Historically global trade has not had a strong value-based focus. Despite these challenges, concepts related to human rights have slowly been seeping into international trade. This chapter will provide an overview of the increasing role of human rights and digital technology in export control regimes over the past two decades and how this has led to the expansion of export controls of surveillance technologies. It will take a particularly close look at the EU debate on export controls, human rights and digital technologies, before looking at China and India. We argue that export controls become a powerful way of inserting human rights into international trade. In contrast to claims that Internet regulation is fundamentally impossible, export controls provide a key example of how human rights norms can be embedded in technical Internet infrastructure by restricting the flow of surveillance technologies which are likely to have a negative human rights impact.

During a disaster, the timely provision of customised and relevant data is of utmost importance. In the case of floods, data from remote sensing (satellite-based or airborne) is often used, but in recent years data from social media platforms has also been increasingly utilised. Focusing on these data sources, this study provides an in-depth assessment of requirements by emergency responders. Furthermore, the paper sheds light on the legal and ethical considerations that need to be taken into account during data collection and processing. A particular focus lies on the use of artificial intelligence (AI) for data analysis in disaster response. Topics such as privacy preservation and AI-informed decision making are highlighted throughout the paper. The investigation was carried out based on expert interviews with scientists, an extensive literature review, and workshops with emergency responders.

More people voted in 2024 than any other year in human history, while often relying on the internet for political information. This combination resulted in critical challenges for democracy. To address these concerns, we designed an exhibition that applied interactive experiences to help visitors understand the impact of digitization on democracy. This late-breaking work addresses the research questions: 1) What do participants, exposed to playful interventions, think about these topics? and 2) How do people estimate their skills and knowledge about countering misinformation? We collected data in 5 countries through showcases held within weeks of relevant 2024 elections. During visits, participants completed a survey detailing their experiences and emotional responses. Participants expressed high levels of self-confidence regarding the detection of misinformation and spotting AI-generated content. This paper contributes to addressing digital literacy needs by fostering engaging interactions with AI and politically relevant issues surrounding campaigning and misinformation.

This chapter explores the concept of digital cultural sovereignty in European Cultural Heritage Institutions (CHIs), emphasising the intersection of cultural and digital sovereignty in their digitisation practices. The study aims to define digital cultural sovereignty - control and agency over cultural heritage, expressions, and identity in digital form - and its significance for creating inclusive digital transformation strategies. By mapping the digital practices of European CHIs and using a decolonial lens, the research identifies gaps in current methodologies and offers insights into the integration of cultural and digital sovereignty. The findings highlight examples of cross-cultural collaborations, outlining the challenges and opportunities for CHIs to promote digital cultural sovereignty. This research contributes to the field by providing strategies for CHIs to act as responsible custodians of culture, fostering a resilient socio-technical ecosystem that empowers communities locally and globally.

Human analysts working for threat intelligence leverage tools powered by artificial intelligence to routinely assemble actionable intelligence. Yet, threat intelligence sources and methods often have significant uncertainties and biases. In addition, data sharing might be limited for operational, strategic, or legal reasons. Experts are aware of these limitations but lack formal means to represent and quantify these uncertainties in their daily work. In this chapter, we enunciate the technical, legal, and societal challenges for building explainable AI for threat intelligence. We also discuss ideas for overcoming these challenges.

Accountability is considered a cornerstone of public administration and good governance. This study characterizes the relationship between the Dutch Intelligence and Secret Service (“AIVD”) and citizens (represented by parliament, courts, and oversight boards) as a complex actor-forum relationship. We utilize different accountability principles of public administration found in international and Dutch instruments and academic literature to propose workable principles of accountability for the AIVD. These proposed principles of accountability can be summarized as acting within duty, explainability, necessity, proportionality, reporting and record keeping, redress, and continuous independent oversight. Similarly, there are some conditions to support the workability of accountability principles. These conditions may be characterized as productive actor-forum relationships, cooperation, flexibility, value alignment, and learning and improving opportunities.

The AI Act represents a significant legislative effort by the European Union to govern the use of AI systems according to different risk-related classes, imposing different degrees of compliance obligations to users and providers of AI systems. However, it is often critiqued due to the lack of general public comprehension and effectiveness regarding the classification of AI systems to the corresponding risk classes. To mitigate these shortcomings, we propose a Decision-Tree-based framework aimed at increasing legal compliance and classification clarity. By performing a quantitative evaluation, we show that our framework is especially beneficial to individuals without a legal background, allowing them to enhance the accuracy and speed of AI system classification according to the AI Act. The qualitative study results show that the framework is helpful to all participants, allowing them to justify intuitively made decisions and making the classification process clearer.

Content moderation is a vital condition that online platforms must facilitate, according to the law, to create suitable online environments for their users. By the law, we mean national or European laws that require the removal of content by online platforms, such as EU Regulation 2021/784, which addresses the dissemination of terrorist content online. Content moderation required by these national or European laws, summarised here as ‘the law’, is different from the moderation of pieces of content that is not directly required by law but instead is conducted voluntarily by the platforms. New regulatory requests create an additional layer of complexity of legal grounds for the moderation of content and are relevant to platforms’ daily decisions. The decisions made are either grounded in reasons stemming from different sources of law, such as international or national provisions, or can be based on contractual grounds, such as the platform's Terms of Service and Community Standards. However, how to empirically measure these essential aspects of content moderation remains unclear. Therefore, we ask the following research question: How do online platforms interpret the law when they moderate online content? To understand this complex interplay and empirically test the quality of a platform's content moderation claims, this article develops a methodology that facilitates empirical evidence of the individual decisions taken per piece of content while highlighting the subjective element of content classification by human moderators. We then apply this methodology to a single empirical case, an anonymous medium-sized German platform that provided us access to their content moderation decisions. With more knowledge of how platforms interpret the law, we can better understand the complex nature of content moderation, its regulation and compliance practices, and to what degree legal moderation might differ from moderation due to contractual reasons in dimensions such as the need for context, information, and time. Our results show considerable divergence between the platform's interpretation of the law and ours. We believe that a significant number of platform legal interpretations are incorrect due to divergent interpretations of the law and that platforms are removing legal content that they falsely believe to be illegal (‘overblocking’) while simultaneously not moderating illegal content (‘underblocking’). In conclusion, we provide recommendations for content moderation system design that takes (legal) human content moderation into account and creates new methodological ways to test its quality and effect on speech in online platforms.

Content moderation is a vital condition that online platforms must facilitate according to the law and to create (adequate) online environments for their users. While new regulatory requests, like the Digital Services Act in the European Union create novel obligations for platforms, other legal dimensions like the law of Member States are an additional layer of legal grounds for the moderation of content and relevant for the decisions taken on a day-by-day basis. The decisions taken are either grounded in reasons stemming from law or can be based on contractual grounds like the platform’s Terms of Service and their Community Standards. How to measure these essential aspects of content moderation empirically however is still unclear. We therefore ask the following research question: How do online platforms interpret the law when they moderate online content?To understand this complex interplay and to test the quality of the platform’s content moderation claims empirically, this article develops a methodology that facilitates empirical evidence on the individual decisions taken per piece of content, while highlighting the subjective element of content classification by human moderators. We then apply this methodology to a single empirical case, an anonymous medium-sized German platform which has provided us access to their content moderation decisions. By better understanding how platforms interpret the law we can understand how complex content moderation, its regulation and compliance practices are, as well as to what degree legal moderation might differ from moderation due to contractual reasons in dimensions like the need for context, information, or time.Our results show a considerable divergence between the platforms interpretation of the law and our own interpretation. We believe that a significant number of platform legal interpretations are incorrect. These divergent interpretations of the law mean that we believe platforms are removing legal content that they falsely believe to be illegal (‘over-blocking’) while simultaneously not moderating illegal content (‘under-blocking’). In conclusions, we provide recommendations for content moderation system design that takes (legal) human content moderation into account and creates new methodological ways to test their quality and effect on speech on online platforms.

Safeguarding democratic elections is hard. Social media plays a vital role in the discourse around elections and during electoral campaigns. The following article provides an analysis of the ‘systemic electoral risks’ created by Twitter and Facebook and the mitigation strategies employed by the platforms. It is based on the 2020 proposal by the European Commission for the new Digital Services Act (DSA) in the context of the 2021 German federal elections. This article focuses on Twitter and Facebook and their roles during the German federal elections that took place on 26 September 2021. We analysed three systemic electoral risk categories: 1) the dissemination of illegal content, 2) negative effects on electoral rights, and 3) the influence of disinformation and developed systematic categories for this purpose. In conclusion, we discuss how to respond to these challenges as well as avenues for future research.

The UN sustainable development goals (SDGs) were adopted by the United Nations as a “universal call to action to end poverty, protect the planet, and ensure that by 2030 all people enjoy peace and prosperity.” These goals prove to have a strong appeal to managers in both public and private sectors. Despite the popularity of the goals, little is known about the consequences (intended and unintended, desired and undesired) of organisations adopting SDGs in their management practices. Therefore, our research question is: “What is the potential role of SDGs as an accountability mechanism?” The following article will study how organisations responsible for technological infrastructures in the Netherlands use the SDGs as an accountability mechanism. To do this, the authors will first provide an overview of the SDGs and how we conceptualize accountability. We will then present our case study methodology before looking at a single case study based on interviews with employees from three organizations running infrastructure in the Netherlands. Based on this case study, we will provide a broader analysis of the key tensions that are becoming apparent when using the SDGs as an accountability mechanism. In conclusion, we will argue that the SDGs may provide a valuable tool to make organizations more accountable to societal needs, however further shifts are needed in the way the accountability mechanisms are designed in order to ensure meaningful accountability.

The AI Act represents a significant legislative effort by the European Union to govern the use of AI systems according to different risk-related classes, linking varying degrees of compliance obligations to the system's classification. However, it is often critiqued due to the lack of general public comprehension and effectiveness regarding the classification of AI systems to the corresponding risk classes. To mitigate those shortcomings, we propose a Decision-Tree-based framework aimed at increasing robustness, legal compliance and classification clarity with the Regulation. Quantitative evaluation shows that our framework is especially useful to individuals without a legal background, allowing them to improve considerably the accuracy and significantly reduce the time of case classification.

Basic human rights, like freedom of expression, freedom of the press, and privacy, are being radically transformed by new technologies. The manifestation of these rights in online spaces is known as “digital rights,” which can be impeded or empowered through the design, governance, and litigation of emerging technologies. Design defines how people encounter the digital world. Some design choices can exploit the right to privacy by commodifying attention through tactics that keep users addicted to maximize profitability; similar design mechanisms and vulnerabilities have facilitated the abuse of journalists and human rights advocates across the globe. But design can also empower human rights, providing novel tools of resistance, accountability, and accessibility, as well as the inclusion of previously underserved voices in the development process. The new capabilities offered by these technologies often transcend political boundaries, presenting complex challenges for meaningful governance and regulation. To address these challenges, collaborations like the Internet Governance Forum and NETmundial have brought together stakeholders from governments, nonprofits, industry, and academia, with efforts to address digital rights like universal internet access. Concurrently, economic forces and international trade negotiations can have substantial impacts on digital rights, with attempts to enforce steeper restrictions on intellectual property. Private actors have also fought to ensure their digital rights through litigation. In Europe, landmark cases have reshaped the international management of data and privacy. In India, indefinite shutdowns of the internet by the government were found to be unconstitutional, establishing online accessibility as a fundamental human right, intimately tied with the right to assembly. And in Africa, litigation has helped ensure freedom of speech and of the press, rights that may affect more individualsas digital technologies continue to shape media. These three spheres—design, diplomacy, and law—illustrate the complexity and ongoing debate to define, protect, and communicate digital rights.

Safeguarding democratic elections is hard. Social media plays a vital role in the discourse around elections and during electoral campaigns. The following article provides an analysis of the 'systemic electoral risks' created by Twitter and Facebook and the mitigation strategies employed by the platforms. It is based on the 2020 proposal by the European Commission for the new Digital Services Act (DSA) in the context of the 2021 German federal elections. This article focuses on Twitter and Facebook and their roles during the German federal elections that took place on 26 September 2021. We analysed three systemic electoral risk categories: 1) the dissemination of illegal content, 2) negative effects on electoral rights, and 3) the influence of disinformation and developed systematic categories for this purpose. In conclusion, we discuss how to respond to these challenges as well as avenues for future research.

Technical systems accompany us in our everyday lives, interact with us, influence us and guide our decisions. However, these systems do not only consist of a technical aspect alone, but are much more socio-technically integrated into specific human application contexts. One example of such a socio-technical system is Google Maps.

Recent years have seen a massive growth in ethical and legal frameworks to govern data science practices. Yet one of the core questions associated with ethical and legal frameworks is the extent to which they are implemented in practice. A particularly interesting case in this context comes to public officials, for whom higher standards typically exist. We are thus trying to understand how ethical and legal frameworks influence the everyday practices on data and algorithms of public sector data professionals. The following paper looks at two cases: public sector data professionals (1) at municipalities in the Netherlands and (2) at the Netherlands Police. We compare these two cases based on an analytical research framework we develop in this article to help understanding of everyday professional practices. We conclude that there is a wide gap between legal and ethical governance rules and the everyday practices.

In a collaboration between TU Delft and Utrecht University, the authors recently wrote a qualitative study on the gap between regulatory (ethical and legal) frameworks and the daily practices of data professionals. This People of Data highlights the importance of collaboration in the success of interdisciplinary research and the responsibility of data scientists in safeguarding the public and ethical values.