Artificial Intelligence (AI) is revolutionizing the way content is produced and integrated into journalistic workflows. The EU AI act’s Article 50 sets up transparency requirements aimed at encouraging the adoption and disclosure of AI in an ethical and responsible manner. In this study, we organized focus group interviews with Dutch citizens (N=21) to understand their expectations and needs regarding AI disclosures in the context of news production and journalism. These conversations are essential to understand if legal and regulatory policies are grounded in real-world experiences of citizens, and adequately address their concerns and enhance their digital interactions. We found that citizens predominantly favor disclosures of AI usage in journalistic content, in the form of (1) source references, (2) visual indicators (logos/watermarks) and (3) have varying preferences regarding information presentation and interaction modalities. Our findings highlight the need for interdisciplinary approaches to align standardization efforts with AI disclosures for news media.

The article “The Rise of Technology Courts” explores the evolving role of courts in the digital world, where technological advancements and artificial intelligence (AI) are transforming traditional adjudication processes. It argues that traditional courts are undergoing a significant transition due to digitization and the increasing influence of technology companies. The paper frames this transformation through the concept of the “sphere of the digital,” which explains how digital technology and AI redefine societal expectations of what courts should be and how they function. The article highlights that technology is not only changing the materiality of courts—moving from physical buildings to digital portals—but also affecting their symbolic function as public institutions. It discusses the emergence of AI-powered judicial services, online dispute resolution (ODR), and technology-driven alternative adjudication bodies like the Meta Oversight Board. These developments challenge the traditional notions of judicial authority, jurisdiction, and legal expertise. The paper concludes that while these technology-driven solutions offer increased efficiency and accessibility, they also raise fundamental questions about the legitimacy, transparency, and independence of adjudicatory bodies. As technology companies continue to shape digital justice, the article also argues that there are lessons to learn for the role and structure of traditional courts to ensure that human rights and public values are upheld.

Recommender systems are the algorithms which select, filter, and personalize content across many of the world's largest platforms and apps. As such, their positive and negative effects on individuals and on societies have been extensively theorized and studied. Our overarching question is how to ensure that recommender systems enact the values of the individuals and societies that they serve. Addressing this question in a principled fashion requires technical knowledge of recommender design and operation, and also critically depends on insights from diverse fields including social science, ethics, economics, psychology, policy, and law. This article is a multidisciplinary effort to synthesize theory and practice from different perspectives, with the goal of providing a shared language, articulating current design approaches, and identifying open problems. We collect a set of values that seem most relevant to recommender systems operating across different domains, and then examine them from the perspectives of current industry practice, measurement, product design, and policy approaches. Important open problems include multi-stakeholder processes for defining values and resolving trade-offs, better values-driven measurements, recommender controls that people use, non-behavioral algorithmic feedback, optimization for long-term outcomes, causal inference of recommender effects, academic-industry research collaborations, and interdisciplinary policy-making.

The COVID-19 pandemic has created one of the largest medical, financial, and social disruption in history. In the fight against this virus, many European governments have turned to collecting and using online data (for various technological applications) as a key strategic remedy. This study consists of data from a national representative survey in the Netherlands focusing on the extent to which data-driven technologies from the government can count on the support of the general public. By focusing on trust perceptions, risk beliefs and privacy concerns, we introduce a typology consisting of three subgroups: the sceptical, the carefree, and the neutral respondents. It was found that each of the three groups exhibit unique demographic characteristics. In addition, findings also revealed that these three identified groups have different support levels for specific digital solutions from the government. These findings contribute to an important and timely debate and entail relevant policy implications with regard to the democratic legitimation of data-driven technologies in times of COVID-19.

News recommenders help users to find relevant online content and have the potential to fulfill a crucial role in a democratic society, directing the scarce attention of citizens towards the information that is most important to them. Simultaneously, recent concerns about so-called filter bubbles, misinformation and selective exposure are symptomatic of the disruptive potential of these digital news recommenders. Recommender systems can make or break filter bubbles, and as such can be instrumental in creating either a more closed or a more open internet. Current approaches to evaluating recommender systems are often focused on measuring an increase in user clicks and short-term engagement, rather than measuring the user's longer term interest in diverse and important information.

The ongoing substitution of human decision makers by automated decision-making (ADM) systems in a whole range of areas raises the question of whether and, if so, under which conditions ADM is acceptable and fair. So far, this debate has been primarily led by academics, civil society, technology developers and members of the expert groups tasked to develop ethical guidelines for ADM. Ultimately, however, ADM affects citizens, who will live with, act upon and ultimately have to accept the authority of ADM systems. The paper aims to contribute to this larger debate by providing deeper insights into the question of whether, and if so, why and under which conditions, citizens are inclined to accept ADM as fair. The results of a survey (N = 958) with a representative sample of the Dutch adult population, show that most respondents assume that AI-driven ADM systems are fairer than human decision-makers. A more nuanced view emerges from an analysis of the responses, with emotions, expectations about AI being data- and calculation-driven, as well as the role of the programmer – among other dimensions – being cited as reasons for (un)fairness by AI or humans. Individual characteristics such as age and education level influenced not only perceptions about AI fairness, but also the reasons provided for such perceptions. The paper concludes with a normative assessment of the findings and suggestions for the future debate and research.