Building Problem Sensing Capacities Through Portfolio Analysis
Short description
How can regulators spot weaknesses in AI governance before they become failures? This project compares national AI policy portfolios: the combinations of rules and policy instruments that countries use to govern AI. It draws on the Digital Policy Alert dataset to study how these combinations support learning and give people and organisations a predictable regulatory environment.
The researcher will develop methods for detecting early signs that regulation no longer fits its context, including LLM-assisted analysis of legal and policy texts. Outputs will include an open dataset, a codebook and practical guidance for strengthening regulatory problem sensing.
Interested in this project?
Applications are now open for this position.
Deadline: 7 November 2026
The intended start date is 1 January 2027.
View the St. Gallen DC01 job advertisementApply through the University of St. Gallen’s online recruitment portal. Include a motivation letter, CV, academic certificates and transcripts, at least two reference letters, and a short research proposal addressing the project. Follow the official advertisement for the complete requirements.
What the project involves
- Compare national AI policy portfolios and the mix of instruments they contain.
- Develop and apply LLM-assisted methods for analysing EU and national regulation.
- Create early-warning indicators, an open dataset and guidance for regulatory learning.