REGULAIRE
Technologies change.
How can the institutions
that govern them learn?
Institutions that
learn as technologies change.
Artificial intelligence, quantum technologies and digital platforms are changing how societies work. Their effects often emerge while rules are still being interpreted, implemented or revised. Institutions need ways to recognise problems early, test proportionate responses and adjust as they learn more.
REGULAIRE studies how this regulatory learning happens. It asks how authorities gather evidence, understand whether interventions work, share lessons across borders and sectors, and reconsider approaches that no longer serve their purpose. These are practical questions about how governance operates, as well as research questions about how institutions change.
The network brings together fifteen doctoral projects at ten universities, working with regulators, public agencies, international organisations and other partners. Coordinated by the Technical University of Munich, REGULAIRE connects research in law, public policy, computer science, design, communication and economics with the institutions facing these questions in practice. Our aim is to make governance more timely, proportionate and accountable as evidence develops.
Four perspectives on
how regulation learns.
From recognising early signals to making lessons travel, each strand connects a research work package with its doctoral projects.
Anticipation & foresight
How can regulators recognise emerging problems early? We examine how authorities read policy portfolios, hear signals from outside established institutions and anticipate the effects of transformative technologies. The projects develop ways to recognise a mismatch between rules and practice before it becomes a crisis.
Explore the projectsTools & interventions
How can regulatory interventions become opportunities to learn? We study how research exemptions, procurement, software prototypes and AI literacy can generate useful evidence. The aim is to understand when an intervention supports adaptation, and how to avoid both overreaction and inaction.
Explore the projectsInstitutional capacity
What enables institutions to turn evidence into action? We investigate the capabilities, working practices and resources that make regulatory learning possible. Design methods, work inside public bodies and the retirement of obsolete rules help explain how individual insights become an organisation’s capacity to respond.
Explore the projectsFeedback & shared learning
How can lessons travel beyond a single experiment? We examine how evidence is preserved, shared and challenged across regulatory cycles and jurisdictions. The projects address institutional memory, coordination between authorities, systemic actors and the accountability safeguards needed when rules adapt.
Explore the projectsWhat we
offer you.
As a REGULAIRE doctoral researcher, you will develop your own project within an international community that connects academic research with the everyday work of governing technology.
Research
Develop an original doctoral project with academic supervision across institutions. You will investigate how regulators learn, connect your findings with the other projects and contribute evidence and methods for governing transformative technologies.
Practice
Spend time with organisations involved in technology governance. Planned secondments and engagement with practitioners help you understand institutional routines, refine research questions and explore how your findings can inform decisions.
Interdisciplinarity
Work alongside researchers in law, public policy, computer science, design, communication and economics. You will build depth in your own field while learning how other disciplines approach evidence, uncertainty and institutional change.
Training
Combine doctoral study at your host university with network summer schools, methods workshops and research seminars. The programme supports academic writing, communication, professional development and careers in research, regulation, policy and industry.
