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.@en

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.

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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.@en

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.@en

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. @en

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.@en

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.

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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.@en

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.@en

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.

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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.

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Content moderation is protecting human rights such as freedom of speech, as well as the right to impart and seek information. Online platforms implement rules to moderate content on their platforms through their Terms of Service (ToS), which provides for the legal grounds to delete content. Content moderation is an example of a socio-technical process. The architecture includes a layer that classifies content according to the ToS, followed by human moderation for selected pieces of content. New regulatory approaches, such as the Digital Services Act (DSA) or the Artificial Intelligence Act (AIA) demand more transparency and explainability for moderation systems and the decisions taken. Therefore, this article answers questions about the socio-technical sphere of human moderation: • How is certainty about content moderation decisions perceived within the moderation process? • How does the measurement of time affect content moderator’s work? • How much context is needed to take a content moderation decision? A sample of 1600 pieces of content was coded according to international and national law, as well as on the Community Standards developed by Meta, mimicking a content moderation scenario that includes lex specialis for content moderation – the German Network.@en

The internet is a place where the political opinion of voters is ever more formed on platforms and their user-generated content globally. A sphere in which the right to free- dom of expression, information and free and fair election are core human rights normative safeguards for our democracy. Securing this process for whoever is not an easy task, as examples like the 2016 US election, the Brexit campaign or the events of the 6th of Jan- uary 2021 illustrate. The European Union has taken regulatory action to secure the digital manifestations of elections, by issuing legislation like the General Data Protection Regu- lation, the Artificial Intelligence Act, the Digital Services Act (DSA)or the Proposal for a regulation of the European Parliament and the European council on the transparency and targeting of political advertising. The aim is to make platforms more transparent, regarding their algorithms deciding on recommendations, price of the ad, or to standardize content moderation to a certain degree. Platforms on the other hand use their Terms of Service (ToS) to implement their Community Standards – a selection of law-like clauses allowing for deletion or blocking of content – to set quasi-norms to safeguard democracy on- line. The ToS used by very large platforms (VLOP) according to Art 25 DSA however does not include granular clauses for European campaigning. The more recent design solutions on platforms include advertising repositories, or warning labels attached to problematic content to better inform the public. However, moderation of content addressing the heart of democracy and the democratic process per se is crucial for the status of human rights in Europe. The first decision taken on a piece of content – if it should be uploaded on the platform or not – is usually automated and controlled by machine learning algorithms. The system in place selects the pieces of content that will be decided upon in the next process step by a human. The moderation of political speech, however, is not solely text-based but does include a fine line of sarcastic elements, emojis or visual content to express itself which is another obstacle to moderating in an electoral context. This article, therefore, asks the question about how to better safeguard the right to fair elections, the right to freedom of expression and information in online campaigning and elections adhering to the recent European legislation, such as the GDPR, the DSA and the AIA and the proposal on the transparency and targeting of political advertising? The article answers the question by taking a closer look at the publicly available data published by platforms on behalf of their transparency reports. Furthermore, the ToS and Community Standards should be analyzed and compared. The process and architecture of content moderation for the selected online platforms are described and modelled according to the publicly available information. Only by providing a more concrete look at content moderation design and practice better solutions for the digital future of democracy can be crafted.@en

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.@en

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.@en

Users' perception of geographic space depends heavily on geographic information systems (GIS). GIS are the most common way for users to estimate travel time, provide routing information and recommend appropriate forms of transportation. This article analyses how predictions made by Google Maps, one of the most popular GIS, influence users' perceptions and travel choices. To analyze this influence, a pre-study in a classroom setting (n=36) as well as an online survey (n=521) were conducted. We study users intuitive perception of travel time, before using the Google Maps Mobile App as a'treatment' to see how it influences their perceptions of travel time and choice of transportation type. We then contrast this original Google Maps treatment to a mock-up'warning label version' of Google which informs users about biases in Google Maps and an'unbiased version' of Google Maps based on ground truth data. Our analysis suggests that Google Maps systematically underestimates necessary car driving time, which has an impact on users' choice of transportation.

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When the word 'ethical' becomes synonymous with specious, you know that something is amiss. With each data governance scandal, with each creation of a corporate 'ethics board', 'ethical standards' seemingly lose a few more feathers, to the point of generating instant suspicion when invoked in any official report. We argue that a key challenge in this regard is to more precisely define the ethics-regulation interface. In order to do this, we first provide an overview of recent endeavours to develop ethical frameworks around technology. We then look at a successful process of refinement of the ethics-regulation interface: the case of healthcare ethics in the UK. The third section develops an account of what a more robust ethics-regulation interface could look like, which would support a process of cross-fertilisation between the political, ethical and legal approaches. Finally, the fourth and last section critically examines a ‘live’ implementation of such ethics-regulation interface, as put forward in Quebec's ‘Bill 29′.

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