Inbar Cohen

Sir Isaac Newton was one of the greatest scientists of all time, a thinker of extraordinary range and creativity who has left enduring legacies in mathematics and the natural sciences. In this volume a team of distinguished contributors examine all the main aspects of Newton's thought, including not only his approach to space, time, mechanics, and universal gravity in his Principia, his research in optics, and his contributions to mathematics, but also his more clandestine investigations into alchemy, theology, and prophecy, which have sometimes been overshadowed by his mathematical and scientific interests.

Newton’s physics is based on two fundamental concepts: mass and force. In the _Principia_ Newton explores the propoerties of several types of force. The most important of these are forces that produce accelerations or changes in the state of motion or of rest of bodies. In Definition 4 of the Principia, Newton separates these into three principal categories: impact or percussion, pressure, and centripetal force. In the Principia, Nwton mentions other types of forces, including (in Book 2) the forces with which fluids resist motions through them. Of a different sort is Newton’s „force of inertia“, which is neither an accelerative force nor a static force and is nit, properly speaking in the context of dynamics, a force at all.

Researchers and practitioners are increasingly using machine‐generated synthetic data as a tool for advancing health science and practice, by expanding access to health data while—potentially—mitigating privacy and related ethical concerns around data sharing. While using synthetic data in this way holds promise, we argue that it also raises significant ethical, legal, and policy concerns, including persistent privacy and security problems, accuracy and reliability issues, worries about fairness and bias, and new regulatory challenges. The virtue of synthetic data is often understood to be its detachment from the data subjects whose measurement data is used to generate it. However, we argue that addressing the ethical issues synthetic data raises might require bringing data subjects back into the picture, finding ways that researchers and data subjects can be more meaningfully engaged in the construction and evaluation of datasets and in the creation of institutional safeguards that promote responsible use.

The Research Handbook on Health, AI and the Law explores the use of AI in healthcare, identifying the important laws and ethical issues that arise from its use. Adopting an international approach, it analyses the varying responses of multiple jurisdictions to the use of AI and examines the influence of major religious and secular ethical traditions. Bringing together a diverse range of carefully selected legal experts, the Research Handbook critically assesses the different uses of AI in healthcare and its promise to provide greater accuracy for healthcare professionals and patients by diagnosing diseases and detecting illness earlier and helping hospitals run more efficiently. It also highlights a series of legal and ethical challenges AI raises relating to bias, privacy, data security, medical liability, informed consent and intellectual property. AI governance is rigorously examined in countries across the globe spanning Asia, Europe and the US while different responses from international organisations towards AI in healthcare are also evaluated. This Research Handbook is a key resource for scholars and law students and for those interested in current and developing legal paradigms. Its legal and practical dimensions will also be beneficial to lawyers practising in health law and internet and technology law, policymakers and medical professionals.

Should the law recognize an individual's right not to be a genetic parent when genetic parenthood does not carry with it legal or gestational parenthood? If so, should we allow individuals to waive that right in advance, either by contract or a less formal means? How should the law's treatment of gestational and legal parenthood inform these questions? Developments in reproductive technology have brought these questions to the fore, most prominently in the preembryo disposition cases a number of courts have confronted - disputes over the use of stored frozen preembryos that couples have fertilized in the course of In Vitro Fertilization (IVF) - but other examples abound.In this Article, I argue that in analyzing these cases it is essential to unbundle the possible rights not to be a genetic, gestational, and legal parent, and to recognize that the three rights do not stand and fall together. I show that we cannot move from the discourse surrounding the rights not to be a gestational and legal parent to a justification for a right not to be a genetic parent. Instead, I argue that the normative mooring of the right not to be a genetic parent is best understood as a way of protecting individuals from what I call "attributional parenthood," a harm that stems from the social assignment of the status of parent to the provider of genetic material that persists notwithstanding the fact that the legal system has declared him or her a non-parent.Using this framework, I argue for the recognition of the right not to be a genetic parent. However, I reject the claim, common among courts and commentators, that this right should not be capable of advance waiver. I instead conclude that we should permit advance waiver of the right through contract, with several interventions aimed at improving contractual consent. In preembryo disposition disputes where the parties have not contracted, I argue for a general default rule of non-use, perhaps with a sub-rule permitting use when non-use would mean the impossibility of one party ever having any genetic children.

Originally edited by Timothy Stoltzfus Jost, this text examines how different countries around the world approach the same challenges in health care law and ethics: how to finance care for as many people as possible; how to ensure quality care; how to best secure patients' rights; how to regulate abortion, end of life decision making, and assisted reproduction; and how to manage infectious diseases, tobacco use, and human subject research. The new edition considers a broader array of countries, particularly from Asia, Latin America, Africa, and the Middle East.

For the average person, genetic testing has two very different faces. The rise of genetic testing is often promoted as the democratization of genetics by enabling individuals to gain insights into their unique makeup. At the same time, many have raised concerns that genetic testing and sequencing reveal intensely personal and private information. As these technologies become increasingly available as consumer products, the ethical, legal, and regulatory challenges presented by genomics are ever looming. Assembling multidisciplinary experts, this volume evaluates the different models used to deliver consumer genetics and considers a number of key questions: How should we mediate privacy and other ethical concerns around genetic databases? Does aggregating data from genetic testing turn people into products by commercializing their data? How might this data reduce or exacerbate existing healthcare disparities? Contributing authors also provide guidance on protecting consumer privacy and safety while promoting innovation.

In the last several months, several major disciplines have started their initial reckoning with what ChatGPT and other Large Language Models (LLMs) mean for them – law, medicine, business among other professions. With a heavy dose of humility, given how fast the technology is moving and how uncertain its social implications are, this article attempts to give some early tentative thoughts on what ChatGPT might mean for bioethics. I will first argue that many bioethics issues raised by ChatGPT are similar to those raised by current medical AI – built into devices, decision support tools, data analytics, etc. These include issues of data ownership, consent for data use, data representativeness and bias, and privacy. I describe how these familiar issues appear somewhat differently in the ChatGPT context, but much of the existing bioethical thinking on these issues provides a strong starting point. There are, however, a few “new-ish” issues I highlight – by new-ish I mean issues that while perhaps not truly new seem much more important for it than other forms of medical AI. These include issues about informed consent and the right to know we are dealing with an AI, the problem of medical deepfakes, the risk of oligopoly and inequitable access related to foundational models, environmental effects, and on the positive side opportunities for the democratization of knowledge and empowering patients. I also discuss how races towards dominance (between large companies and between the U.S. and geopolitical rivals like China) risk sidelining ethics.

Artificial Intelligence (AI), especially of the machine learning (ML) variety, is used by health care organizations to assist with a number of tasks, including diagnosing patients and optimizing operational workflows. AI products already proliferate the health care market, with usage increasing as the technology matures. Although AI may potentially revolutionize health care, the use of AI in health settings also leads to risks ranging from violating patient privacy to implementing a biased algorithm. This chapter begins with a broad overview of health care AI and how it is currently used. We then adopt a “lifecycle” approach to discussing issues with health care AI. We start by discussing the legal and ethical issues pertaining to how data to build AI are gathered in health care settings, focusing on privacy. Next, we turn to issues in algorithm development, especially algorithmic bias. We then discuss AI deployment to treat patients, focusing on informed consent. Finally, we will discuss existing oversight mechanisms for health AI in the United States: liability and regulation.

Medical crowdfunding has raised many ethical concerns, among them that it may undermine privacy, widen health inequities, and commodify health care. One motivation for medical crowdfunding has received particular attention among ethicists. Recent studies have shown that many individuals are using crowdfunding to finance access to scientifically unsupported medical treatments. Recently, GoFundMe prohibited campaigns for antivaccination groups on the grounds that they “promote misinformation about vaccines” and for treatment at a German clinic offering unproven cancer treatments due to “the need to make sure people are equipped to make well‐informed decisions.” GoFundMe has not taken any additional actions to regulate the much larger presence of campaigns seeking to fund unproven medical interventions on the platform. In this article, we make the ethical case for intervention by GoFundMe and other crowdfunding platforms.