Recently, the concept of sovereignty in the digital has attracted much attention. Several publications dealing with this concept assume that it can best be described as a network of different, overlapping exercises of power. Nevertheless, there is a need for further research on how exactly sovereignty in the digital can be understood. In order to contribute to a better understanding of this concept, I illustrate its complex structure using contact tracing apps as a paradigmatic example. I conduct a narrative review to show what sovereignty looks like in the context of these apps. In the context of digital contact tracing apps, sovereignty is best understood as a complex network of three actors—nations, (big tech) companies, and individuals—that exercise various forms of power against or on behalf of each other to claim sovereignty for themselves and to either weaken or strengthen the sovereignty claims of other actors. Since large parts of the results can be generalized from the particular context of contact tracing apps, they contribute to a better overall understanding of the concept of sovereignty in digital. This might, in turn, be helpful for discussions about this technology as well as about the regulation and governance of the digital in general.

Harnessing the metaverse for medical and healthcare purposes is currently heralded as the “next frontier in healthcare.” However, to ensure the “amazing possibilities” of the so-called “healthcare metaverse” can be fully realized, it’s vital to proactively identify and address potential challenges, especially those of an ethical nature. This paper aims to spotlight these ethical challenges within the healthcare metaverse and chart a course for confronting these issues and cultivating an ethics framework for this emerging field. We will demonstrate that the ethical quandaries within the healthcare metaverse bear striking similarities to those seen in digital medicine, an arena that grapples with vast quantities of data and the application of artificial intelligence. Reflecting on these parallels, we explore how six central ethical challenges in digital medicine – 1) accessibility, 2) fairness, 3) discrimination and bias, 4) responsibility, 5) privacy, data safety and security, and data ownership, as well as 6) environmental issues – unfold within the healthcare metaverse’s virtual boundaries and show that the metaverse’s immersive nature further intensifies these ethical challenges. In view of this, we advocate that the next phase in forging ethics for the healthcare metaverse involves a nuanced reconsideration of current ethical methods and principles in digital medicine, with an emphasis on the immersive element of the metaverse. We foresee the concept of embodiment within virtual settings to be at the heart of this immersion-focused reassessment.

Since uncertainty is a major challenge in medicine and bears the risk of causing incorrect diagnoses and harmful treatment, there are many efforts to tackle it. For some time, AI technologies have been increasingly implemented in medicine and used to reduce medical uncertainties. What initially seems desirable, however, poses challenges. We use a multimethod approach that combines philosophical inquiry, conceptual analysis, and ethical considerations to identify key challenges that arise when AI is used for medical certainty purposes. We identify several challenges. Where AI is used to reduce medical uncertainties, it is likely to result in (a) patients being stripped down to their measurable data points, and being made disambiguous. Additionally, the widespread use of AI technologies in health care bears the risk of (b) human physicians being pushed out of the medical decision-making process, and patient participation being more and more limited. Further, the successful use of AI requires extensive and invasive monitoring of patients, which raises (c) questions about surveillance as well as privacy and security issues. We outline these several challenges and show that they are immediate consequences of AI-driven security efforts. If not addressed, they could entail unfavorable consequences. We contend that diminishing medical uncertainties through AI involves a tradeoff. The advantages, including enhanced precision, personalization, and overall improvement in medicine, are accompanied by several novel challenges. This paper addresses them and gives suggestions about how to use AI for certainty purposes without causing harm to patients.

Political decision-making is often riddled with uncertainties, largely due to the complexities and fluid nature of contemporary societies, which make it difficult to predict the consequences of political decisions. Despite these challenges, political leaders cannot shy away from decision-making, even when faced with overwhelming uncertainties. Thankfully, there are tools that can help them manage these uncertainties and support their decisions. Among these tools, Artificial Intelligence (AI) has recently emerged. AI-systems promise to efficiently analyze complex situations, pinpoint critical factors, and thus reduce some of the prevailing uncertainties. Furthermore, some of them have the power to carry out in-depth simulations with varying parameters, predicting the consequences of various political decisions, and thereby providing new certainties. With these capabilities, AI-systems prove to be a valuable tool for supporting political decision-making. However, using such technologies for certainty purposes in political decision-making contexts also presents several challenges—and if these challenges are not addressed, the integration of AI in political decision-making could lead to adverse consequences. This paper seeks to identify these challenges through analyses of existing literature, conceptual considerations, and political-ethical-philosophical reasoning. The aim is to pave the way for proactively addressing these issues, facilitating the responsible use of AI for managing uncertainty and supporting political decision-making. The key challenges identified and discussed in this paper include: (1) potential algorithmic biases, (2) false illusions of certainty, (3) presumptions that there is no alternative to AI proposals, which can quickly lead to technocratic scenarios, and (4) concerns regarding human control.

It is important to accompany the research on Emotional Artificial Intelligence with ethical oversight. Previous publications on the ethics of Emotional Artificial Intelligence emphasize the importance of subjecting every (possible) type of Emotional Artificial Intelligence to separate ethical considerations. That’s why, in this contribution I will focus on a particular subset of AI systems: AI-driven Decision-Support Systems (AI-DSS), and ask whether it would be advisable from an ethical perspective to equip these AI systems with emotional capacities. I will show, on one hand, equipping AI-DSS with emotional capabilities offers great opportunities, as they open the possibility to prevent emotionally biased decisions – but that it also amplifies the ethical challenges already posed by emotionally-incapable AI-DSS. Yet, if their introduction is accompanied by a broad social discourse and prepared by suitable measures to address these challenges, I argue, nothing should fundamentally stand in the way of equipping AI-DSS with emotional capabilities.