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AbstractThe concept of Meaningful Human Control (MHC) has gained prominence in the field of Artificial Intelligence ethics. MHC is discussed in relation to lethal autonomous weapons, autonomous cars, and more recently, AI systems in general. Little, however, has been done to analyze the concept. Those using MHC tend to look at it narrowly and intuitively—as if it is clear what it means. They fail to see the many issues concerning human control over machines. In this article, I break the concept into its three constitutive words ('meaningful', 'human', and, 'control') to outline the many meanings of MHC. While the intention is not to come to therealmeaning of MHC, this analysis brings up the many issues that should be considered if meaningful human control is to be realized. These include: which humans count as meaningful in the application context, whether the control those humans are given must be meaningful, whether humans must retain control over the things that are meaningful in life, whether the style of control is human-like, whether each actor (designer, operator, subject, government) has the control they need, and what it is exactly that a human is controlling (e.g., the training data, the inputs, the outputs, etc. of the AI system).

Transparency is important for liberal democracies; however, the value of transparency is difficult to articulate. In this article we articulate transparency as an instrumental value for providing what we call ensurance and assurance to liberal democratic citizens. Ensurance refers to the property of liberal democracies which prevents it from sliding into authoritarianism and assurance is the property whereby citizens are assured that ensurance exists. Looking at the rise of bulk data collection and use afforded by information communication technologies, this paper focuses on the way that technologies disrupt relations between the state and its citizens, and suggests Value Sensitive Design as a methodology to protect key aspects of liberal democracies. Bulk data collection makes the achieving of ensurance and assurance more difficult due to two types of opacity which arise as a result of the practice: technical opacity-the difficulty for citizens to understand the technology behind bulk data collection; and, algorithmic opacity-opacity which results from properties inherent to algorithms which guide the collection and processing of bulk data. Design requirements will be suggested to respond to the disruptions caused by ICTs between liberal democracies and their citizens which threaten the necessary value for liberal democracies of representativeness.

Given recognition of widespreadstate sponsored surveillance programs, areliberal democraciesdescending into an Orwellianauthoritarian nightmare? The realities of the modern surveillance state instead suggest ourworries ought to be about Kafkaesquebureaucratic black holes. In this paper we suggest thatauthoritarianism can be avoidedbyliberal democracies if they adhere to processes ofensurance and assurance. Moreover, we argue thatboth of these attributes are instrumentally enabled by transparency.

Chapter 1: Introduction: Understanding and Regulating Al-Powered Recommender systems -- Part I: Fairness and Transparency -- Chapter 2: Recommender Systems and Discrimination -- Chapter 3: From Algoritmic Transparency to Algorithmic Choice: European Perspectives on Recommender Systems and Platform Regulation -- Chapter 4: Black Hole instead of Black Box? - The Double Opaqueness of Recommender Systems on Gaming Platforms and its Legal Implications -- Chapter 5: Digital Labor as a Structural Fairness Issue in Recommender Systems -- Part II: Manipulation and Personal Autonomy -- Chapter 6: Recommender Systems, Manipulation and Private Autonomy - How European civil law regulates and should regulate recommender systems for the benefit of private autonomy -- Chapter 7: Reasoning with Recommender Systems? Practical Reasoning, Digital Nudging, and Autonomy -- Chapter 8: Recommending Ourselves to Death: values in the age of algorithms -- Part III: Designing and Evaluating Recommender Systems -- Chapter 9: Ethical and Legal Analysis of Machine Learning Based Systems: A Scenario Analysis of a Food Recommender System -- Chapter 10: Factors influencing trust and use of recommendation AI: A case study of diet improvement AI in Japan -- Chapter 11: Ethics of E-Learning Recommender Systems: Epistemic Positioning and Ideological Orientation.

This open access book brings together a range of contributions that seek to explore the ethical issues arising from the overlap between counter-terrorism, ethics, and technologies. Terrorism and our responses pose some of the most significant ethical challenges to states and people. At the same time, we are becoming increasingly aware of the ethical implications of new and emerging technologies. Whether it is the use of remote weapons like drones as part of counter-terrorism strategies, the application of surveillance technologies to monitor and respond to terrorist activities, or counterintelligence agencies use of machine learning to detect suspicious behavior and hacking computers to gain access to encrypted data, technologies play a significant role in modern counter-terrorism. However, each of these technologies carries with them a range of ethical issues and challenges. How we use these technologies and the policies that govern them have broader impact beyond just the identification and response to terrorist activities. As we are seeing with China, the need to respond to domestic terrorism is one of the justifications for their rollout of the "social credit system." Counter-terrorism technologies can easily succumb to mission creep, where a technology's exceptional application becomes normalized and rolled out to society more generally. This collection is not just timely but an important contribution to understand the ethics of counter-terrorism and technology and has far wider implications for societies and nations around the world.

This open access book brings together a range of contributions that seek to explore the ethical issues arising from the overlap between counter-terrorism, ethics, and technologies. Terrorism and our responses pose some of the most significant ethical challenges to states and people. At the same time, we are becoming increasingly aware of the ethical implications of new and emerging technologies. Whether it is the use of remote weapons like drones as part of counter-terrorism strategies, the application of surveillance technologies to monitor and respond to terrorist activities, or counterintelligence agencies use of machine learning to detect suspicious behavior and hacking computers to gain access to encrypted data, technologies play a significant role in modern counter-terrorism. However, each of these technologies carries with them a range of ethical issues and challenges. How we use these technologies and the policies that govern them have broader impact beyond just the identification and response to terrorist activities. As we are seeing with China, the need to respond to domestic terrorism is one of the justifications for their rollout of the "social credit system." Counter-terrorism technologies can easily succumb to mission creep, where a technology's exceptional application becomes normalized and rolled out to society more generally. This collection is not just timely but an important contribution to understand the ethics of counter-terrorism and technology and has far wider implications for societies and nations around the world.