arXiv subjects

Marie-Therese Sekwenz

Publications and source records attributed to Marie-Therese Sekwenz.

8 recordsLinked to original sources

arXiv2026

Click, Branch, Audit: A Decision-Tree Toolkit for Assessing Fundamental Rights Impacts under the Digital Services Act of Very Large Platforms & Search Engines

The EU Digital Services Act (DSA) requires Very Large Online Platforms and Search Engines (VLOPs/VLOSEs) to assess and mitigate systemic risks, including actual or foreseeable negative effects on fundamental rights, and subjects these assessments to independent audit. Yet how such rights-relevant risks should be identified, assessed, evidenced, and documented remains methodologically under-specified. We address this gap by introducing a decision-tree-based toolkit that operationalizes Article 34(1)(b) DSA and related audit requirements into a structured assessment process. The toolkit decomposes platforms as systems-of-systems and guides assessors through DSA applicability, context definition, subsystem and stakeholder identification, risk identification, risk assessment, reporting, and visualization. A central design contribution is its treatment of vulnerability as situational and relational: rather than assigning vulnerability to fixed groups, the toolkit asks how particular platform subsystems and dependencies may place stakeholders in vulnerable positions. It further makes fundamental rights-relevant judgments traceable by recording the affected right, interference and justification analysis within the structure of a proportionality test, while also covering a perception and impact dimension including severity, scope, duration, reversibility, as well as practical consequences. We developed the toolkit iteratively through a design-science process combining literature-derived design requirements, three interdisciplinary expert workshops (N=4; N=11; N=20) testing the framework design with two DSA user persona scenarios. We contribute an extensible methodological foundation for making fundamental-rights risk assessments under the DSA more streamlined, systematic, transparent, and auditable.

cs.CY↗

arXiv2026

When Is Content "AI-Generated Enough"? Labelling Synthetic Media under the Digital Services Act and the AI Act

European platform and AI governance increasingly relies on transparency duties to address synthetic and manipulated media. Under the DSA, very large online platforms and search engines may use prominent markings and recipient-facing indication tools as systemic-risk mitigation measures. Under the AI Act, providers must support machine-readable marking, while deployers must disclose deepfakes and certain AI-generated or manipulated public-interest text, subject to statutory qualifications. This extended abstract examines when labelling is a meaningful regulatory response to synthetic media and when it risks becoming over-inclusive, under-inclusive, or ineffective. It argues that the central challenge is not only whether content should be labelled, but how legal thresholds, technical provenance systems, platform interfaces, and reporting practices determine when content is sufficiently generated, manipulated, or authentic-looking to trigger transparency obligations. Drawing on the emerging Article 50 AI Act implementation framework and a snapshot of the DSA Statement of Reasons database, the paper identifies four governance tensions: definitional ambiguity, interface and responsibility design, communicative effectiveness, and fairness and contestability. It conceptualises labelling as a socio-technical classification practice that distributes responsibility among AI providers, deployers, platforms, uploaders, and recipients.

cs.CY↗

arXiv2026

AI at the Front Lines of Platform Governance: Using LLMs to Support Illegal Content Reporting under the Digital Services Act

Illegal content reporting mechanisms are a key technical and organizational measure through which online platforms address illegal content under the European Union Digital Services Act (DSA). Article 16 requires user notices to be sufficiently substantiated and submitted in good faith, placing users in the difficult position of interpreting legal and procedural language and translating ambiguous content into legally meaningful categories and reasons. We investigate how large language model (LLM)-based assistants can support this reporting process. In a controlled user study (N = 450) using an interface modeled on a major platform reporting workflow, we compare three conditions: unaided reporting, a conventional explainable AI assistant (XAI) that suggests a single legal category with a rationale, and an evaluative AI assistant (EvalAI) that presents balanced pro and con arguments across candidate legal provisions. We further examine these assistance forms under systematically varied AI error regimes. Our results show that EvalAI improves provision-level accuracy under AI error and reduces misclassification distance relative to conventional XAI, particularly for near-miss and overbreadth errors. When AI output is correct, conventional XAI enables faster decisions, but neither AI assistance form reliably improves the quality of users' substantiated explanations relative to unaided reporting. We discuss design implications for compliance-oriented reporting interfaces, highlighting trade-offs between accuracy, deliberation, explanation quality, and vulnerability to misleading AI output.

cs.HC↗

arXiv2026

"There is literally zero funding": Understanding the Emerging Role of Trusted Flaggers under the EU Digital Services Act

The European Union's Digital Services Act (DSA) introduced regulatory mechanisms which serve as a way to manage harmful content online. The recognition of Trusted Flaggers (TFs) is one such mechanism which accredits entities with experience, platform independence, and skill in identifying and reporting illegal content. With the DSA's TF role being roughly one year old, we interviewed representatives of seven such TF organizations to learn about their experiences of becoming a TF and how it impacts their interactions with online platforms and with individual users. We additionally ran a workshop involving TF representatives, primarily as it was requested by TFs themselves, who collectively wanted to share experiences of their new role and learn from each other rather than be isolated. Notably, we found that accreditation as a TF can be cumbersome, that resources for TFs remain the same despite an increasing workload, and that platforms priorities often diverge from TFs. We conclude with recommendations for future research into understanding user representation within the DSA and the need for standardization measures tailored to the needs and resource constraints of TFs.

cs.CY↗

arXiv2025

Prompt template for a fictitious LLM agent in a content-flagging experiment

Digital regulations such as the European Union's Digital Services Act (DSA) represent major efforts to shape human-centered and human rights-based frameworks for society. Yet, as these laws are translated into practice, challenges emerge at the intersection of technology, law, and design. This paper presents a qualitative case study examining how designers act as mediators between abstract legal requirements and real-world digital experiences for users, focusing on the design of content reporting mechanisms under Article 16 of the DSA. Through an expert workshop with professional designers from diverse fields (N=9), we explore how legal obligations are interpreted by designers and reflected in discussions and design solutions. Our findings resonate with previous research on the design of reporting mechanisms and dark patterns, highlighting how UX design choices can mislead or hinder users' decision-making and therefore also highlighting the crucial role of design decisions. We show how participatory design methods can bridge disciplinary divides, making legal obligations accessible in compliance fostering design solutions. By using legal design as a lens, we argue that the co-creation of digital regulations and user experience is a core site for digital humanism; where designers, engineers, and legal scholars must collaborate to ensure that systems uphold legal standards to address the challenge the regulation poses to these disciplines.

cs.CY↗

arXiv2025

From Reports to Reality: Testing Consistency in Instagram's Digital Services Act Compliance Data

The Digital Services Act (DSA) introduces harmonized rules for content moderation and platform governance in the European Union, mandating robust compliance mechanisms, particularly for very large online platforms and search engines. This study examined compliance with DSA requirements, focusing on Instagram as a case study. We develop and apply a multi-level consistency framework to evaluate DSA compliance. Our findings contribute to the broader discussion on empirically-based regulation, providing insight into how researchers, regulators, auditors and platforms can better utilize DSA mechanisms to improve reporting and enforcement quality and accountability. This work underscores that consistency can help detect potential compliance failures. It also demonstrates that platforms should be evaluated as part of an interconnected ecosystem rather than through isolated processes, which is crucial for effective compliance evaluation under the DSA.

cs.CY↗

arXiv2025

Doing Audits Right? The Role of Sampling and Legal Content Analysis in Systemic Risk Assessments and Independent Audits in the Digital Services Act

A central requirement of the European Union's Digital Services Act (DSA) is that online platforms undergo internal and external audits. A key component of these audits is the assessment of systemic risks, including the dissemination of illegal content, threats to fundamental rights, impacts on democratic processes, and gender-based violence. The DSA Delegated Regulation outlines how such audits should be conducted, setting expectations for both platforms and auditors. This article evaluates the strengths and limitations of different qualitative and quantitative methods for auditing these systemic risks and proposes a mixed-method approach for DSA compliance. We argue that content sampling, combined with legal and empirical analysis, offers a viable method for risk-specific audits. First, we examine relevant legal provisions on sample selection for audit purposes. We then assess sampling techniques and methods suitable for detecting systemic risks, focusing on how representativeness can be understood across disciplines. Finally, we review initial systemic risk assessment reports submitted by platforms, analyzing their testing and sampling methodologies. By proposing a structured, mixed-method approach tailored to specific risk categories and platform characteristics, this article addresses the challenge of evidence-based audits under the DSA. Our contribution emphasizes the need for adaptable, context-sensitive auditing strategies and adds to the emerging field of DSA compliance research.

cs.CY↗

arXiv2025

Mapping Compliance: A Taxonomy for Political Content Analysis under the EU's Digital Electoral Framework

The rise of digital platforms has transformed political campaigning, introducing complex regulatory challenges. This paper presents a comprehensive taxonomy for analyzing political content in the EU's digital electoral landscape, aligning with the requirements set forth in new regulations, such as the Digital Services Act. Using a legal doctrinal methodology, we construct a detailed codebook that enables systematic content analysis across user-generated and political ad content to assess compliance with regulatory mandates.

cs.CY↗