Emerging Issues in Transnational Biomedical Research

Ethical issues near the end of life often arise because of concerns about how much and what kind of care make sense for someone with a limited life expectancy, especially if the person is very ill. There is often conflict between health professionals and family members about what constitutes appropriate care. Many conflicts can be avoided by clarifying who makes the difficult decisions to limit care, and by advance planning. Caregivers should begin making legal preparations soon after their loved one has been diagnosed with a serious illness. Ethical and legal issues are embedded in the role of family caregiver. As the key decision-maker the family caregiver is faced with choosing options in addressing the concerns and expectations of the care recipient and/or other family members, and their own limitations in skills, time and resources. Decision-making and planning for incapacity, long-term care and death usually do not occur in the advance of an event, therefore, it is not surprising that only 20–30% of Americans have formalized their wishes in the event of their incapacity or death. Decision-making about the future usually occurs at the time of a diagnosis of a terminal illness. Physicians honor the principle of patient autonomy about decisions affecting their lives. A conversation about advance directives and questions about caregiving should involve the physician, patient, and family caregiver. Advance directives help to preserve the recipient’s well-being by protecting them against unwanted medical interventions.

Our improved understanding of the experience of people with dementia provides a new impetus to address legal and ethical issues. This paper explores emerging issues in relation to awareness in dementia and its impact on legal and ethical matters. The different approaches and principles demonstrated in relation to ethical issues are discussed, with an exploration of the concepts of beneficence, non-maleficence, autonomy, and paternalism. Application of these concepts is discussed in relation to advance directives, capacity, and decision making, participation in research and treatment, including informed consent, and truth telling. The tensions that exist between the imperatives of doing no harm and of maintaining autonomy in addressing legal and ethical issues are highlighted, and attention drawn to the manner in which the attribution of unawareness is used to justify withholding autonomy. The review emphasizes the importance of considering competency and awareness as being multi-faceted, to be understood in the context of social interaction.

37 - Responses to COVID-19: Ethical and Legal Issues

Introduction: Addiction treatment in India is provided by both government and private hospitals. Inpatient treatment is required in a relatively small proportion of patients. Despite this, there is a huge treatment gap for addiction treatment. This may lead to forced admission by the family members in unregistered/unlicensed rehabilitation centers. Case Report: A male patient presented to us for the treatment of opioid use disorder at our tertiary care hospital and addiction treatment center. Before reaching us, he sought treatment from various private drug rehabilitation centers for 7–8 years. His experience of previous inpatient stays in drug rehabilitation centers consisted of many human rights violations, the absence of qualified mental health professionals, forced admissions, physical and psychological torture, violence, and other legal and ethical issues. Discussion and Conclusion: The case highlights various ethical and legal issues in substance use treatment. There is a need for strict implementation of the Mental Health Care Act 2017 for the treatment of addiction. At the same time, there is a need to provide evidence-based treatment more widely across the country through various government programs and ministries. The central and state governments need to take action against those who flout the rules and regulations of this act. Addressing the shortage and increasing the number of trained addiction professionals is crucial. Finally, there is a need to provide addiction treatment services in government settings more widely across the country. This may decrease stigma and reduce the treatment gap of addiction.

Advances in artificial intelligence (AI) systems suggest that they can be used to improve healthcare outcomes via diagnosis, prognostication, patient management, risk assessment, etc. AI systems could be particularly useful in emergency healthcare (EHC) by synthesizing data to generate accurate conclusions rapidly. But the use of AI in EHC raises ethical, legal, and social concerns. The present study undertakes a scoping review to collate, map, and synthesize existing literature on the ethical, legal and social issues (ELSIs) associated with AI in EHC. The aim was to assess which ELSI issues were recognized and analyzed in the current literature and which were under-explored. Online databases were used to identify papers published on the identified topic. An initial search strategy of IEEE, Pubmed, and Scopus yielded 156 unique records; 40 records underwent textual review, after which another 7 were excluded due to scope. The final 33 were analysed for content. Overall, the literature was mostly positive towards AI applications on EHC, with key themes aligning with the general AI ethics literature: transparency, bias, benefit/harm, justice, accountability, privacy and trust. Analyses of these issues, however, were mostly superficial and did not substantially engage with some of the distinctive features of EHC like urgency and high-stakes decision-making. In particular, urgency and stakes were under-recognised or under-explored in the EHC AI literature. Arguably, urgency in some emergency scenarios could justify more flexible ethical/regulatory standards, while conversely high-stakes contexts might require more stringent standards. Lack of discussion of these contextual nuances suggests a significant gap in the literature of deeper research into the unique ethical, legal and social issues arising from AI use in EHC. This paper extends current knowledge by highlighting the need for deeper and more contextualized investigation of AI ethics in EHC. Not applicable.

Artificial intelligence (AI) refers to a group of technologies that enable people to perform a variety of activities, including observing, comprehending, analysing and translating data, among other things. Nowadays, practically every school of thought is interested in AI. One such innovation, a chatbot by the name of ChatGPT (Chat Generative Pre-Trained Transformer), launched by OpenAI recently, has taken the internet by storm. It had one million users within 1 week of its launch. The present communication explores the practicability and versatility of the ChatGPT in forensic examinations and scenarios, and also addresses the ethical and legal issues surrounding its usage. The observations suggest that the said technology, in its current form, has limited relevance in the realm of forensic science and the law. Only human critical thinking, expertise, and practical experience can provide the information and competencies needed in the realms of forensics, research, clinical and legal practices. Thus, the ChatGPT should be used with utmost caution in the disciplines of medicine, forensic science and the law, irrespective of its many positive attributes.

Ethical issues center themselves around Artificial Intelligence (AI) and the various opportunities and threats that it offers. The purpose of this research paper is to explain the positive side of AI, as well as the problems that require addressing. The actual study starts with the aims and objectives of the research and briefly highlights the importance of the research topic, the operational definitions of the terms under study, and the conceptual framework. It covers the history of AI, development in technology, and consequences on society. The benefits and the disadvantages of AI are included in the evaluation of its impact on specific sectors. Social consequences are considered, with an emphasis on how the application of AI will influence social structures and groups. The legal issues are considered, turning to the existing legislation and the possible legal repercussions. Ethical issues are considered with a focus on the proper use of artificial intelligence systems. Finally, the general ideas developed in the research are briefly highlighted, the thesis is repeated, and attention is drawn to the fact that further investigation and prevention efforts are required to tackle AI’s ethical issues. The findings of the study are then followed by suggestions for future work in this area.

Since the day when the first child was born with the aid of assisted reproduction (Louise Brown), the scientific community has always been interested in the implementation and the application of assisted reproduction methods. Although these methods help people around the globe to become parents, they may cause serious health risks, raising at the same time crucial legal and ethical issues. Moreover, the aforementioned issues deepen further due to the development of "reproductive tourism" since people travel to countries where the law permits the application of methods that are prohibited in their home country, thus circumventing the law. This situation can be perilous for the parties involved and evoke serious social and legal issues. Most major issues will be outlined by this comparative study of Greek and German legislation by examining surrogacy and heterologous fertilisation, a field where most delicate situations arise. Last but not least, the need of a common European legal framework, which will protect the public health and the rights of children and parents, is undeniable.

The Team Physician: Ethical and Legal Issues

The focus of this article is on families with both parental mental health issues and child protection concerns, a common clinical situation. Ethical dilemmas can arise from conflicting laws in a particular jurisdiction. This is evident in the State of South Australia, Australia. The issue is highlighted by examining the Mental Health Act 1993 (SA), the Children's Protection Act 1993 (SA) and Mental Health Act 2009 (SA). In developing a family approach where a parent has a mental illness and where statutory child protection concerns exist, both the Mental Health Act and the Children's Protection Act are needed to inform the clinical decision making for family members. Clinical, ethical, and legal issues are discussed. Two ethical models: Relational Ethics and Co-operation Despite Disagreement put forward the need for services to develop meaningful dialogue and collaborative practice. Professional codes of ethics need to address these complex, pluralistic ethical issues.

A recent article by Maxwell J. Mehlman and Tracy Yeheng Li, in the Journal of Law and the Biosciences, sought to examine the ethical, legal, social, and policy issues associated with the use of genetic screening and germ-line therapies (‘genomic technologies’) by the US Military. In this commentary, we will elaborate several related matters: the relationship between genetic and non-genetic screening methods, the history of selection processes and force strength, and the consequences and ethics of, as Mehlman and Li suggest, engineering enhanced soldiers. We contend, first, that the strengths of genomic testing as a method of determining enrollment in the armed forces has limited appeal, given the state of current selection methods in the US armed forces. Second, that the vagaries of genetic selection, much like other forms of selection that do not bear causally or reliably on soldier performance (such as race, gender, and sexuality), pose a systematic threat to force strength by limiting the (valuable) diversity of combat units. Third, that the idea of enhancing warfighters through germ-line interventions poses serious ethical issues in terms of the control and ownership of ‘enhancements’ when members separate from service.

This paper examines the ethical, legal, and social issues (ELSI) arising from the integration of generative artificial intelligence (AI) in educational settings in Japan. Following the emergence of ChatGPT in late 2022, Japanese educational institutions initiated pilot programs to explore AI applications in classrooms. Unlike traditional AI systems, where students were merely analyzed subjects, generative AI transforms students into active users, thereby expanding their potential risks and benefits. The study analyzes the AI development process, from training data collection to output generation, identifying key ELSI concerns, including bias, hallucination, privacy violations, and copyright infringement. Educational applications raise fundamental questions regarding the nature of teaching, learning, and schools. This study proposes multilevel response strategies: AI company engagement through procurement guidelines and pledge systems, institutional policy development, and enhanced AI literacy training for both educators and students. Responsible implementation requires balancing innovation with ethical considerations to maintain the trusting relationships that are essential to educational environments.

Many new parents have little awareness of the battery of screening tests that are routinely conducted on newborns in the United States and the developed world. Newborn screening, one of the most significant achievements in public health over the past 50 years, invites ongoing debate over a number of ethical and legal issues that have been part of the newborn screening landscape since the inception of the programs in the 1960s. This chapter reviews the history of newborn screening, outlines some of the key ethical and legal issues raised by these programs, and offers a prediction about how new technology may change these systems over the next few decades.

HIV infection forces mental health professionals to confront difficult legal and ethical issues. Problem solving requires the delicate balancing of diverse interests and a thoughtful approach that rationally weighs the benefits and disadvantages of traditional as well as new solutions.

Language Models (LMs) have demonstrated exceptional performance across various Natural Language Processing (NLP) tasks. Despite these advancements, LMs can inherit and amplify societal biases related to sensitive attributes such as gender and race, limiting their adoption in real‐world applications. Therefore, fairness has been extensively explored in LMs, leading to the proposal of various fairness notions. However, the lack of clear agreement on which fairness definition to apply in specific contexts and the complexity of understanding the distinctions between these definitions can create confusion and impede further progress. To this end, this paper proposes a systematic survey that clarifies the definitions of fairness as they apply to LMs. Specifically, we begin with a brief introduction to LMs and fairness in LMs, followed by a comprehensive, up‐to‐date overview of existing fairness notions in LMs and the introduction of a novel taxonomy that categorizes these concepts based on their transformer architecture: encoder‐only, decoder‐only, and encoder‐decoder LMs. We further illustrate each definition through experiments, showcasing their practical implications and outcomes. Finally, we discuss current research challenges and open questions, aiming to foster innovative ideas and advance the field. The repository is publicly available online at https://github.com/vanbanTruong/Fairness‐in‐Large‐Language‐Models/tree/main/definitions . This article is categorized under: Commercial, Legal, and Ethical Issues > Fairness in Data Mining Commercial, Legal, and Ethical Issues > Social Considerations Technologies > Artificial Intelligence .