In this chapter, Philipp Kellmeyer discusses how to protect mental privacy and mental integrity in the interaction of AI-based neurotechnology from the perspective of philosophy, ethics, neuroscience, and psychology. The author argues that mental privacy and integrity are important anthropological goods that need to be protected from unjustified interferences. He then outlines the current scholarly discussion and policy initiatives about neurorights and takes the position that while existing human rights provide sufficient legal instruments, an approach is required that makes these rights actionable and justiciable to protect mental privacy and mental integrity, for example, by connecting fundamental rights to specific applied laws.

The author spells out the different key features of AI systems, introducing inter alia the notions of machine learning and deep learning as well as the use of AI systems as part of robotics.

In this chapter, the philosopher Christoph Durt elaborates a novel view on AI and its relation to humans. He contends that AI is neither merely a tool, nor an artificial subject, nor necessarily a simulation of human intelligence. These misconceptions of AI have led to grave misunderstandings of the opportunities and dangers of AI. A more comprehensive concept of AI is needed to better understand the possibilities of responsible AI. The chapter shows the roots of the misconceptions in the Turing Test. The author argues that the simplicity of the setup of the Turing Test is deceptive, and that Turing was aware that the text exchanges can develop in much more intricate ways than usually thought. The Turing Test only seemingly avoids difficult philosophical questions by passing on the burden to an evaluator, who is part of the setup, and hides in plain sight his or her decisive contribution. Durt shows that, different from all previous technology, AI processes meaningful aspects of the world as experienced and understood by humans. He delineates a more comprehensive picture according to which AI integrates into the human lifeworld through its interrelations with humans and data.

In this chapter, the law scholar Boris Paal identifies a conflict between two objectives pursued by the data protection law, the comprehensive protection of privacy and personal rights and the facilitation of an effective and competitive data economy. Focusing on the European Union’s General Data Protection Regulation (GDPR), the author recognises its failure to address the implications of AI, the development of which depends on the access to large amounts of data. The regulation is observed as not only immensely burdensome for controllers but also likely to significantly limit the output of AI-based applications. In general, the main principles of the GDPR seem to be in direct conflict with the functioning and underlying mechanisms of AI applications, which evidently, were not considered sufficiently whilst the regulation was being drafted. Hence, Paal argues that establishing a separate legal basis governing the permissibility of processing operations using AI-based applications should be considered; the enhanced legal framework should seek to reconcile data protection with the openness for new opportunities of AI developments.

In this chapter, political philosopher Alex Leveringhaus asks whether Lethal Autonomous Weapons (AWS) are morally repugnant and whether this entails that they should be prohibited by international law. To this end, Leveringhaus critically surveys three prominent ethical arguments against AWS: firstly, AWS create ‘responsibility gaps’; secondly, that their use is incompatible with human dignity; and ,thirdly, that AWS replace human agency with artificial agency. He argues that some of these arguments fail to show that AWS are morally different from more established weapons. However, the author concludes that AWS are currently problematic due to their lack of predictability.

In this chapter, the law scholar Ebrahim Afsah outlines different implications of AI for the area of national security. He argues that while AI overlaps with many challenges to the national security arising from cyberspace, it also creates new risks, including the emergence of a superintelligence in the future, the development of autonomous weapons, the enhancement of existing military capabilities, and threats to foreign relations and economic stability. Most of these risks, however, Afsah concludes, can be subsumed under existing normative frameworks.

To answer the question of what responsible AI means, the authors, Jaan Tallinn and Richard Ngo, propose a framework for the deployment of AI which focuses on two concepts: delegation and supervision. The framework aims towards building ‘delegate AIs’ which lack goals of their own but can perform any task delegated to them. However, AIs trained with hardcoded reward functions, or even human feedback, often learn to game their reward signal instead of accomplishing their intended tasks. Thus, Tallinn and Ngo argue that it will be important to develop more advanced techniques for continuous high-quality supervision – for example, by evaluating the reasons which AIs give for their choices of actions. These supervision techniques might be made scalable by training AIs to generate reward signals for more advanced AIs. Given their current limitations, however, Tallinn and Ngo call for caution when developing new AI: we must be aware of the risks and overcome self-interest and dangerous competitive incentives in order to avoid them.

The philosopher Wilfried Hinsch focuses on statistical discrimination by means of computational profiling. He defines statistical profiling as an estimate of what individuals will do by considering the group of people they can be assigned to. The author explores which criteria of fairness and justice are appropriate for the assessment of computational profiling. According to Hinsch, grounds of discrimination such as gender or ethnicity do not explain when or why it is wrong to discriminate. Thus, Hinsch argues that discrimination constitutes a rule-guided social practice that imposes unreasonable burdens on specific people. He argues that, on the one hand, statistical profiling is a part of human nature and not by itself wrongful discrimination. However, on the other hand, even statistically correct profiles can be unacceptable considering reasons of procedural fairness or substantive justice. Because of this, Hinsch suggests a fairness index for profiles to determine procedural fairness; and argues that because AI systems do not rely on human stereotypes or rather limited data, computational profiling may be a better safeguard of fairness than humans.

The chapter aims to serve as a conceptual sketch for the intricacies involved in autonomous algorithmic collusion, including the notion of concerted practices for cases that would otherwise elude the cartel prohibition. Stefan Thomas, a law scholar, starts by assessing how algorithms can influence competition in markets before dealing with the traditional criteria of distinction between explicit and tacit collusion, which might reveal a potential gap in the existing legal framework regarding algorithmic collusion. Finally, he analyses whether the existing cartel prohibition can be construed in a way that captures the phenomenon appropriately. This chapter shows how enforcement paradigms that hinge on descriptions of the inner sphere and conduct of human beings may collapse when applied to the effects precipitated by independent AI based computer agents.

In this chapter the law scholars Haksoo Ko, Sangchul Park, and Yong Lim, analyse the way South Korea has been dealing with the COVID-19 pandemic and its legal consequences. Instead of enforcing strict lockdowns, South Korea imposed several other measures, such as a robust AI-based contact tracing scheme. The chapter provides an overview of the legal framework and the technology which allowed South Korea to employ its technology-based contact tracing scheme. Additionally, the authors showcase the information system South Korea implemented, as well as the actual use of the data. The authors argue that South Korea has a rather stringent data-protection regime, which proved to be the biggest hurdle in implementing the contact tracing scheme. However, the country introduced a separate legal framework for extensive contact tracing after its bruising encounter with the Middle East Respiratory Syndrome (MERS) in 2015 which was reactivated and provided government agencies with extensive authority to process personal data for epidemiological purposes. The AI-based technology built in the process of creating smart cities also proved handy as it was repurposed for contact tracing purposes.

The law scholar Dustin Lewis explores the requirements of international law with regard to the employments of AI-related tools and techniques in armed conflict. The scope of this chapter is not limited to Lethal Autonomous Weapons (AWS) but also encompasses other AI-related tools and techniques related to warfighting, detention, and humanitarian services. After providing an overview of international law applicable to armed conflict, the author outlines some preconditions necessary to respect international law. According to Lewis, current international law essentially presupposes humans – and not artificial, non-humans – as legal agents. From that premise, the author argues that any employment of AI-related tools or techniques in an armed conflict needs to be susceptible to being administered, discerned, attributed, understood, and assessed by human agents.

In the past decade, Artificial Intelligence (AI) as a general-purpose tool has become a disruptive force globally. By leveraging the power of artificial neural networks, deep learning frameworks can now translate text from hundreds of languages, enable real-time navigation for everyone, recognise pathological medical images, as well as enable many other applications across all sectors in society. However, the enormous potential for innovation and technological advances and the chances that AI systems provide come with hazards and risks that are not yet fully explored, let alone fully understood. One can stress the opportunities of AI systems to improve healthcare, especially in times of a pandemic, provide automated mobility, support the protection of the environment, protect our security, and otherwise support human welfare. Nevertheless, we must not neglect that AI systems can pose risks to individuals and societies; for example by disseminating biases, by undermining political deliberation, or by the development of autonomous weapons. This means that there is an urgent need for responsible governance of AI systems. This Handbook shall be a basis to spell out in more detail what could become relevant features of Responsible AI and how we can achieve and implement them at the regional, national, and international level. Hence, the aim of this Handbook is to address some of the most pressing philosophical, ethical, legal, and societal challenges posed by AI.

In this chapter, the philosophers Oliver Mueller and Boris Essmann address AI-supported neurotechnology, especially Brain–Computer Interfaces (BCIs) that may in the future supplement and restore functioning in agency-limited individuals or even augment or enhance capacities for natural agency. The authors propose a normative framework for the evaluation of neurotechnological and AI-assisted agency based on ‘cyberbilities’. These are capabilities that emerge from human–machine interactions in which agency is distributed across human and artificial elements. The authors conclude by providing a list of cyberbilities that is meant to support the well-being of individuals.

The chapter by the philosopher Catrin Misselhorn provides an overview of the most central debates in artificial morality and machine ethics. Artificial moral agents are AI systems which are able to recognise the morally relevant aspects of a situation and take them into account in their decisions and actions. Misselhorn shows that artificial morality is not just a matter of Science Fiction scenarios but rather an issue that has to be considered today. She lays the conceptual foundations of artificial morality and discusses the ethical issues that arise. She addresses questions like: which morality should be part of an AI system? Can AI systems be aligned with human morality, or do they need a machine-specific morality? Are there decisions, which should never be transferred to machines? Could artificial morality have impacts on human morality if it becomes more pervasive? These and other questions relating to AI are discussed and answered.