Dick A. H. Blankvoort

Harshvardhan J. Pandit, Dick A. H. Blankvoort, Dick A. H. Blankvoort et al.

Generative AI services like ChatGPT and Gemini are some of the fastest-growing consumer services. Individuals using such services must accept their terms of use before access, and conform to these terms for continued use of the service. Established literature has shown that despite their status as legally-binding agreements, terms of use are not actually well-understood, and may contain implications that are surprising for consumers. In this paper, we analyse the terms of 6 generative AI services from the perspective of an EU-based consumer. Our findings, based on a developed codebook which we provide in the paper, reiterate known issues regarding generative AI services such as the default use of user data for training and surface new concerns regarding responsibility, liability, and rights. All terms in our analysis contained language that explicitly discards assurances regarding the quality, availability and appropriateness of the service, regardless of whether the service is free or paid. The terms also make users solely responsible for outputs meeting norms dictated by the provider, despite no information or control being provided over the functioning of the model, and at the risk of account termination. The terms further restrict users in how outputs can be used while service providers utilise both user-provided inputs as well as user-liable outputs for a wide variety of purposes at their discretion. The implications of these practices are severe, as we find consumers suffer from lack of necessary information, significant imbalance of power, and have responsibilities they cannot materially fulfil without violating the terms. To remedy this situation, we make concrete recommendations for authorities and policymakers to urgently upgrade existing consumer protection mechanisms to tackle this growing issue.

Dick A. H. Blankvoort, Harshvardhan J. Pandit, Maximilian Gahntz

The AI Act's Article 53(1)(d) requires providers of general-purpose AI (GPAI) models to publish a sufficiently detailed public summary about the content used for training based on a template provided by the AI Office. The stated goal of this obligation is to increase transparency regarding the data used for training GPAI models, and to enable relevant stakeholders to exercise their rights, especially regarding IP, copyright, and data protection. This paper provides a quality assessment framework to assess the public summary across two key dimensions: \textit{transparency} regarding information being provided in a clear, comprehensive, and sufficiently detailed manner; and \textit{usefulness} regarding whether the provision of the document and the contents can be effectively utilised by stakeholders to carry out rights related actions. This framework enables identification of key issues in public summaries, and provides a structured and research-based method to compare practices across public summaries and providers. It also enables authorities such as the AI Office to identify potential issues that could emerge and provides actionable recommendations and guidelines for providers to develop public summaries with high quality. The paper provides an assessment of 5 public summaries published as of 12th January 2026 which were found through an exhaustive search process. To disseminate these findings as a public resource, the paper also describes the development of a website where the assessments, outcomes, and methodologies will be shared.

Maribeth Rauh, Dick A. H. Blankvoort, Matias Duran et al.

The use of chatbots for various forms of companionship is growing rapidly, raising a myriad of questions about simulated relationships, emotional dependence, and psychological harm. While major platforms such as ChatGPT, Grok, and Character.AI are the subject of a growing body of research and legal inquiries, apps explicitly built for simulating intimate interpersonal relationships remain under-explored. In this work, we evaluate the five most popular AI companion mobile applications in the EU and UK markets for factors that encourage parasocial interaction and may manipulate users. We do this by manually annotating the user experience each offers. Specifically, we systematically record and quantify design dark patterns, anthropomorphism, stereotypes, erotica, and technical performance issues. We find that all apps contain substantial dark patterns aimed at increasing monetisation and user engagement. Erotica and gamification features such as levelling are also prevalent, and although other features vary considerably between applications, all apps have highly anthropomorphic design. These findings shed light on the mechanics used to leverage users' simulated relationships. On that basis, we put forward concrete recommendations for regulators to strengthen consumer protection in this rapidly emerging market. Content warning: This article contains objectifying images of women, erotic images, textual references to incest, and other potentially sensitive, offensive, and distressing text.