Risk-based approach to EU AI act: benefits and challenges of co-regulation
Ronit Justo-Hanani
What the paper says
The regulation of artificial intelligence (AI) is an important policy area in which a risk-based approach is increasingly being pursued. This article examines co-regulation, a hybrid regulatory model where public and private sectors collaborate to manage AI risks within a risk-based framework. Drawing on an analysis of the EU AI Act, the article identifies the significant benefits and challenges of these public-private partnerships. It argues that, to achieve the societal goals of safety, health, and fundamental rights, the EU’s framework should mandate data sharing mechanisms between private and public actors to build the necessary regulatory capacity. Moreover, the framework needs to be flexible enough to adapt to evolving risks and industry developments, ensuring that public oversight of AI remains risk-based, transparent, and free from industry capture. This is particularly important for promoting compliance and establishing a truly effective regulatory framework.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.