Katja de Vries

Biträdande universitetslektor i offentlig rätt vid Juridiska institutionen, Professorer, lärare, forskare

Trädgårdsgatan 1 och 20, Västra Ågatan 26
Box 512
751 20 UPPSALA

Kort presentation

Katja de Vries (Jur. dr.) är biträdande lektor i offentlig rätt vid Uppsala Universitet (Ragnar Söderberg Stiftelse 2020-24). Hon är också anknuten till Institutet för Rättsinformatik (SU), the Center for Law, Science, Technology and Society (Bryssel), och Rättssociologiska Institutionen (LU). Hon forskar framst kring rätt och AI, och hennes forskning fokuserar nu särskilt på AI-skapade data ('deepfakes' or 'synthetic data') .

Detta stycke finns inte på svenska, därför visas den engelska versionen.

Currently (2020-24) Katja de Vries is conducting research within her individual research project “CreAI: Co-existing with creative Artificial Intelligence within the limits of EU law. Data protection, intellectual property, freedom of expression and cybercrime” funded by the Ragnar Söderberg Foundation.

She is also part of the "ADM GOV - The automated administration: governance of ADM in the public sector" (2022-26) which is funded within the Research programme "Future Challenges in the Nordics – People, Culture and Society" of the SLS (Society of Swedish Literature in Finland). She will be conducting research within ADM-GOV mainly under the period 2024-26.

Prior to her current position as an assistant professor in public law at Uppsala University, Katja de Vries worked as a postdoc at the Swedish Law and Informatics Research Institute at Stockholm University (2019-2020), the Department of Sociology of Law at Lund University (2019) and the Technologies in Practice research group, Department of Business IT, IT University of Copenhagen (2018). In 2014-2016 she was a fulltime researcher at the Institute for Computing and Information Sciences (iCIS) in the Computer Science Department at the Radboud Universiteit Nijmegen (the Netherlands) within the USEMP project. The project resulted in the DataBait transparency tool that showed users of social networks which sensitive and commercially interesting information can be derived from their data.

In October 2016 Katja de Vries defended her PhD thesis "Machine learning/Informational fundamental rights. Makings of sameness and difference" (available upon request). She has published on a wide range of legal and philosophical topics and has co-edited ‘Privacy, Due Process and the Computational Turn’ (Routledge, 2013). Prior to her doctoral research she studied at Sciences Po in Paris, obtained three masters degrees with distinction at Leiden University (Civil Law, Cognitive Psychology and Philosophy) and graduated at Oxford University (Magister Juris).

De Vries's main research interest are the challenges posed by machine learning to privacy, data protection, antidiscrimination and intellectual property law. Further fields of expertise include: philosophy of technology, legal theory, and science and technology studies (STS). She has taught the advanced BA-course “Law, Ethics and Politics” at the Faculty of Law of Saint-Louis University (Brussels, Belgium), the MSc-course 'Critical Big Data Management' at the IT University of Copenhagen (Denmark), and contributed to the advanced course in Legal Informatics at the Law Faculty of Stockholm University.

De Vries has participated in several European (FP6, FP7 and H2020) interdisciplinary research projects. Next to her research within the aforementioned USEMP project, De Vries has also been an active member of the European “Living in Surveillance Societies”-network, and has contributed with her research to three other topical EU projects: FIDIS (exploring the future of identity in the information society), SIAM (creating a decision support tool for the acquisition of security technologies in public transportation sites in alignment with ethical and legal requirements), and CANDID (Checking Assumptions aND promoting responsibility In smart Development projects).

Publikationer på Google Scholar

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Katja de Vries
Senast uppdaterad: 2021-03-09