Current Fellows

Lucas is a research assistant at Aalborg University and researches digital technologies, learning, and collaboration.
In his CAISA Fellowship, Lucas researches how artificial intelligence can be used to support fair, consistent, and transparent judgment in oral examinations.

Aysel is an assistant professor of Law, Human Rights, and Digitalisation at the University of Copenhagen. Her research focuses on how digital technologies and artificial intelligence (AI) in the public sector shape rights, public administration, and decision-making processes. She is a co-founder of Denmark's first database on the use of AI in the public sector.
As part of her CAISA Fellowship, Aysel is working to further advance the database into a sustainable transparency infrastructure that strengthens public oversight of algorithmic governance and contributes to the national debate on digital sovereignty.

Ilker is a postdoc in the Language and Multimodal Processing Group at the Department of Computer Science at the University of Copenhagen. His primary research focuses on natural language processing (NLP), with a particular interest in pixel-based language modelling and multimodal learning.
As part of his CAISA Fellowship, Ilker researches how generative multimodal AI models moderate content about political and public figures. He maps biases across countries and models, contributing new insights into political bias in generative AI.

Agnete Meldgaard Hansen is an associate professor at the Department of People and Technology at Roskilde University. Her research focuses on care work in the healthcare and elderly care sectors, with a particular emphasis on how new technologies, including artificial intelligence (AI), influence care practices, relationships, and ethics.
As part of her CAISA Fellowship, Agnete examines the ethical implications of AI in elderly care and compiles existing knowledge into a practice-oriented research brief. Through interviews with municipalities and key stakeholders, she identifies and explores the ethical dilemmas that arise when AI is integrated into care work, contributing to a more nuanced and informed debate on responsible AI in Danish elderly care.

Anja is a professor of Media Studies and Director of DATALAB at Aarhus University. Her research focuses on how AI-driven algorithms shape collective behaviour and democratic processes, and she has played key roles in international expert groups on disinformation and digital democracy. She currently chairs the EU Code of Practice on transparency in AI-generated content.
As part of her CAISA Fellowship, Anja is working to finalize the EU Code of Practice, which will guide companies in complying with AI regulation and transparency requirements. The work involves ongoing dialogue with industry, civil society, and academia, as well as input from EU Member States and institutions ahead of its publication in June 2026.

Samuel Rhys Cox researches human-centred AI, with a particular focus on conversational agents and chatbots. His work explores how AI systems can be designed to support people in sensitive and reflective contexts, including health, well-being, and creative practices.
As part of his CAISA Fellowship, Samuel researches how the framing and presentation of a chatbot’s memory and data retention influence users’ comfort, privacy perceptions, and willingness to self-disclose.

Jun is an Associate Professor at the Center for Tracking and Society, University of Copenhagen, where he leads a Sapere Aude: DFF-Starting Grant project. His research explores the relationship between people and digital technologies, with a focus on datafication, management, and artificial intelligence from a comparative perspective.
As part of his CAISA Fellowship, Jun examines how AI benchmarks function as de facto infrastructures shaping the development of AI systems - not as neutral standards, but as sociotechnical practices influenced by power relations, institutional interests, and geopolitical ambitions. His work highlights how these benchmarks actively shape what is considered legitimate knowledge, performance, and progress in artificial intelligence.


