The availability of data is a condition for the development of AI. This is no different in the context of healthcare-related AI applications. Healthcare data are required in the research, development, and follow-up phases of AI. In fact, data collection is also necessary to establish evidence of compliance with legislation. Several legislative instruments, such as the Medical Devices Regulation and the AI Act, enacted data collection obligations to establish (evidence of) the safety of medical therapies, devices, and procedures. Increasingly, such health-related data are collected in the real world from individual data subjects. The relevant legal instruments therefore explicitly mention they shall be without prejudice to other legal acts, including the GDPR. Following an introduction to real-world data, evidence, and electronic health records, this chapter considers the use of AI for healthcare from the perspective of healthcare data. It discusses the role of data custodians, especially when confronted with a request to share healthcare data, as well as the impact of concepts such as data ownership, patient autonomy, informed consent, and privacy and data protection-enhancing techniques.

The chapter examines a classic subject of HRI, social robotics, and the law, such as the design, manufacture, and use of humanoid AI robots for healthcare. The aim is to illustrate a new set of legal challenges that are unique to these systems when displayed in outer space. Such challenges may require the adoption of new legal standards, in particular, either sui generis standards of space law, or stricter or more flexible standards for HRI in space missions, down to a new “principle of equality” between human standards and robotic standards in outer space. The chapter complements current discussions and initiatives on the development of standards for the use of humanoid AI robots in health law, consumer law, and cybersecurity by considering the realignment of terrestrial standards that we may thus expect with the increasing use of humanoid AI systems in space journeys. The assumption is that breathtaking advancements of AI and robotics, current trends on the privatization of the space, and the evolution of current regulatory frameworks, also but not only in space law, will put the development of these new legal standards in the spotlight.

This chapter offers lessons from engineering and other industries that promise developments in healthcare, and practical guidance for clinician-engineer partnerships. Section 1 provides guidance on how to establish a shared vocabulary and common understanding between engineers and clinicians of what terms such as AI and ML do and don’t mean. Section 2 identifies challenges clinician-engineering partnerships must overcome to deliver sustained value and ways to avoid common causes of failure. Section 3 provides specific advice on how to design projects to produce value at a series of stages rather than rely on the success of one, ambitious final model. Section 4 concludes by drawing on cautionary lessons from healthcare and other industries.

INTRODUCTION

• 1. In this chapter, I will first discuss the rise of robotics and AI in the healthcare sector and the concern of some scholars that this may lead to a dehumanisation of the physician-patient relationship (part 2). I will then elaborate on four potential existing legal safeguards against such dehumanisation: the fact that only qualified persons are allowed to provide healthcare (part 3) and the resulting liability of the physician if things go wrong (part 4); the right of the patient to receive information about his/her health condition and to give his/her prior informed consent under the Belgian Law on Patient Rights (part 5), and finally transparency and informed consent under the General Data Protection Regulation (GDPR) (part 6). I will conclude with an overview (part 7).

THE RISE OF ROBOTICS AND AI TO DEAL WITH INCREASING DEMANDS IN THE HEALTHCARE SECTOR

• 2. A recent publication commissioned by the European Parliament states that the health sector is facing increasing demands on services brought on by issues such as an ageing population, an increase of chronic diseases, budgetary constraints, and a shortage of qualified workers. Developments in the field of robotics and AI can provide countless opportunities for addressing these challenges, resulting in necessary and significant cost and time savings. These efficiency benefits are the result of the fact the work is done more efficiently, more quickly and at a lower cost than a human actor could do it. According to the same study, the application of robotics and AI could lead to improvements in fields such as medical diagnosis, surgical intervention, prevention and treatment of diseases, and support for rehabilitation and longterm care. They could also contribute to more effective and automated work management processes, while offering continuous training for healthcare workers. It is estimated that the market for AI in healthcare will reach around $6,6 billion by 2021 and $8 billion by 2022, with significant cost savings for healthcare systems. According to a recent French study, the health sector is internationally the second most impacted sector by robotics and AI after the telecommunications and technologies sector, but preceding the financial services and automotive sector.

Many ethical questions about our future with intelligent machines rest upon assumptions concerning the origins, development and ideal future of humanity and of the universe, and hence overlap considerably with many religious questions. First, could computers themselves become moral in any sense, and could different components of morality – whatever they are – be instantiated in a computer? Second, could computers enhance the moral functioning of humans? Do computers potentially have a role in narrowing the gap between moral aspiration and how morality is actually lived out? Third, if we develop machines comparable in intelligence to humans, how should we treat them? This question is especially acute for embodied robots and human-like androids. Fourthly, numerous moral issues arise as society changes such that artificial intelligence plays an increasingly significant role in making decisions, with implications for how human beings function socially and as individuals, treat each other and access resources.

This paper presents the main topics, arguments, and positions in the philosophy of AI at present (excluding ethics). Apart from the basic concepts of intelligence and computation, the main topics of artificial cognition are perception, action, meaning, rational choice, free will, consciousness, and normativity. Through a better understanding of these topics, the philosophy of AI contributes to our understanding of the nature, prospects, and value of AI. Furthermore, these topics can be understood more deeply through the discussion of AI; so we suggest that “AI philosophy” provides a new method for philosophy.

In this chapter, Fruzsina Molnár-Gábor and Johanne Giesecke consider specific aspects of how the application of AI-based systems in medical contexts may be guided under international standards. They sketch the relevant international frameworks for the governance of medical AI. Among the frameworks that exist, the World Medical Association’s activity appears particularly promising as a guide for standardisation processes. The organisation has already unified the application of medical expertise to a certain extent worldwide, and its guidance is anchored in the rules of various legal systems. It might provide the basis for a certain level of conformity of acceptance and implementation of new guidelines within national rules and regulations, such as those on new technology applications within the AI field. In order to develop a draft declaration, the authors then sketch out the potential applications of AI and its effects on the doctor–patient relationship in terms of information, consent, diagnosis, treatment, aftercare, and education. Finally, they spell out an assessment of how further activities of the WMA in this field might affect national rules, using the example of Germany.

It is only recently that the EPO’s Boards of Appeal have had to deal with appeals relating to the surge of AI based inventions. In doing so the Boards of Appeal have adopted a gradualist approach, adapting the extensive EPO case law relating to the patentability of computer programs ‘as such’ and applying it to AI inventions. The most recent change to the Guidelines indicates the EPO’s willingness to adapt to technological developments and to refine its approach to patentability of inventions involving AI, while at the same time taking a firm line against patenting non-technical inventions.