Ethical Governance Research Articles

An ESG-Compliant Framework for Fraud Detection in Online Payments Using Data Privacy and Machine Learning

Purpose: The purpose of this paper is to analyze the role of machine learning (ML) in fraudulent online payment transaction detection across industries, with a specific focus on integrating Environmental, Social, and Governance (ESG) principles to bring sustainability and ethics in fraud detection. Methodology: This study reviews the effectiveness of machine learning (ML) techniques in real-time fraud detection, presenting the efficiency of different ML techniques across industries and how those techniques can be modified to apply the principles of ESG. It checks on ethical practices concerning data, compliance with data privacy, and sustainable management, further investigating how effectively ML-driven frameworks can support fraud detection without compromising the standards of ESG. Findings: The study finds that integrating ESG principles within machine learning frameworks for fraud detection enhances both the effectiveness and ethical alignment of these systems. ML models not only support real-time fraud detection but also reinforce sustainable data management and governance practices, providing businesses with an advanced approach to mitigating cyber risks while upholding ESG commitments. Unique Contribution to Theory, Practice, and Policy: This paper contributes by advancing ESG-integrated frameworks for fraud detection, offering a sustainable and ethical model for using ML in financial systems. In practice, it provides actionable insights for industries seeking to align fraud prevention with ESG goals. The paper also suggests policy considerations, advocating for stronger ethical standards and data governance in ML applications for fraud detection.

Investigating Adoption Determinants, Obstacles, and Interventions for AI Implementation in Emirati Media Organizations

This research explores the integration and impact of artificial intelligence (AI) within Emirati media organizations, focusing on adoption determinants, obstacles, and interventions. Utilizing a mixed-methods approach, the study incorporates qualitative data from 21 in-depth interviews with media professionals and a thematic analysis of 30 scholarly articles published between 2019 and 2024. The research aims to provide a nuanced understanding of AI's transformative effects on the UAE media landscape. Key findings reveal that AI is significantly enhancing content creation, distribution, and audience engagement processes within Emirati media organizations. AI technologies such as machine learning, natural language processing, and predictive analytics are being leveraged to improve operational efficiency, streamline workflows, and deliver personalized content to audiences. These advancements are driving competitive advantages and elevating the overall quality of media output. Despite these benefits, several challenges hinder widespread AI adoption. Technological barriers, including limited access to advanced AI tools and infrastructure, pose significant obstacles. Additionally, there is a pronounced shortage of skilled personnel capable of implementing and managing AI systems, which exacerbates concerns over job displacement and workforce anxiety. Ethical considerations, such as ensuring unbiased AI algorithms and protecting user privacy, are also critical issues that require attention. The study underscores the importance of continuous training and upskilling for media professionals to adapt to the evolving technological landscape. It highlights the role of robust ethical guidelines and governance frameworks in promoting responsible AI use. Government support, through targeted policies, funding initiatives, and incentives, is identified as a crucial factor in facilitating AI integration and addressing adoption barriers. The research concludes by providing strategic recommendations for media organizations and policymakers. It advocates for the development of comprehensive AI adoption roadmaps that include capacity-building initiatives, ethical oversight, and collaborative efforts between industry stakeholders. By addressing these areas, Emirati media organizations can harness the full potential of AI to drive innovation, improve audience engagement, and maintain competitiveness in a rapidly digitizing global media environment. This study contributes to the growing body of knowledge on AI in media, offering valuable insights into the specific context of the UAE. It provides a foundation for future research on AI's role in media and serves as a guide for organizations seeking to navigate the complexities of AI adoption.

Behavioral strategies for reducing corruption: from regulation to choice architecture

Abstract Traditionally, corruption is seen as a rational pursuit of profit, focusing on personal gain. However, this view overlooks other influences. This paper focuses on the behavioral aspects of corruption, providing a deeper understanding of its complexities, and addressing the factors overlooked by conventional approaches. Reviewing some of the literature, we highlight how researchers have approached corruption from the perspective of behavioral sciences. Additionally, we examine how the emerging discipline of Behavioral Public Policy (BPP) employs innovative methods to reduce corrupt practices, offering new strategies that transcend traditional perspectives. Our paper innovates by demonstrating how corruption can be reduced by substituting traditional regulations with nonregulatory tools like nudges and sludge audits, or by leveraging digital choice architectures to minimize human-to-human interactions, known corruption enablers. By reducing regulations and administrative red tape, and introducing digital frameworks, these tools simplify processes minimizing opportunities for corrupt behavior. In this paper, we aim to infuse corruption research with a behavioral twist, a digital approach, and a deregulatory perspective, offering policymakers an alternative path to foster transparency, accountability and ethical governance. While this approach will not completely eradicate corruption, it strives to show how BPP can reduce its occurrences.

Exploring administrative evil, the ethics of dissent, and guerrilla government in The Good Place

This article uses the comedy television series The Good Place as a starting point to theoretically explore the value of guerrilla government as a measure to disrupt administrative evil. Drawing from the literature of administrative evil and Rosemary O’Leary’s work on the ethics of dissent and guerrilla government, this article considers the personal ethics and organizational cultural motivations for dissent as well as how administrators work to disrupt administrative evil while navigating through various strategies including loyalty, neglect, voice, and exit. This article demonstrates how popular media can be used as a means of theorizing for public administration scholars as well as a space where ideas related to public administration can apply existing theories in a method that can be engaging to mainstream audiences. The paper concludes with a proposed model of how administrative evil and guerrilla government may be conceptualized to interact with one another as well as potential areas of opportunity for administrators to practice dissent within the broader maze of bureaucracy administrative evil can become lost amongst.

Artificial Intelligence in Morocco: Towards Holistic, Responsible and Ethical National AI Strategy for Moroccan Competitiveness and Strategic Intelligence

This paper analyses current achievements and emerging landscape of artificial intelligence in Morocco. It explores also the various challenges and opportunities related to the development of an AI ecosystem that facilitates the emergence of an agile, holistic, responsible, ethical, and forward-looking national artificial intelligence strategy that supports Morocco's global competitiveness and its strategic intelligence. Based on a methodological triangulation approach, we combined a documentary approach focused on a literature reviews and international benchmarks of national AI policies and strategies. In addition, we have proposed a conceptual model that outlines the essential elements and key enablers and drivers of the national AI strategy for Morocco. We have called it “LAFBAH AI Framework” focusing on Leadership & Vision, Adaptive Governance, Forward-thinking, Breakthrough Innovations, Agility in Implementation, and Human centred approach. This model is predictive and prescriptive, and most importantly, aligned with the Moroccan priorities and strategic orientations of Morocco’s New Development Model. The study's findings show that Morocco possesses strategic assets that can help it establish itself as an AI hub for Africa and bolster its leadership and digital influence. These assets mainly include the country's international commitment to AI, its participation in AI cooperation programs, a dynamic creation of institutions and university centres dedicated to AI and the start of a virtuous public and political dialogue on the subject involving the private sector, academia and civil society.Our research argues in favour of a holistic and integrated approach to AI in Morocco, which combines AI Governance with technological innovation, ethical and societal considerations to promote sustainable and inclusive development and enhance Moroccan competitiveness. It also demonstrates the urgent need to design and ensure the implementation of an innovative, adapted and integrated national AI strategy for Morocco. This national AI strategy should be designed as an integrative, agile, dynamic framework with a clear and integrated vision, ambitious strategic objectives, relevant priorities and choices and key pillars of AI such as responsible, ethical and innovative governance and strong ecosystem enablers, collaborative research and development, AI talent and skills, sufficient data and infrastructure.We have also designed the fundamental and necessary milestones for a new ecosystem of artificial intelligence in Morocco focused on the imperatives of the knowledge society, the digital, health, food and energy sovereignties of the country, while aspiring to be a hub of artificial intelligence in Africa.

The Role of AI in Personalizing Insurance Policies

This article analyzes the transformative impact of artificial intelligence on the insurance industry through four key innovations. It examines how AI has enabled real-time risk assessment and dynamic pricing through personalized policy optimization, integrated terabytes of daily customer data for precise underwriting, implemented advanced analytics frameworks for enhanced fraud detection and customer segmentation, and automated operations for improved efficiency. The findings demonstrate that AI implementation has achieved an 82% improvement in risk prediction accuracy, reduced operational costs by 67%, and increased customer satisfaction by 76%. However, these technological advancements necessitate robust ethical governance frameworks, particularly in data privacy and algorithmic fairness. The research comprehensively analyzes AI's role in reshaping insurance operations while emphasizing the critical balance between technological innovation and ethical implementation. These insights offer valuable guidance for insurance providers pursuing digital transformation while maintaining regulatory compliance and customer trust.

SEGURANÇA PÚBLICA, VIGILANTISMO E NOVAS TECNOLOGIAS: O RECONHECIMENTO FACIAL COMO FERRAMENTA DE GARANTIA DE DIREITOS

This study analyzes the use of facial recognition technologies as a public security tool, addressing its benefits and associated ethical and legal challenges. The research highlights that, although the technology can improve efficiency in identifying suspects and solving crimes, especially during large events, significant concerns remain regarding privacy and discrimination. In Brazil, inadequate implementation and the lack of specific regulations reinforce criticisms of the unequal application of the technology, particularly in vulnerable communities. The study suggests that public acceptance of facial recognition depends on transparency, proper oversight, and alignment with legal frameworks, such as the LGPD. Only through clear and ethical governance will it be possible to balance the benefits of public security with the protection of fundamental rights.

Ethics dumping in artificial intelligence

Artificial Intelligence (AI) systems encode not just statistical models and complex algorithms designed to process and analyze data, but also significant normative baggage. This ethical dimension, derived from the underlying code and training data, shapes the recommendations given, behaviors exhibited, and perceptions had by AI. These factors influence how AI is regulated, used, misused, and impacts end-users. The multifaceted nature of AI’s influence has sparked extensive discussions across disciplines like Science and Technology Studies (STS), Ethical, Legal and Social Implications (ELSI) studies, public policy analysis, and responsible innovation—underscoring the need to examine AI’s ethical ramifications. While the initial wave of AI ethics focused on articulating principles and guidelines, recent scholarship increasingly emphasizes the practical implementation of ethical principles, regulatory oversight, and mitigating unforeseen negative consequences. Drawing from the concept of “ethics dumping” in research ethics, this paper argues that practices surrounding AI development and deployment can, unduly and in a very concerning way, offload ethical responsibilities from developers and regulators to ill-equipped users and host environments. Four key trends illustrating such ethics dumping are identified: (1) AI developers embedding ethics through coded value assumptions, (2) AI ethics guidelines promoting broad or unactionable principles disconnected from local contexts, (3) institutions implementing AI systems without evaluating ethical implications, and (4) decision-makers enacting ethical governance frameworks disconnected from practice. Mitigating AI ethics dumping requires empowering users, fostering stakeholder engagement in norm-setting, harmonizing ethical guidelines while allowing flexibility for local variation, and establishing clear accountability mechanisms across the AI ecosystem.

Artificial Intelligence in Governance: Opportunities, Challenges, and Ethical Implications for Public Administration

The integration of Artificial Intelligence (AI) in the public sector presents both unprecedented opportunities and significant challenges for governments worldwide. This article examines the multifaceted impact of AI on public administration, exploring its applications in service delivery, urban planning, public safety, and administrative efficiency. While AI offers substantial benefits, including enhanced decision-making, cost savings, and improved citizen services, it also raises critical concerns regarding bias, privacy, accountability, and workforce displacement. This article provides a comprehensive analysis of the ethical considerations surrounding AI deployment in governance, emphasizing the need for transparency, inclusivity, and human oversight. By critically evaluating both the promises and perils of AI in public sector operations, this article contributes to the ongoing discourse on responsible AI adoption in government. The findings underscore the importance of developing robust governance frameworks that can harness AI's potential while safeguarding citizens' rights and ensuring equitable service delivery. As governments navigate the AI revolution, this article offers insights into strategies for balancing technological advancement with ethical governance, paving the way for a more efficient, fair, and responsive public sector.

Assessing the Efficacy of Gene-Drive Technology in Reducing Malaria Transmission in Sub-Saharan Africa: Current Progress and Future Prospects

Malaria continues to pose a significant public health challenge in Sub-Saharan Africa, necessitating innovative solutions to combat its transmission. This review examined the efficacy of gene-drive technology as a novel approach to reducing malaria transmission through genetic modifications of Anopheles mosquitoes. Utilizing a comprehensive literature review and analysis of experimental studies and pilot projects, we assessed the mechanisms of gene drives, including population suppression and replacement strategies. The findings indicated that gene-drive technology has the potential to significantly alter mosquito populations, thereby diminishing the burden of malaria. However, challenges such as ecological concerns, regulatory complexities, and public acceptance must be addressed for successful implementation. The integration of gene drives with existing malaria control measures, collaborative research efforts, and robust ethical governance is crucial for maximizing effectiveness and ensuring sustainable outcomes. Furthermore, monitoring and evaluation systems are essential for assessing the safety and efficacy of gene-drive initiatives. This review underscored the transformative potential of gene-drive technology in malaria prevention, advocating for continued dialogue among stakeholders to navigate the complexities associated with its application in Sub-Saharan Africa. Keywords: Gene-drive technology, Malaria transmission, Anopheles mosquitoes, Public health, Sub-Saharan Africa.

Public Anxieties About AI: Implications for Corporate Strategy and Societal Impact

This research critically examines the underlying anxieties surrounding artificial intelligence (AI) that are often concealed in public discourse, particularly in the United Kingdom. Despite an initial reluctance to acknowledge AI-related fears in focus groups, where 86% of participants claimed no significant concerns, further exploration through anonymous surveys and interviews uncovered deep anxieties about AI’s impact on job security, data privacy, and ethical governance. The research employed a mixed-methods approach, incorporating focus groups, a survey of 867 participants, and 53 semi-structured interviews to investigate these anxieties in depth. The study identifies key sources of concern, ranging from the fear of job displacement to the opacity of AI systems, particularly in relation to data handling and the control exerted by corporations and governments. The analysis reveals that anxieties are not evenly distributed across demographics but rather shaped by factors such as age, education, and occupation. These findings point to the necessity of addressing these anxieties to foster trust in AI technologies. This study highlights the need for ethical and transparent AI governance, providing critical insights for policymakers and organisations as they navigate the complex socio-technical landscape that AI presents.

Artificial intelligence for internal communication: Strategies, challenges, and implications

This qualitative study explores the intersection of artificial intelligence (AI) and internal communication, investigating AI applications, challenges, and best practices. In-depth interviews with 20 senior communication professionals examined perceptions of AI’s impact on internal communication processes and outcomes. Key findings indicate AI improves internal communication efficiency, information flow, listening capability, and employee experience. However, challenges include lack of AI knowledge among employees, fears about job security andbias, and concerns about authenticity loss. To enable effective AI adoption for internal communication, organizations need education and training, a “co-piloting” approach between humans and machines, transparent communication, ethical governance, and an open culture of experimentation. This research makes important theoretical contributions by illuminating AI’s transformative potential for internal communication. It also offers practical insights to guide organizations in strategically leveraging AI to elevate internal communication.

CSR investments and innovation – aligning and creating shared value

This research aims to advance the field of Corporate Social Responsibility (CSR) and innovation by exploring how CSR investments can drive product and service innovations, creating value for both the firm and its broader stakeholders. Specifically, it examines the relationship between CSR initiatives and their influence on CSR investments, as well as the resulting impact on innovation in products or services that contribute to shared value creation. The proposed framework is tested across three firm sizes—small, medium, and large—using a sample of 410 businesses within the Australian economy. The analysis was conducted using AMOS version 28, which established appropriate measurement indicators and revealed significant direct and indirect effects for the full sample. Additionally, the multi-group analysis explored nuanced relationships based on firm size.By investigating a relatively unexplored Australian context, the paper makes significant contributions by addressing the limited research on internal (employee) CSR, external (environmental) CSR, and ethical (governance) responsibility, examining their impacts on CSR investments. Furthermore, it explores how CSR investments influence innovation to create shared value and highlights the moderating effects of different firm sizes on the relationships between the antecedents, CSR investments, and innovation. The paper concludes by discussing the theoretical and practical implications of the findings, as well as outlining directions for future research and acknowledging limitations.

Comprehensive Exploration of CRISPR and Gene Editing Technologies: Applications, Ethical Considerations, and Future Implications in Genetic Research

CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) and other gene-editing technologies have revolutionized genetic research by enabling precise, targeted modifications of DNA sequences. This paper provides a comprehensive exploration of CRISPR technology, detailing its development, mechanism of action, and versatility in diverse applications. From advancements in medicine, including therapeutic interventions for genetic disorders, to innovations in agriculture aimed at enhancing crop resilience and yield, CRISPR's transformative potential is vast. However, the rapid evolution of gene editing presents significant ethical and societal challenges, particularly concerning human germline editing, ecological impacts, and issues of accessibility and equity. This paper examines these ethical considerations, emphasizing the need for robust regulatory frameworks and responsible scientific practices. It also projects the future trajectory of gene editing technologies, speculating on emerging trends, possible breakthroughs, and the global implications of CRISPR in fields such as personalized medicine, synthetic biology, and biotechnology. By critically analyzing current applications and addressing ethical concerns, this study aims to provide a balanced perspective on CRISPR's potential to reshape genetic research while advocating for ethical governance and public engagement in its ongoing development. CRISPR’s ability to target specific genes with high accuracy has made it an invaluable tool not only in research laboratories but also in clinical settings, where it shows promise in treating previously incurable diseases. Recent advancements have extended CRISPR’s applications beyond simple gene knockout, allowing for base editing, prime editing, and epigenetic modifications that expand the possibilities for genetic correction and enhancement. As scientists explore using CRISPR in complex organisms, the precision and control required for safe and effective treatments become a key focus, particularly in addressing off-target effects that could lead to unintended genetic consequences.

A policy framework on AI usage in developing countries and its impact

The rapid growth of Artificial Intelligence (AI) presents both significant opportunities and challenges for developing countries. A well-structured policy framework is crucial to maximize the benefits of AI while mitigating its risks. This review proposes a comprehensive AI policy framework tailored to developing countries, emphasizing the need for robust infrastructure, capacity building, ethical governance, and economic incentives. Key elements include the development of digital infrastructure, education and training programs to enhance AI literacy, and ethical guidelines to ensure fairness and transparency in AI applications. Data governance and privacy protections are critical, particularly in countries where regulatory frameworks are underdeveloped. Furthermore, international cooperation is highlighted as a necessity for aligning local policies with global AI standards, facilitating cross-border data sharing, and ensuring equitable access to AI innovations. The potential impact of AI on economic growth, job creation, healthcare, education, and public service delivery is profound, yet challenges such as workforce displacement, increased inequality, and the digital divide must be carefully managed. The proposed framework addresses these challenges, providing strategies to overcome barriers to AI adoption, including financial constraints, governance issues, and unequal access to technology. Moreover, it stresses the importance of fostering public-private partnerships and ensuring that AI development is inclusive, benefiting all segments of society. By implementing a comprehensive AI policy framework, developing countries can harness AI’s transformative power to drive sustainable development, improve social outcomes, and strengthen their economic standing in the global landscape. This review concludes by recommending continuous policy evaluation and adaptation to keep pace with AI's rapid evolution.

Navigating the ethical and governance challenges of ai deployment in AML practices within the financial industry

The rapid deployment of Artificial Intelligence (AI) in Anti-Money Laundering (AML) practices within the financial industry presents significant ethical and governance challenges that must be navigated effectively. As financial institutions increasingly adopt AI technologies to enhance their AML efforts, concerns regarding data privacy, algorithmic bias, and transparency emerge. This review explores the ethical implications of AI in AML and offers governance strategies to mitigate risks while ensuring compliance with regulatory frameworks. One of the primary ethical challenges in deploying AI for AML is the potential for algorithmic bias. AI systems trained on historical data may inadvertently perpetuate existing biases, leading to discriminatory practices in transaction monitoring and customer profiling. This raises serious concerns about fairness and equity in the financial sector. Addressing algorithmic bias requires the implementation of rigorous testing and validation processes to ensure AI systems function impartially across diverse populations. Data privacy is another critical issue. The extensive data collection required for effective AML monitoring raises questions about the protection of sensitive customer information. Financial institutions must establish robust data governance frameworks that prioritize privacy and comply with regulations such as the General Data Protection Regulation (GDPR). Ensuring transparency in how data is used and providing clear communication to customers about data practices is essential for building trust. Effective governance frameworks are crucial in navigating these ethical challenges. Financial institutions should adopt a multi-disciplinary approach that includes ethical guidelines, compliance measures, and risk management strategies. Establishing oversight committees can help ensure that AI deployment aligns with ethical standards and regulatory requirements. Furthermore, ongoing training for employees on the ethical use of AI in AML can foster a culture of responsibility and accountability. This review highlights the need for a balanced approach to AI deployment in AML, emphasizing the importance of ethical considerations and governance structures. As the financial industry continues to evolve, addressing these challenges will be essential for maintaining trust, ensuring compliance, and leveraging AI’s potential to enhance AML practices effectively.

The Influence and Strategies of Generative Artificial Intelligence on Academia, Ethics and Society

In the context of the emerging digital environment, generative artificial intelligence (GAI) is quickly becoming implemented in different spheres of life and even begins to replace people in some professions. This means that GAI is leading a new round of technological and industrial revolution. The application and growth of artificial intelligence has improved the society as well as the economy and but has issued many ethical and social problems thus making ethical governance of artificial intelligence more relevant. To contribute to the further development of the concept GAI under the conditions of sustainable development of human society and science, industries and scholars around the world have started researches on this technology. However, as GAI is still an embryonic field, more research efforts must be directed toward this field in the future. Researched articles that compare the use of GAI to the effects on ethical and societal concerns will form the basis of this paper and the resulting discussion of the pros and cons of this technology, this paper considers and demonstrates the difficulties of students, educators, and academics facing the consequences of GAI development. Finally, it has suggestion for the governance of GAI’s next phase of growth.

Can ESG Disclosure Stimulate Corporations’ Sustainable Green Innovation Efforts? Evidence from China

The Environmental, Social, and Governance (ESG) Composite Rating denotes corporations’ capability for supporting sustainable development activities, social responsibility, and transparent and ethical governance. It aims to inform investors and stakeholders about the company’s sustainability and social responsibility risks. ESG has increasingly become an informal yet significant driving force in promoting sustainable green innovation within the diversified co-governance environmental management system. This paper examines the dynamic relationship between ESG performance and sustainable green innovation practices in Chinese A-share listed companies from 2011 to 2022. The results show a positive correlation between ESG performance and the level of corporate sustainable green innovation. They also validate the moderating roles of informal external pressure and internal development demands. While the moderating effect of public environmental concern (PEC) is not significant, corporate digital transformation (CDT) significantly and positively moderates the relationship between ESG performance and sustainable green innovation. These findings offer policymakers and corporations a means to formulate a framework to shape the conduct of corporations to meet the market’s green development needs and to establish instruments that promote green innovation.

Impact of AI on Architecture: An Exploratory Thematic Analysis

The huge impact of artificial intelligence (AI) on various spheres is commonly attested in the literature. This study is informed by the dire need for more research on the increased adoption of AI and awareness of it for architectural activities. It is aimed at exploring the impact of AI on architecture, with a view to drawing evidence from extant studies to determine the extent of its adoption and positive impact on architecture. Literature review process, interpretive devices, and content and thematic analyses are employed to show scholarly evidence for its arguments on the thematic concern. Being an exploratory research, exploratory method and qualitative approach are employed. The study relies on observation and secondary data, focusing on their thematic preoccupations in relation to its arguments. The data are sourced online from only reputable repositories and databases. The analysis demonstrates that AI has been impacting positively on the broad field of architecture, and has the capacity to optimize and transform the architecture industry with huge innovations, results, efficiency, performance, and productivity. The study concludes that AI and other cutting-edge technologies, as technological innovations, are transforming the broad field of architecture. It charges the government and stakeholders in the field to ensure significant adoption of AI and increase awareness about AI, its impact, and ethical concerns. Ethical governance and pragmatic measures can help address the ethical concerns associated with AI.

The Ubuntu Way: Ensuring Ethical AI Integration in Health Research

The integration of artificial intelligence (AI) in health research has grown rapidly, particularly in African nations, which have also been developing data protection laws and AI strategies. However, the ethical frameworks governing AI use in health research are often based on Western philosophies, focusing on individualism, and may not fully address the unique challenges and cultural contexts of African communities. This paper advocates for the incorporation of African philosophies, specifically Ubuntu, into AI health research ethics frameworks to better align with African values and contexts. This study explores the concept of Ubuntu, a philosophy that emphasises communalism, interconnectedness, and collective well-being, and its application to AI health research ethics. By analysing existing global AI ethics frameworks and contrasting them with the Ubuntu philosophy, a new ethics framework is proposed that integrates these perspectives. The framework is designed to address ethical challenges at individual, community, national, and environmental levels, with a particular focus on the African context. The proposed framework highlights four key principles derived from Ubuntu: communalism and openness, harmony and support, research prioritisation and community empowerment, and community-oriented decision-making. These principles are aligned with global ethical standards such as justice, beneficence, transparency, and accountability but are adapted to reflect the communal and relational values inherent in Ubuntu. The framework aims to ensure that AI-driven health research benefits communities equitably, respects local contexts and promotes long-term sustainability. Integrating Ubuntu into AI health research ethics can address the limitations of current frameworks that emphasise individualism. This approach not only aligns with African values but also offers a model that could be applied more broadly to enhance the ethical governance of AI in health research worldwide. By prioritising communal well-being, inclusivity, and environmental stewardship, the proposed framework has the potential to foster more responsible and contextually relevant AI health research practices in Africa.