Artificial Intelligence Governance Research Articles

Navigating ethical considerations in the use of artificial intelligence for patient care: A systematic review.

To explore the ethical considerations and challenges faced by nursing professionals in integrating artificial intelligence (AI) into patient care. AI's integration into nursing practice enhances clinical decision-making and operational efficiency but raises ethical concerns regarding privacy, accountability, informed consent, and the preservation of human-centered care. A systematic review was conducted, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Thirteen studies were selected from databases including PubMed, Embase, IEEE Xplore, PsycINFO, and CINAHL. Thematic analysis identified key ethical themes related to AI use in nursing. The review highlighted critical ethical challenges, such as data privacy and security, accountability for AI-driven decisions, transparency in AI decision-making, and maintaining the human touch in care. The findings underscore the importance of stakeholder engagement, continuous education for nurses, and robust governance frameworks to guide ethical AI implementation in nursing. The results align with existing literature on AI's ethical complexities in healthcare. Addressing these challenges requires strengthening nursing competencies in AI, advocating for patient-centered AI design, and ensuring that AI integration upholds ethical standards. Although AI offers significant benefits for nursing practice, it also introduces ethical challenges that must be carefully managed. Enhancing nursing education, promoting stakeholder engagement, and developing comprehensive policies are essential for ethically integrating AI into nursing. AI can improve clinical decision-making and efficiency, but nurses must actively preserve humanistic care aspects through ongoing education and involvement in AI governance. Establish ethical frameworks and data protection policies tailored to AI in nursing. Support continuous professional development and allocate resources for the ethical integration of AI in healthcare.

Ethical implications of artificial intelligence in skin cancer diagnostics: use-case analyses.

Skin cancer is the most common cancer worldwide. Early diagnosis is crucial for improving patient survival and morbidity. Artificial intelligence (AI)-assisted smartphone applications (apps) for skin cancer potentially offer accessible, early risk assessment of suspicious skin lesions. However, the integration of novel technologies into dermatology pathways raises ethical concerns. Although ethical principles for AI governance are well known, how these principles should be applied to real-life AI apps readily available for public use is less well understood. We conducted an ethical use-case analysis of commercially available skin cancer apps to better understand the ethical issues arising from their development and use in a real-world context. Established methods for ethical analysis of clinical AI applications were applied to two popular skin cancer apps in the UK: SkinVision and Scanoma. Systematic searches of published literature, regulatory documents, and websites were conducted to review the evidence regarding app development, effectiveness, and use. Screening for inclusion was undertaken by two researchers independently. Ethical concerns were identified with reference to previously described ethical concerns and principles for AI-assisted healthcare. By conceptualising ethical principles within the use-context of skin cancer apps, we identified specific ethical issues arising throughout the AI lifecycle of both apps. One company provided extensive detail regarding algorithm development and decision-making, this information was insufficiently reported for the other app. Other concerns identified related to number, quality, and consistency of studies assessing algorithm efficacy. Limited efforts to address potential skin tone biases and exclusion of individuals with darker skin tones as target users by one app risks perpetuating existing inequalities. Inadequate regulatory oversight was identified. Findings from our ethical use-case analysis of two patient-facing AI-assisted skin cancer apps suggest inadequate incorporation of bioethical norms such as justice, responsibility and transparency into the development and deployment of both apps. Improved regulation should increase accountability. Ensuring ethics by design through integration between technology developers, dermatologists, ethicists, and the public is urgently needed to prevent the potential benefits of AI-assisted skin cancer apps being overshadowed by potential ethical harms.

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 governance framework for healthcare.

Recent advancements in the field of Artificial Intelligence (AI) provide promising applications of this technology with the aim of solving complex healthcare challenges. These include optimizing operational efficiencies, supporting clinical administrative functions, and improving care outcomes. Numerous AI models are validated in research settings but few make their way into useful applications due to challenges associated with implementation and adoption. In this article, we describe some of these challenges, along with the need for a facilitating entity to safely translate AI systems into practical use. The authors propose a new AI governance framework to enable healthcare organizations with a mechanism to implement and adopt AI systems.

6.Q. Round table: Artificial Intelligence in healthcare: navigating ethically with equity and workforce empowerment

Abstract Background Artificial Intelligence (AI) is emerging as a pivotal technology with vast promises for healthcare. However, integrating AI into clinical and public health settings must be cautiously approached to ensure that it does not inadvertently exacerbate existing health system problems. The healthcare workers, already under severe stress, could view AI as a threat to job security rather than as a support mechanism. Moreover, past experiences with digital transformations, such as Electronic Health Records, have shown that technological integration can sometimes increase rather than decrease the burden on healthcare workers, leading to burnout and dissatisfaction, and thus worsening the healthcare workforce crisis. Furthermore, equity and ethical considerations are paramount in the deployment of AI in healthcare. Data privacy, patient consent, and algorithmic bias must be addressed to ensure that AI applications are designed to support and enhance human decision-making that is sensitive to the social determinants of health and accountable to equity and social inclusion, to the needs and rights of the healthcare workforce, and the dignity of the patients and populations. While AI presents significant opportunities for health systems and healthcare workers, there is a lack of knowledge, evidence-based policies, and ethical frameworks that support equitable and human-centred approaches to AI implementation. Objectives This round table workshop aligns three major public health challenges: the integration of AI in health systems, the global healthcare workforce crisis, and the improvement of equity and equality. It critically explores capacity building for AI, equity in AI implementation, and regulatory measures for ethical and responsible AI deployment, addressing the following major questions: What are the critical impacts of AI on the healthcare workforce? How can the healthcare workforce be effectively upskilled and supported to adapt to the changes brought by AI technologies? What regulatory frameworks and governance models are necessary to ensure AI’s safe and ethical implementation in healthcare, that is also sensitive to equity, gender equality and the needs of minority groups? Finally, what actionable steps and leadership can public health take to implement AI technologies while addressing the healthcare workforce needs, equity issues, and ethical guidelines? The panellists will illuminate these questions from different disciplinary approaches, helping us to disentangle complexity and to build capacity for evidence-based and socially inclusive AI policies. The workshop contributes to better understand the risks and benefits of AI. It seeks to advance knowledge exchange of good practice experiences and effective implementation. Key messages • The effects of AI on the healthcare workforce must be monitored and strategies adapted to mitigate the healthcare workforce crisis and to upskill and empower healthcare workers. • There is a need for human-centred and ethically responsive AI implementation and governance measures that support equity, gender equality, and diversity in healthcare settings. Speakers/Panelists Abi Sriharan Schulich School of Business York University, York, Canada Kasia Czabanowska Maastricht University, Maastricht, Netherlands Bernadette Kumar Migration Health Unit, Norwegian Institute of Public Health, Oslo, Norway Marius-Ionuț Ungureanu Babeș-Bolyai University, Cluj-Napoca, Romania Farhang Tahzib Faculty of Public Health, Haywards heath, UK

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.

The Future of Work: A Human-centric Approach to AI, Robotics, and Cloud Computing

This study investigates the impact of artificial intelligence (AI), robotics, and cloud computing on the future of work, focusing on adoption trends, productivity gains, and ethical challenges. Using a mixed-method approach, data were sourced from the OECD AI Policy Observatory, Pew Research Center, and European Union Open Data Portal. Quantitative analysis included K-Means clustering of industries based on technology adoption, with high adopters like North America and Europe leading in cloud computing (65.87%), and Africa showing stronger AI adoption (63.02%). The analysis also highlighted a 14.5% productivity increase in manufacturing, but a 19.3% risk of job displacement. Sentiment analysis revealed that 75% of public sentiment on algorithmic bias was negative, correlating strongly (0.74) with reported violations. The study affirms the need for improved AI governance and stronger GDPR compliance to address ethical challenges, while prioritizing human-centric strategies that ensure inclusive and sustainable outcomes for the workforce.

EU’s AI Regulation Approaches and Their Implication for Human Rights

The rapid development of Artificial Intelligence (AI) technologies presents significant opportunities, but also introduces critical challenges, particularly concerning the protection of human rights. In response, the European Union (EU) has developed comprehensive AI regulations, most notably the AI Act, positioning itself as a leader in global AI governance. However, questions remain regarding the effectiveness of these laws in safeguarding key human rights such as privacy, equality, autonomy, and freedom. This study aims to assess the sufficiency of the EU’s current AI regulations in protecting human rights, analyze the specific impacts of AI technologies on privacy and equality, and explore emerging legal trends in AI regulation within the EU and their broader global implications. Utilizing a mixed-method approach, this research integrates legislative analysis, comparative research, scientific forecasting, and interdisciplinary inquiry. The study critically examines the provisions of the AI Act and other relevant EU regulations, comparing them with international legal frameworks to identify gaps and future challenges. The findings reveal that, while the EU’s AI regulations offer foundational protections, there are significant deficiencies in addressing complex issues such as privacy, algorithmic bias, and transparency, particularly in high-risk areas like healthcare, law enforcement, and autonomous systems. The study also highlights that existing regulations are inadequate in managing the rapid integration of AI technologies across sectors and that marginalized groups are especially vulnerable to the risks posed by algorithmic decision-making systems. Furthermore, the EU’s AI regulatory framework is poised to become a global benchmark, but there is an urgent need for more adaptive and flexible legal mechanisms to keep pace with the dynamic nature of AI advancements. In conclusion, the study emphasizes the need for legal reforms to bridge the current gaps in privacy protection and address algorithmic bias, ensuring the robust protection of human rights in the age of AI.

Governance of artificial intelligence in Southeast Asia

AbstractGovernance of artificial intelligence (AI) has not achieved global participation. The primary state‐led instrument focusing specifically on the global governance of artificial intelligence is the Global Partnership on Artificial Intelligence (GPAI). Although GPAI aims for broad international participation, the only GPAI member from Southeast Asia is Singapore. GPAI's imbalanced global participation, restrictive membership process, and limited translations are potential barriers to Southeast Asian participation. However, a comparative policy analysis suggests that GPAI members and nonmembers in Southeast Asia have AI governance policies which are largely compatible, despite key differences. This study uses quantitative topic‐modeling and qualitative content analysis to compare the AI governance policies of Indonesia, Malaysia, Thailand, and Vietnam with the policies of Australia and Singapore, as reference GPAI members. The policies of GPAI, Australia, and Singapore emphasise the function of ethics while the policies of Indonesia, Malaysia, Thailand, and Vietnam emphasise the function of human capital development. State‐led, global AI governance efforts could attract more Southeast Asian participation by further emphasising human capital development and deemphasising the function of ethics. GPAI could increase the likelihood of Southeast Asian participation by decreasing its emphasis on political systems, allowing intergovernmental organisations to join, and recruiting all G20 members.

AI Ethics in Journalism (Studies): An Evolving Field Between Research and Practice

The integration of artificial intelligence (AI) in journalism has sparked complex ethical debates, particularly with the rise of generative AI systems. By now, AI permeates the entire news cycle, from information gathering to news dissemination, raising questions revolving around issues such as transparency, accountability, responsibility, bias, and diversity. Previous research showed that news organizations have slowly approached and adapted to ethical concerns regarding the use of AI, developing critical stances mainly due to rising AI power, growing audience skepticism, and mounting tensions within the industry between news publishers’ strategies and journalists’ anxieties. Consequently, ethical guidelines have started to emerge in news organizations, but their practical application remains challenging and under-studied, not only due to the opacity of AI algorithms, but also due to the difficulties of “embedding” journalistic values into AI systems. In the light of an intensifying discourse about ethical concerns in the news industry and growing efforts by governments and institutions such as the European Union to strengthen AI governance, journalism studies have started to explore the issue as well. However, research on AI ethics is still in its infancy, with significant gaps in understanding the practical enforcement of ethical guidelines within newsrooms, in particular when it comes to the design of AI systems. This essay critically discusses the way journalism (studies) approach ethical issues related to the use and the design of AI systems, given that the responsible use and design of AI systems in journalism is crucial given its integral role for democracy and society.

Regulatory impact of a governmental approach for artificial intelligence technology implementation in Vietnam

This study assesses Vietnam’s state-level implementation of artificial intelligence (AI) technology and analyses the government’s efforts to encourage AI implementation by focusing on the National Strategy on AI Development Program. This study emphasizes the possibility of implementing AI at the state level in Vietnam and the importance of conducting continuous reviews and enhancements to achieve sustainable and inclusive AI growth. Impact evaluations were conducted in public organizations alone, and implication evaluations were considered optional. AI impact assessments were constrained by societal norms that necessitated establishing relationships among findings. There is a lack of official information regarding the positive impact of Vietnam’s AI policy on the development of AI infrastructure, research, and talent pools. The study’s findings highlight the necessity of facilitating extensive AI legislation, and strengthening international cooperation. The study concludes with the following recommendations for improving Vietnam’s AI policy: implementing a strong AI governance structure and supporting AI education and awareness.

Unravelling Smart HRM 4.0: A Narrative Review of Progressive 4.0 Technology Integration in Human Resource Management

The integration of progressive 4.0 technology into human resource management (HRM) represents a significant shift in how organizations optimize and enhance workforce capabilities. This review explores the origins, applications, benefits, challenges and future prospects surrounding smart HRM 4.0. By reviewing existing literature, this paper examines the utilization of Artificial Intelligence (AI), Big Data analytics, machine learning (ML) and the Internet of Things (IoT) in HRM, specifically in talent acquisition, training, performance management, and rewards. Additionally, it addresses the implementation challenges including data quality assurance, skill shortages, and cultural resistance. The paper also emphasizes the importance of ethical considerations. In terms of future research, it highlights the necessity for ethically deploying Industry 4.0 and establishing robust AI governance frameworks. By combining technological innovation with ethical values, organizations can navigate the complexities of this integration, leading to a future characterized by workplace efficiency, accountability, and fairness.

From roadmap to regulation: will there be a transatlantic approach to governing artificial intelligence?

ABSTRACT The transformative nature and accelerating pace of development of Artificial Intelligence (AI) technologies have generated frenzied political debate and urgent calls for regulation. The European Union’s (EU) AI Act is one of the earliest, most ambitious, legally binding efforts to regulate high-risk AI systems. This article argues that the thrust of the EU’s focus on ‘ethical and secure’ AI and its first-mover regulatory status have helped to foster transatlantic cooperation on AI governance. To probe this assertion, the article analyzes the ethical underpinnings and key provisions of the AI Act and compares them to policy developments in the United States. The analysis provides preliminary evidence of policy similarities across the Atlantic from an alignment of ethical concerns to a shared understanding of the risks and associated need for common guidelines and standards in the AI sector. Tracing agreements within the EU-US Trade and Technology Council (TTC) suggests further cooperation and relative congruence in the EU and US approaches to AI.

Comparative Analysis Of Ai Governance In Africa Relative To Global Standards And Practices

Africa as a continent recognizes the need for Artificial Intelligence (AI) governance frameworks. However, despite initiatives like the African Union's Continental AI Strategy, African nations grappled with challenges in formulating comprehensive AI policies, while established global frameworks provided advanced benchmarks for comparison. To address this disparity, this study conducted a comparative analysis of AI governance in Africa relative to global standards and practices. Employing a comprehensive document analysis methodology, the research examined key policy documents, strategic frameworks, and regulatory guidelines across African, European, American, and Asian contexts. The findings revealed that while the African Union demonstrated commitment to coordinated AI governance, African approaches generally lagged behind global benchmarks in comprehensiveness, formalization, and ethical integration. The study identified a notable fragmentation in AI governance across African nations, contrasting with more unified approaches in other regions. African frameworks emphasized leveraging AI for socio-economic development, diverging from the risk mitigation focus seen in EU regulations. The integration of indigenous African ethical perspectives in AI governance frameworks was limited, presenting both challenges and opportunities. Significant disparities in digital infrastructure and AI capacity between Africa and other regions were found to affect governance implementation. The study concluded that despite these challenges, there was potential for Africa to develop innovative, context-specific AI governance models that could contribute valuable insights to the global discourse on responsible AI development. Recommendations included accelerating the implementation of the Continental AI Strategy, prioritizing investment in digital infrastructure, developing Africa-centric AI ethics frameworks, establishing mechanisms for regular benchmarking against global standards, fostering increased collaboration, and implementing AI literacy programs across the continent.

Human Subjectivity in Information Practice and AI Governance

ABSTRACTThe rise of Artificial Intelligence (AI) introduces a notable tension in the realm of traditional, human‐centric information practices, where human subjectivity has been pivotal in both influencing and being influenced by our interactions with information. An excessive reliance on AI distances humans from practices, potentially diminishing human subjectivity. Additionally, as AI takes on roles once exclusively human, it might constrict opportunities for personal growth and the cultivation of unique insights. Moreover, this technological dependency could dilute the richness of direct human interactions, weakening the fabric of social bonds. These issues—increased AI dependence, AI's encroachment on human roles, and the degradation of social ties—underscore the urgent necessity to revisit our interaction with technology, ensuring it serves to enrich rather than undermine the human experience. In light of this, our panel gathers experts to explore strategies for preserving human subjectivity through cognitive autonomy, creative agency, and social connectivity in the age of AI‐driven information practices. Our dialogue also aims to develop a comprehensive AI governance framework, scrutinized from an interdisciplinary perspective, continually refined in collaboration with academic communities, such as ASIS&T, to solidify and enhance our approaches.

Ethical Artificial Intelligence Framework Theory (EAIFT): A New Paradigm for Embedding Ethical Reasoning in AI Systems

The rapid development of artificial intelligence (AI) has created several ethical issues, including bias, a lack of transparency, and privacy concerns, demanding the incorporation of ethical governance directly into AI systems. This study introduces the Ethical Artificial Intelligence Framework Theory (EAIFT), a novel approach to incorporating ethical reasoning into AI. It emphasizes real-time oversight, open decision-making, bias detection, and the ability to change ethical and legal norms. EAIFT advocates for establishing "ethical AI watchdogs" that automatically monitor and ensure the ethical operation of AI systems, together with dynamic compliance algorithms that can adapt to regulatory changes. The paradigm also encourages transparency and explainability to build user trust and detect and correct biases to ensure fairness. This paper employs a qualitative methodology that combines stakeholder interviews, content analysis, and expert commentary to evaluate EAIFT's potential to increase ethical accountability in various areas, including healthcare, banking, and criminal justice. The findings suggest that EAIFT outperforms existing ethical frameworks by proactively reducing biases, increasing transparency, and ensuring adherence to ethical standards. While presenting a comprehensive and adaptable technique, the study also acknowledges limitations in empirical testing and the need for additional research to widen EAIFT's applicability to future ethical challenges in artificial intelligence. The paper suggests future research subjects, such as empirical testing in different scenarios, a more in-depth examination of ethical risks, and the inclusion of the framework into new AI technologies to promote responsible AI governance by societal norms and values.

AI Governance: A Challenge for Public Health.

The rapid evolution of artificial intelligence (AI) is structuralizing social, political, and economic determinants of health into the invisible algorithms that shape all facets of modern life. Nevertheless, AI holds immense potential as a public health tool, enabling beneficial objectives such as precision public health and medicine. Developing an AI governance framework that can maximize the benefits and minimize the risks of AI is a significant challenge. The benefits of public health engagement in AI governance could be extensive. Here, we describe how several public health concepts can enhance AI governance. Specifically, we explain how (1) harm reduction can provide a framework for navigating the governance debate between traditional regulation and "soft law" approaches; (2) a public health understanding of social determinants of health is crucial to optimally weigh the potential risks and benefits of AI; (3) public health ethics provides a toolset for guiding governance decisions where individual interests intersect with collective interests; and (4) a One Health approach can improve AI governance effectiveness while advancing public health outcomes. Public health theories, perspectives, and innovations could substantially enrich and improve AI governance, creating a more equitable and socially beneficial path for AI development.

Comparative legal frameworks for regulating artificial intelligence: A model for harmonizing AI laws in Latin America and Africa

As Artificial Intelligence (AI) technologies advance, the need for comprehensive and harmonized legal frameworks has become paramount. This paper conducts a comparative analysis of the regulatory approaches to AI in Latin America and Africa, regions with unique challenges and opportunities in AI governance. While both regions have shown growing interest in AI, their legal landscapes differ significantly, with fragmented policies and varying levels of enforcement. The analysis reveals that despite these differences, there are common concerns such as data privacy, ethical use, and the impact of AI on labor markets that demand coordinated regulatory responses. The paper proposes a model for harmonizing AI laws between these regions, focusing on fostering cross-regional collaboration, developing shared ethical guidelines, and establishing joint regulatory bodies to ensure consistent enforcement. This model aims to balance innovation with the protection of fundamental rights, drawing on successful frameworks from other jurisdictions while adapting to the socio-economic contexts of Latin America and Africa. The harmonization of AI laws is not only essential for mitigating risks associated with AI but also for promoting economic integration and technological collaboration between these regions. By aligning their regulatory approaches, Latin America and Africa can better position themselves in the global AI landscape, ensuring that AI development is inclusive, ethical, and sustainable. The paper concludes by highlighting the importance of regional cooperation in AI governance and the potential of a harmonized legal framework to foster innovation while safeguarding public interest. This comparative study serves as a foundational step towards creating a unified AI regulatory environment that can effectively address the complexities of AI technologies and their socio-economic impacts across these two diverse regions.

The Convergence of Artificial Intelligence and Privacy: Navigating Innovation with Ethical Considerations

This article explores the complex relationship between artificial intelligence (AI) and privacy. While acknowledging AI's potential benefits, the authors emphasize the ethical implications of its data-driven nature. The article begins by outlining the privacy risks inherent in AI systems, including data breaches, surveillance, and the potential for bias and discrimination. It then delves into ethical considerations surrounding AI development, such as transparency, accountability, and the need to prioritize human values. Various frameworks for balancing innovation with privacy protection are discussed, including Privacy by Design principles and the General Data Protection Regulation (GDPR). It also examine case studies of privacy violations in AI systems, highlighting the real-world consequences of inadequate safeguards. Looking towards the future, the article identifies advancements in privacy-preserving AI technologies as a crucial area of research. It concludes by advocating for a comprehensive approach to AI governance that combines technological innovation with ethical and regulatory strategies, by stressing the importance of proactive measures to mitigate privacy risks and ensure that AI technologies are developed and deployed in a manner that respects.

The future is bright: artificial intelligence for trainee medical officers in Australia and New Zealand.

Given their frontline role in Australia and Aotearoa New Zealand (ANZ) healthcare, trainee medical officers (TMOs) will play a crucial role in the development and use of artificial intelligence (AI) for clinical care, ongoing medical education and research. As 'digital natives', particularly those with technical expertise in AI, TMOs should also be leaders in informing the safe uptake and governance of AI within ANZ healthcare as they have a practical understanding of its associated risks and benefits. However, this is only possible if a culture of broad collaboration is instilled while the use of AI in ANZ is still in its initial phase.