4 papers
A Statistical Framework for Algorithmic Collective Action with Multiple Collectives
Claudio Battiloro, Pietro Greiner, Dario Rancati +3
As learning systems increasingly shape everyday decisions, Algorithmic Collective Action (ACA), i.e., users coordinating changes to shared data to steer model behavior, offers a co…
Algorithmic Collective Action with Multiple Collectives
Claudio Battiloro, Pietro Greiner, Bret Nestor +2
As learning systems increasingly influence everyday decisions, user-side steering via Algorithmic Collective Action (ACA)-coordinated changes to shared data-offers a complement to…
Can a Bayesian Oracle Prevent Harm from an Agent?
Yoshua Bengio, Michael K. Cohen, Nikolay Malkin +4
Is there a way to design powerful AI systems based on machine learning methods that would satisfy probabilistic safety guarantees? With the long-term goal of obtaining a probabilis…
Superintelligent Agents Pose Catastrophic Risks: Can Scientist AI Offer a Safer Path?
Yoshua Bengio, Michael Cohen, Damiano Fornasiere +10
The leading AI companies are increasingly focused on building generalist AI agents -- systems that can autonomously plan, act, and pursue goals across almost all tasks that humans…