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This book discusses the implementation of privacy by design in Europe, a principle that has been codified within the European Data Protection Regulation (GDPR). While privacy by design inspires hope for future privacy-sensitive designs, it also introduces the need for a common understanding of the legal and technical concepts of privacy and data protection. By pursuing an interdisciplinary approach and comparing the problem definitions and objectives of both disciplines, this book bridges the gap between the legal and technical fields in order to enhance the regulatory and academic discourse. The research presented reveals the scope of legal principles and technical tools for privacy protection, and shows that the concept of privacy by design goes beyond the principle of the GDPR. The book presents an analysis of how current regulations delegate the implementation of technical privacy and data protection measures to developers and describes how policy design must evolve in order to implement privacy by design and default principles.--

AbstractThe current political and regulatory discourse frequently references the term "trustworthy artificial intelligence (AI)." In Europe, the attempts to ensure trustworthy AI started already with the High‐Level Expert Group Ethics Guidelines for Trustworthy AI and have now merged into the regulatory discourse on the EU AI Act. Around the globe, policymakers are actively pursuing initiatives—as the US Executive Order on Safe, Secure, and Trustworthy AI, or the Bletchley Declaration on AI showcase—based on the premise that the right regulatory strategy can shape trust in AI. To analyze the validity of this premise, we propose to consider the broader literature on trust in automation. On this basis, we constructed a framework to analyze 16 factors that impact trust in AI and automation more broadly. We analyze the interplay between these factors and disentangle them to determine the impact regulation can have on each. The article thus provides policymakers and legal scholars with a foundation to gauge different regulatory strategies, notably by differentiating between those strategies where regulation is more likely to also influence trust on AI (e.g., regulating the types of tasks that AI may fulfill) and those where its influence on trust is more limited (e.g., measures that increase awareness of complacency and automation biases). Our analysis underscores the critical role of nuanced regulation in shaping the human‐automation relationship and offers a targeted approach to policymakers to debate how to streamline regulatory efforts for future AI governance.

Ambient assisted living (AAL) technologies are increasingly presented and sold as essential smart additions to daily life and home environments that will radically transform the healthcare and wellness markets of the future. An ethical approach and a thorough understanding of all ethics in surveillance/monitoring architectures are therefore pressing. AAL poses many ethical challenges raising questions that will affect immediate acceptance and long-term usage. Furthermore, ethical issues emerge from social inequalities and their potential exacerbation by AAL, accentuating the existing access gap between high-income countries (HIC) and low and middle-income countries (LMIC). Legal aspects mainly refer to the adherence to existing legal frameworks and cover issues related to product safety, data protection, cybersecurity, intellectual property, and access to data by public, private, and government bodies. Successful privacy-friendly AAL applications are needed, as the pressure to bring Internet of Things (IoT) devices and ones equipped with artificial intelligence (AI) quickly to market cannot overlook the fact that the environments in which AAL will operate are mostly private (e.g., the home). The social issues focus on the impact of AAL technologies before and after their adoption. Future AAL technologies need to consider all aspects of equality such as gender, race, age and social disadvantages and avoid increasing loneliness and isolation among, e.g. older and frail people. Finally, the current power asymmetries between the target and general populations should not be underestimated nor should the discrepant needs and motivations of the target group and those developing and deploying AAL systems. Whilst AAL technologies provide promising solutions for the health and social care challenges, they are not exempt from ethical, legal and social issues (ELSI). A set of ELSI guidelines is needed to integrate these factors at the research and development stage.