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The science and practice of proportionality in AI risk evaluations
0
Zitationen
22
Autoren
2026
Jahr
Abstract
AI evaluations should provide meaningful risk information without imposing excessive burden.
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Autoren
- Carlos Mougán
- Lauritz Morlock
- Jair Aguirre
- James R. M. Black
- Jan Brauner
- Siméon Campos
- Sunishchal Dev
- David Fernández Llorca
- Alberto Franzin
- Mario Fritz
- Emilia Gómez
- Friederike Grosse-Holz
- Eloise Hamilton
- Max Hasin
- José Hernández-Orallo
- Dan Lahav
- Luca Massarelli
- Vasilios Mavroudis
- Malcolm Murray
- Patricia Paskov
- Jaime Raldua
- Wout Schellaert
Institutionen
- European Union(BE)
- European Commission(BE)
- RAND Corporation(US)
- Johns Hopkins Center for Health Security(US)
- Safran (France)(FR)
- Saft (France)(FR)
- Joint Research Center(ES)
- Helmholtz Center for Information Security(DE)
- Aaron Marcus and Associates(US)
- University of Cambridge(GB)
- Leverhulme Trust(GB)
- Universitat Politècnica de València(ES)
- San Francisco State University(US)
- Italian National Agency for the Evaluation of Universities and Research Institutes(IT)
- The Alan Turing Institute(GB)
- Vaxart (United States)(US)