Asian Bioethics Review最新文献

Population biobanks are an increasingly important infrastructure to support research and will be a much-needed resource in the delivery of personalised medicine. Artificial intelligence (AI) systems can process and cross-link very large amounts of data quickly and be used not only for improving research power but also for helping with complex diagnosis and prediction of diseases based on health profiles. AI, therefore, potentially has a critical role to play in personalised medicine, and biobanks can provide a lot of the necessary baseline data related to healthy populations that will enable the development of AI tools. To develop these tools, access to personal data, and in particular, sensitive data, is required. Such data could be accessed from biobanks. Biobanks are a valuable resource for research but accessing and using the data contained within such biobanks raise a host of legal, ethical, and social issues (ELSI). This includes the appropriate consent to manage the collection, storage, use, and sharing of samples and data, and appropriate governance models that provide oversight of secondary use of samples and data. Biobanks have developed new consent models and governance tools to enable access that address some of these ELSI-related issues. In this paper, we consider whether such governance frameworks can enable access to biobank data to develop AI. As Italy has one of the most restrictive regulatory frameworks on the use of genetic data in Europe, we examine the regulatory framework in Italy. We also look at the proposed changes under the European Health Data Space (EHDS). We conclude by arguing that currently, regulatory frameworks are misaligned and unless addressed, accessing data within Italian biobanks to train AI will be severely limited.

This paper discusses the key role medical regulators have in setting standards for doctors who use artificial intelligence (AI) in patient care. Given their mandate to protect public health and safety, it is incumbent on regulators to guide the profession on emerging and vexed areas of practice such as AI. However, formulating effective and robust guidance in a novel field is challenging particularly as regulators are navigating unfamiliar territory. As such, regulators themselves will need to understand what AI is and to grapple with its ethical and practical challenges when doctors use AI in their care of patients. This paper will also argue that effective regulation of AI extends beyond devising guidance for the profession. It includes keeping abreast of developments in AI-based technology and considering the implications for regulation and the practice of medicine. On that note, medical regulators should encourage the profession to evaluate how AI may exacerbate existing issues in medicine and create unintended consequences so that doctors (and patients) are realistic about AI’s potential and pitfalls when it is used in health care delivery.

The increasing integration of artificial intelligence (AI) in healthcare presents a host of ethical, legal, social, and political challenges involving various stakeholders. These challenges prompt various studies proposing frameworks and guidelines to tackle these issues, emphasizing distinct phases of AI development, deployment, and oversight. As a result, the notion of responsible AI has become widespread, incorporating ethical principles such as transparency, fairness, responsibility, and privacy. This paper explores the existing literature on AI use in healthcare to examine how it addresses, defines, and discusses the concept of responsibility. We conducted a scoping review of literature related to AI responsibility in healthcare, searching databases and reference lists between January 2017 and January 2022 for terms related to “responsibility” and “AI in healthcare”, and their derivatives. Following screening, 136 articles were included. Data were grouped into four thematic categories: (1) the variety of terminology used to describe and address responsibility; (2) principles and concepts associated with responsibility; (3) stakeholders’ responsibilities in AI clinical development, use, and deployment; and (4) recommendations for addressing responsibility concerns. The results show the lack of a clear definition of AI responsibility in healthcare and highlight the importance of ensuring responsible development and implementation of AI in healthcare. Further research is necessary to clarify this notion to contribute to developing frameworks regarding the type of responsibility (ethical/moral/professional, legal, and causal) of various stakeholders involved in the AI lifecycle.

Artificial intelligence (AI) is the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. Artificial intelligence can be both a blessing and a curse, and potentially a double-edged sword if not carefully wielded. While it holds massive potential benefits to humans—particularly in healthcare by assisting in treatment of diseases, surgeries, record keeping, and easing the lives of both patients and doctors, its misuse has potential for harm through impact of biases, unemployment, breaches of privacy, and lack of accountability to mention a few. In this article, we discuss the fourth industrial revolution, through a focus on the core of this phenomenon, artificial intelligence. We outline what the fourth industrial revolution is, its basis around AI, and how this infiltrates human lives and society, akin to a transcendence. We focus on the potential dangers of AI and the ethical concerns it brings about particularly in developing countries in general and conflict zones in particular, and we offer potential solutions to such dangers. While we acknowledge the importance and potential of AI, we also call for cautious reservations before plunging straight into the exciting world of the future, one which we long have heard of only in science fiction movies.

Artificial intelligence (AI) has attracted an increasing amount of attention, both positive and negative. Its potential applications in healthcare are indeed manifold and revolutionary, and within the realm of medical imaging and radiology (which will be the focus of this paper), significant increases in accuracy and speed, as well as significant savings in cost, stand to be gained through the adoption of this technology. Because of its novelty, a norm of keeping humans “in the loop” wherever AI mechanisms are deployed has become synonymous with good ethical practice in some circles. It has been argued that keeping humans “in the loop” is important for reasons of safety, accountability, and the maintenance of institutional trust. However, as the application of machine learning for the detection of lumbar spinal stenosis (LSS) in this paper’s case study reveals, there are some scenarios where an insistence on keeping humans in the loop (or in other words, the resistance to automation) seems unwarranted and could possibly lead us to miss out on very real and important opportunities in healthcare—particularly in low-resource settings. It is important to acknowledge these opportunity costs of resisting automation in such contexts, where better options may be unavailable. Using an AI model based on convolutional neural networks developed by a team of researchers at NUH/NUS medical school in Singapore for automated detection and classification of the lumbar spinal canal, lateral recess, and neural foraminal narrowing in an MRI scan of the spine to diagnose LSS, we will aim to demonstrate that where certain criteria hold (e.g., the AI is as accurate or better than human experts, risks are low in the event of an error, the gain in wellbeing is significant, and the task being automated is not essentially or importantly human), it is both morally permissible and even desirable to kick the humans out of the loop.

Large data-intensive health research programmes benefit from collaboration amongst researchers who may be located in different institutions and international contexts. However, complexities in navigating privacy frameworks and data protection laws across various jurisdictions pose significant challenges to researchers seeking to share or transfer data outside of institutional boundaries. Research on the awareness of data protection and privacy laws amongst stakeholders is limited. Our qualitative study, drawn from a larger project in Singapore, revealed insights into stakeholders’ perceptions of the role of law in cross-national health data research. Stakeholders in our study demonstrated a range of perceptions regarding the role of data protection law in governing the collection and transfer of health data for research. The main criticisms included inadequate legal protection to data and lack of uniformed data protection standards. Despite these criticisms, participants recognised the importance of data protection law in supporting cross-border data transfers and proposed measures to improve perceived limitations of existing laws. These measures include strengthening existing legal framework, establishing contractual agreements and imposing severe punishments for data misuse.

The Universal Declaration of Human Rights (UDHR) approved by the United Nations (UN) in 1948 includes the most widely accepted list of individual rights all over the world. Although it has been a catalyst in the pursuit of a universal ethic for human rights, it has not been updated for over 75 years during which significant progress has been made in the recognition of more human rights. It is time to examine whether the current global society aspires for more/other human rights that are not reflected in previous declarations. We offer a review of literature on the potential areas that human rights may be extended to in the current sociocultural atmosphere and share the results of a survey at an international university in Japan which examines the views of 232 young Asian students from Japan, Korea, Vietnam, Thailand, China, Indonesia, etc. regarding the human rights declaration items and their implications, as well as new hypothetical items that they would like to see recognized as human rights. The results demonstrate stronger support for 15 out of the 21 surveyed items by all respondents, as well as stronger support for 10 out of the 21 items by female respondents. These results suggest a variable expansion in the breadth of the human rights concept which is worthy of further research. Also, gender inequality may be the basis for the stronger support of certain human rights by female respondents.

This perspective article explores the use of digital twins (DTs) in medicine, highlighting its capacity to simulate risks and personalize treatments while examining the emerging bioethical concerns. Central concerns include power dynamics, exclusion, and misrepresentation. We propose adopting a relational bioethical approach that advocates for a comprehensive assessment of DTs in medicine, extending beyond individual interactions to consider broader structural relations and varying levels of access to power. This can be achieved through two key relational recommendations: acknowledging the impact of uneven relational structures on access to medical care and promoting social justice by evaluating resource allocation. While DTs in medicine offer promising advancements, a relational bioethical lens may provide a nuanced understanding, fostering equitable, inclusive and responsible integration of DTs into medical practice.

We describe the national health research ethics review system of Uzbekistan and identify policy and program gaps that impede the protection of human research subjects. We find that the National Ethic Committee (NEC), functioning at the national level, is solely responsible for conducting research ethics review. There is little evidence that regional ethics committees work as intended, and there is no research ethics review at medical institutes and research centers even though they conduct CDTs (clinical drug trials). There is no national policy for the ethical review of non-clinical trials. We recommend the establishment of institutional review boards (IRBs) at medical institutes and research centers while at the same time building capacity at the national level to oversee and support the research ethics review system of the entire country.

In an increasingly globalized world, the accessibility of healthcare and medication has expanded beyond local healthcare systems and national borders. This study aims to investigate the transnational health and self-care experiences of 11 Japanese women who have resided in South Korea for a minimum of six months and have utilized oral contraceptives, including those that were acquired over-the-counter (OTC). Data were gathered through semi-structured interviews and analyzed by utilizing the NVivo software. The analysis yielded three significant thematic categories, namely (1) experiences and perceptions of obtaining and utilizing contraceptive pills, including OTC access; (2) individual and social perceptions of pills and their accessibility in Japan, insights from actual users; and (3) enhancing pill accessibility, transnational health and self-care experiences and perspectives. Participants acknowledged that oral contraceptives are a global product and experienced communication challenges with healthcare providers as a result of differing understandings of these medications. Additionally, this study identified transnational strategies, such as purchasing an adequate supply of pills just before departure and seeking pills from local families or acquaintances. This study not only highlights the implications of clinical care for transnational patients but also underscores their critical global perspectives on access to oral contraceptives. Furthermore, it proposes two models for improving accessibility within the Japanese healthcare system, even in prescription-only contexts, by introducing OTC options.