The EPFL International Risk Governance Center (IRGC) is an interdisciplinary unit dedicated to extending knowledge about the increasingly complex, uncertain and ambiguous risks that affect society. We develop risk governance strategies that focus on involving all key stakeholder groups, including citizens, governments, businesses and academia.
Our work is rooted in the IRGC Risk Governance Framework, as well as subsequent frameworks that we developed to apply more specifically to the governance of emerging and systemic risks. We assess how these frameworks can be applied to a wide range of specific risk domains, and in recent years we have focused increasingly on risks associated with emerging technologies.
The following are among the areas we are currently working on:
- Digital technology and governance (TRIGGER H2020)
- Deepfakes
- Precision medicine
- Synthetic biology
- Nanotechnology (NANORIGO H2020)
- Resilience
News and current activities
Risk governance for deepfakes
In this new report, we set out the key risks posed by algorithmically fabricated digital content and we outline 15 potential technological, legal and societal responses.
Critical infrastructure resilience
This new policy brief examines the positive feedback loops that can exist between insurance and resilience, with a particular focus on risks that affect critical infrastructure.
IRGC News
Read the latest news, insights, presentations and media coverage about the EPFL International Risk Governance Center.
Key links
Concepts and frameworks
At the core of IRGC’s work is a series of governance frameworks, which provide guidance in areas such as risk assessment, emerging and systemic risks, and resilience-building.
Specific risk domains
With a view to filling risk-governance deficits in important sectors, IRGC regularly convenes interdisciplinary expert groups to identify key risks and possible responses.
Publications
IRGC produces a wide range of publications, covering both our overarching governance frameworks as well as the outcomes of our work in specific risk domains.