Research Articles

Nurses' perspectives on privacy and ethical concerns regarding artificial intelligence adoption in healthcare

BackgroundWith the increasing integration of artificial intelligence (AI) technologies into healthcare systems, there is a growing emphasis on privacy and ethical considerations. Nurses, as frontline healthcare professionals, are pivotal in-patient care and offer valuable insights into the ethical implications of AI adoption. ObjectivesThis study aimed to explore nurses' perspectives on privacy and ethical concerns associated with the implementation of AI in healthcare settings. MethodsWe employed Van Manen's hermeneutic phenomenology as the qualitative research approach. Data were collected through purposive sampling from the December 7, 2023 to the January 15, 2024, with interviews conducted in Bengali. Thematic analysis was utilized following member checking and an audit trail. ResultsSix themes emerged from the research findings: Ethical dimensions of AI integration, highlighting complexities in incorporating AI ethically; Privacy challenges in healthcare AI, revealing concerns about data security and confidentiality; Balancing innovation and ethical practice, indicating a need to reconcile technological advancements with ethical considerations; Human touch vs. technological progress, underscoring tensions between automation and personalized care; Patient-centered care in the AI era, emphasizing the importance of maintaining focus on patients amidst technological advancements; and Ethical preparedness and education, suggesting a need for enhanced training and education on ethical AI use in healthcare. ConclusionsThe findings underscore the importance of addressing privacy and ethical concerns in AI healthcare development. Nurses advocate for patient-centered approaches and collaborate with policymakers and tech developers to ensure responsible AI adoption. Further research is imperative for mitigating ethical challenges and promoting ethical AI in healthcare practice.

Indigenous Data Sovereignty: A Catalyst for Ethical AI in Business

Indigenous Data Sovereignty: A Catalyst for Ethical AI in Business

Beyond Reproach: Navigating Usage, Detection, and Future Pathways of AI in Education

This essay critiques the emphasis on detecting artificial intelligence (AI) usage in student submissions and advocates for a shift towards the meaningful integration of AI in education. Citing data from Turnitin, it highlights the significant yet understated prevalence of AI in academic work. The discussion underscores the ideological, detection, and moral challenges associated with AI in education, arguing for a reconceptualization of assessment and pedagogy to accommodate AI tools ethically and effectively. It calls for collaborative efforts to redesign curricula and assessments, ensuring educators and students are equipped to navigate the evolving educational landscape. The essay concludes by emphasizing the necessity of preparing graduates for a future in which AI plays a central role in learning and professional practice.Keywords: AI usage detection, ethical AI integration, academic integrity, future of AI in education

Navigating the Grey Area: Students' Ethical Dilemmas in Using AI Tools for Coding Assignments

<div align="center"><table width="100%" border="0" cellspacing="0" cellpadding="0"><tbody><tr><td valign="top" width="605"><p>Integrating artificial intelligence (AI) in higher education, particularly in coding assignments for Information Technology (IT) students, represents a rapidly evolving research area with significant implications for academic practices and integrity. This study focuses on the ethical challenges faced by IT students when using AI tools like ChatGPT for coding assignments. Despite the growing use of AI in education, there is a notable gap in understanding how students perceive and navigate the ethical dilemmas associated with these technologies. To address this gap, this study employed a thematic analysis of qualitative data collected from interviews with IT students. The results reveal a complex landscape of ethical considerations, including issues of originality, academic integrity, and the potential for misuse of AI tools. Students reported challenges in balancing the benefits of AI assistance with the need to maintain independent learning and adhere to ethical standards. The implications of this research are significant for educators, institutions, and policymakers. Understanding the ethical challenges students face can inform the development of more effective teaching strategies, assessment methods, and institutional policies. This study contributes to the ongoing dialogue about AI ethics in academia, providing valuable insights for creating an educational environment that leverages the power of AI while upholding the principles of academic integrity and meaningful learning.</p></td></tr></tbody></table></div>

Viewpoint: A problematization of Artificial Intelligence Ethics: deliberative democracy versus agonistic pluralism

Viewpoint: A problematization of Artificial Intelligence Ethics: deliberative democracy versus agonistic pluralism

Synergizing AI and business: Maximizing innovation, creativity, decision precision, and operational efficiency in high-tech enterprises

The study was conducted on 125 US based high-tech firms from software engineering, hardware production, biotechnology, and telecommunications. Senior-level executives, including CEOs, board members, and CTOs, provided insights through structured questionnaires. Key findings indicate that AI adoption significantly enhances organizational capabilities in terms of employees’ innovation, creativity, and experimentation. Moreover, AI adaptation positively impacts decision making thus yielding more accurate and timely valuable decisions. These findings contribute to both theoretical understanding and managerial practice by guiding strategic investments in AI technologies, fostering innovation, and advocating for ethical AI deployment practices. Future study should examine longitudinal impacts across industries and regions to optimize benefits and minimize risks in digital transformation efforts. It should also integrate qualitative methods for deeper insights and appropriate AI governance systems.

Demystifying Artificial Intelligence for Health Care Professionals: Continuing Professional Development as an Agent of Transformation Leading to Artificial Intelligence-Augmented Practice.

The rapid rise of artificial intelligence (AI) is transforming society; yet, the education of health care providers in this field is lagging. In health care, where AI promises to facilitate diagnostic accuracy, and allow for personalized treatment, bridging the knowledge and skill gaps for providers becomes vital. This article explores the challenges of AI education, such as the emergence of self-proclaimed experts during the pandemic, and the need for comprehensive training in AI language, mechanics, and ethics. It advocates for a new breed of health care professionals who are both practitioners and informaticians, who are capable through initial training or through continuing professional development of harnessing AI's potential. Interdisciplinary collaboration, ongoing education, and incentives are proposed to ensure health care benefits from AI's trajectory. This perspective article explores the hurdles and the imperative of creating educational programming designed specifically to help health care professionals augment their practice with AI.

AI in HR: A Comprehensive Analysis and Framework for Success

Artificial Intelligence (AI) is transforming the field of Human Resources (HR), revolutionizing how organizations manage their workforce. This paper provides a comprehensive analysis of AI's impact on HR practices, from recruitment and talent management to employee engagement and decision-making. It explores the benefits and challenges of AI adoption in HR and offers a practical framework for successful implementation. By examining real-world case studies and current trends, this paper equips HR professionals and organizational leaders with the knowledge and strategies needed to harness the power of AI for more effective and data- driven HR management. Key Words: AI in HR, HR automation, Talent management, Employee engagement, Ethical AI, HR analytics

The Multilateral Integration of Blockchain, Ethical Packet Sniffing and AI for Cybersecurity in BRICS Countries

This policy brief proposes that the BRICS (Brazil, Russia, India and South Africa) should plan and coordinate on ways to mitigate cybersecurity risks on a multilateral level. The BRICS countries are ideal for such a meta-governance mechanism which could coordinate toward the circumvention of some cyber risks. This Policy brief proposes that there should be an integration of blockchain technologies, packet sniffing technologies and AI detection tools to help mitigate emerging cybersecurity risks. The policy brief outlines the risks and challenges prevalent in this current climate, whilst also proposing potential remedies sourced from rigorous academic studies. The precise amendments include the synthesised mechanism of blockchain-based internet registries, packet sniffing technologies AI verification tools and capacity building to aid in the mitigation of cybersecurity risks. In 2007, a cyber-attack in Brazil plunged more than 3 million people into darkness. Cyberattacks collectively cost the BRICS countries $50.3bn in 2013. These funds could have been reinvested into the economy. BRICS needs the rapid technological integration of cyber-crime mitigation tools, tools which this policy brief will outline.

ChatGPT-Empowered Writing Strategies in EFL Students’ Academic Writing: Calibre, Challenges and Chances

ChatGPT’s remarkable ability to produce academic texts has generated significant interest in educational and academic circles. This study provides a specific overview of ChatGPT’s current usage and explores its potential applications, limitations, and implications in English academic writing for EFL students, who often face challenges in language proficiency, content organization, and critical thinking. Using a mixed-methods research approach, this study employed a CSE-based questionnaire and focus group interviews to investigate how ChatGPT can empower academic writing strategies (WS) and how respondents perceive its assistance. Data was collected from 60 Chinese university juniors majoring in English. Quantitative data were analyzed using descriptive statistics and regression analysis, while qualitative data underwent thematic analysis. Findings indicate that ChatGPT can help students apply academic WS more effectively by comprehending research trends, generating writing outlines, enriching writing content, synthesizing literature, and refining papers. However, issues such as potential plagiarism, inaccurate output, improper citations, and the digital gap between users and non-users must be addressed. The study suggests that while ChatGPT-empowered writing can better equip academic WS in planning, composing, and revising, respectively, it is crucial to scrutinize the quality of AI-generated texts. Further research will be urgently expected regarding ChatGPT’s long-term impact on academic integrity, the development of educational policies for ethical AI use, and the integration of ChatGPT into pedagogical approaches to enhance EFL students’ writing and critical thinking.

Ethical considerations in AI use for SMEs and supply chains: Current challenges and future directions

The integration of Artificial Intelligence (AI) in Small and Medium-sized Enterprises (SMEs) and supply chains has revolutionized operational efficiencies and decision-making processes. This review paper aims to explore the ethical implications of AI adoption in these sectors, identifying current challenges and proposing future directions for ethical AI deployment. Through an extensive review of existing literature, the paper examines key ethical concerns such as data privacy, bias in AI algorithms, transparency, and the socio-economic impact on the workforce. The findings indicate that SMEs face unique ethical challenges due to their limited resources and expertise, which exacerbate issues related to AI implementation. Additionally, supply chains grapple with transparency and accountability, necessitating immediate attention to ensure ethical practices. The review concludes that establishing a robust ethical framework is crucial for guiding AI integration in SMEs and supply chains. It recommends the development of standardized ethical guidelines, enhanced stakeholder engagement, and increased investment in AI literacy and infrastructure. Future research should focus on creating adaptable ethical models that evolve alongside technological advancements and industry needs, ensuring that AI contributes to sustainable and equitable growth. This paper contributes to the ongoing discourse on ethical AI, offering actionable insights for policymakers, business leaders, and researchers dedicated to fostering responsible AI practices in SMEs and supply chains. Keywords: Ethical AI, SMEs (Small and Medium-sized Enterprises), Supply Chains, Algorithmic Bias, Data Privacy, Transparency, Accountability, AI Trust, Regulatory Compliance, Stakeholder Engagement, Job Displacement, Explainable AI (XAI), Workforce Reskilling, Sustainable AI Practices, AI Ethics Frameworks.

The Role of Synthetic Data in Advancing AI Models: Opportunities, Challenges, and Ethical Considerations

The rapid evolution of artificial intelligence (AI) relies on access to large, diverse, and high-quality datasets to train and evaluate models. However, acquiring real-world data can be challenging due to privacy concerns, data scarcity, and high costs. Synthetic data—artificially generated data that mimics real data characteristics—offers a promising solution to these issues. This paper explores the role of synthetic data in advancing AI models by analyzing its potential to overcome data limitations, accelerate innovation, and enhance model robustness. We examine current opportunities where synthetic data can provide value, discuss technical challenges such as data fidelity and scalability, and consider ethical implications, including privacy, transparency, and potential biases. By addressing these factors, synthetic data can become an integral component in building more efficient, ethical, and reliable AI systems. This article aims to provide a comprehensive overview of synthetic

The Role of Artificial Intelligence in Achieving the United Nations Sustainable Development Goals

The United Nations' 2030 Agenda for Sustainable Development aims to tackle poverty, inequality, and environmental degradation and foster economic growth. This study investigates the transformative potential of artificial intelligence (AI) in achieving these Sustainable Development Goals (SDGs). Analyzing data from 44 sources, the research highlights AI's capacity to address critical challenges in healthcare, education, environmental management, economic growth, and gender equality. AI applications in renewable energy, waste management, disease detection, personalized education, and gender equality are examined. The study also emphasizes the ethical issues associated with AI, such as algorithmic bias, data privacy breaches, and job displacement. To fully leverage AI's potential, it is essential to develop intelligent automation governance systems, foster interdisciplinary research combining AI and sustainability, and promote public-private partnerships. Additionally, enhancing public AI literacy and implementing eco-friendly AI policies are crucial. The study advocates for a holistic ethical framework to maximize AI's benefits while mitigating risks, promoting cross-disciplinary collaboration, and establishing ethical AI standards. By doing so, AI can significantly contribute to a more inclusive, equitable, and sustainable future.

Factors affecting citizen intention toward AI acceptance and adoption: the moderating role of government regulations

Purpose This paper aims to explore factors impacting citizen intention toward artificial intelligence (AI) adoption, considering government regulation as a moderating variable. It focuses on the Palestinian Cellular Communications Sector in Gaza Strip, providing insights into the citizen-AI relationship dynamics. The research contributes to enhancing comprehension of AI technology from clients’ perspective. Design/methodology/approach To test the hypotheses, a questionnaire was used in an empirical study to collect primary data. In total, 347 Palestinian citizens responded to the survey. Findings The findings of this paper reveal that perceived usefulness, perceived ease of use, perceived risks, social influence, user experience and privacy and security concerns significantly influence citizen intention toward AI adoption. Furthermore, government regulations as a moderating variable strengthen the impact of perceived usefulness, perceived ease of use, perceived risks, social influence, user experience and privacy and security concerns on citizen intention toward AI acceptance and adoption. Thus, further research should explore specific domains and cultural contexts to gain a more comprehensive understanding of the factors shaping acceptance and adoption. Research limitations/implications The findings of the study should be understood in the context of their limitations. First, the study ignored cultural or domain-specific subtleties in favor of generic characteristics, which calls for more research in these particular circumstances. Second, relying on self-reported data might result in biases and limitations due to subjectivity in reporting, indicating the necessity for alternate data gathering methods and approaches in future research. Practical implications Policymakers, developers and organizations working to promote the acceptability and implementation of AI applications should consider the practical implications of this study’s results. To secure the long-term use of AI technologies in a responsible and user-centric way, policymakers should give priority to public education and awareness, user-centered design and ethical AI development techniques. They should also stimulate partnerships and create monitoring systems. Originality/value This paper investigates the originality of factors that influence citizen intention toward AI acceptance and adoption. It uniquely examines the moderating role of government regulations in shaping this intention. By addressing this novel aspect, the paper contributes to advancing our understanding of the complex dynamics surrounding citizen intentions toward AI applications.

Exploring AI's Role in Supporting Diversity and Inclusion Initiatives in Multicultural Marketplaces

This paper explores the relationship between diversity, inclusion, and artificial intelligence (AI) in multicultural workplaces and markets. Growing recognition of the value of diversity and inclusion (D&I) initiatives is changing organizational practices globally. Despite progress, challenges such as unconscious bias, resistance to change, and difficulty in measuring progress still exist.This study is based on a comprehensive literature review that adheres to academic ethical standards. These findings highlight the potential of AI to improve recruitment processes, personalize marketing strategies, and develop inclusive technologies. However, challenges such as bias in AI algorithms and limited data diversity need to be addressed.The paper emphasizes the need for ethical AI frameworks, diverse representation in AI development, and transparency in the use of AI to promote justice. AI has the potential to foster a more equitable society by encouraging diversity and inclusion. Further research is needed to explore the long-term impact of AI on diversity and inclusion and to develop ethical AI frameworks tailored to different industries and cultural contexts.The study also explores how AI can support D&I initiatives by providing data-driven insights, automating processes, and offering personalized interventions to reduce bias and increase inclusivity. By reviewing recent research and case studies, this paper offers practical recommendations for leveraging AI in D&I efforts, aiming to build a more inclusive and equitable workplace culture.

Ethical approaches in designing autonomous and intelligent systems: a comprehensive survey towards responsible development

AbstractOver the past decade, significant progress in artificial intelligence (AI) has spurred the adoption of its algorithms, addressing previously daunting challenges. Alongside these remarkable strides, there has been a simultaneous increase in model complexity and reliance on opaque AI models, lacking transparency. In numerous scenarios, the systems themselves may necessitate making decisions entailing ethical dimensions. Consequently, it has become imperative to devise solutions to integrate ethical considerations into AI system development practices, facilitating broader utilization of AI systems across various domains. Research endeavors should explore innovative approaches to enhance ethical principles in AI systems, fostering greater transparency, accountability, and trustworthiness. Upholding fundamental individual rights, human dignity, autonomy, privacy, equality, and fairness, while mitigating potential harm, remains paramount. Considering ethical values and ensuring compliance with ethical requirements throughout the development lifecycle of autonomous and intelligent systems nurture trust and reliability in their utilization. Ethical considerations should be ingrained within organizational procedures guiding AI research activities, establishing robust frameworks that address ethical concerns and reflect the ethical implications of AI-based systems. This paper presents an overview of ethical approaches and processes aimed at integrating ethical considerations into AI system development practices. It underscores the significance of ethical frameworks in fostering ethical AI implementation and ensuring the ethical integrity of AI technologies.

Framing AI Ethics in Public Discourse: A Critical Discourse Analysis of Media Coverage on AI in Child Protection

Framing AI Ethics in Public Discourse: A Critical Discourse Analysis of Media Coverage on AI in Child Protection

Incorporating AI into the Inner Circle of Emotional Intelligence for Sustainability

This paper delves into the fusion of artificial intelligence (AI) and emotional intelligence (EQ) by analyzing the frameworks of international sustainability agendas driven by UNESCO, WEF, and UNICEF. It explores the potential of AI integrated with EQ to effectively address the Sustainable Development Goals (SDGs), with a focus on education, healthcare, and environmental sustainability. The integration of EQ into AI use is pivotal in using AI to improve educational outcomes and health services, as emphasized by UNESCO and UNICEF’s significant initiatives. This paper highlights the evolving role of AI in understanding and managing human emotions, particularly in personalizing education and healthcare. It proposes that the ethical use of AI, combined with EQ principles, has the power to transform societal interactions and decision-making processes, leading to a more inclusive, sustainable, and healthier global community. Furthermore, this paper considers the ethical dimensions of AI deployment, guided by UNESCO’s recommendations on AI ethics, which advocate for transparency, accountability, and inclusivity in AI developments. It also examines the World Economic Forum’s insights into AI’s potential to revolutionize learning and healthcare in underserved populations, emphasizing the significance of fair AI advancements. By integrating perspectives from prominent global organizations, this paper offers a strategic approach to combining AI with EQ, enhancing the capacity of AI systems to meaningfully address global challenges. In conclusion, this paper advocates for the establishment of a new Sustainable Development Goal, SDG 18, focused on the ethical integration of AI and EQ across all sectors, ensuring that technology advances the well-being of humanity and global sustainability.

Unpacking the role of AI ethics online education for science and engineering students

BackgroundAs artificial intelligence (AI) technology rapidly advances, it becomes imperative to equip students with tools to navigate through the many intricate ethical considerations surrounding its development and use. Despite growing recognition of this necessity, the integration of AI ethics into higher education curricula remains limited. This paucity highlights an urgent need for comprehensive ethics education initiatives in AI, particularly for science and engineering students who are at the forefront of these innovations. Hence, this research investigates the role of an online explicit-reflective learning module in fostering science and engineering graduate students' ethical knowledge, awareness, and problem-solving skills. The study’s participants included 90 graduate students specializing in diverse science and engineering research tracks. Employing the embedded mixed-methods approach, data were collected from pre- and post-intervention questionnaires with closed-ended and open-ended questions.ResultsThe study's results indicate that the online explicit-reflective learning module significantly enhanced students' knowledge of AI ethics. Initially, students exhibited a medium–high level of perceived ethical awareness, which saw a modest but statistically significant enhancement following the participation. Notably, a more distinct increase was observed in students' actual awareness of ethical issues in AI, before and after the intervention. Content analysis of students’ responses to the open-ended questions revealed an increase in their ability to identify and articulate concerns relating to privacy breaches, the utilization of flawed datasets, and issues of biased social representation. Moreover, while students initially displayed limited problem-solving abilities in AI ethics, a considerable enhancement in these competencies was evident post-intervention.ConclusionsThe study results highlight the important role of explicit-reflective learning in preparing future professionals in science and engineering with the skills necessary for ethical decision-making. The study highlights the need for placing more emphasis not only on students’ ability to identify AI-related ethical issues but also on their capacity to resolve and perhaps mitigate the impact of such ethical dilemmas.

A Reasoning and Value Alignment Test to Assess Advanced GPT Reasoning

In response to diverse perspectives on artificial general intelligence (AGI), ranging from potential safety and ethical concerns to more extreme views about the threats it poses to humanity, this research presents a generic method to gauge the reasoning capabilities of artificial intelligence (AI) models as a foundational step in evaluating safety measures. Recognizing that AI reasoning measures cannot be wholly automated, due to factors such as cultural complexity, we conducted an extensive examination of five commercial generative pre-trained transformers (GPTs), focusing on their comprehension and interpretation of culturally intricate contexts. Utilizing our novel “Reasoning and Value Alignment Test,” we assessed the GPT models’ ability to reason in complex situations and grasp local cultural subtleties. Our findings have indicated that, although the models have exhibited high levels of human-like reasoning, significant limitations remained, especially concerning the interpretation of cultural contexts. This article also explored potential applications and use-cases of our Test, underlining its significance in AI training, ethics compliance, sensitivity auditing, and AI-driven cultural consultation. We concluded by emphasizing its broader implications in the AGI domain, highlighting the necessity for interdisciplinary approaches, wider accessibility to various GPT models, and a profound understanding of the interplay between GPT reasoning and cultural sensitivity.