I think that if they: - Find a feature that is necessary for defection in all of the cases of defection in a diverse and realistic set of model organisms - Locate that feature with very little optimization on the defection cases I’d be fairly confident (>~80%) that it would catch any particular deployment-time defection attempt from an ASL-4 schemer. This would cut risk from the deployment by >5x when paired with compelling incrimination and a shutdown. This is a substantial risk reduction, and I might even buy this safety case if there weren’t better options for this threat model (e.g. untrusted monitoring). My main concerns are: - It seems unlikely we would get a feature that meets the above two criteria - The feature might have too many false positives - The possibility that the model organisms were sabotaging your eval by coordinating to route their defection attempts through a particular feature (this seems hard at ASL-4 though (but this claim would need an eval)).
I think that if they:
- Find a feature that is necessary for defection in all of the cases of defection in a diverse and realistic set of model organisms
- Locate that feature with very little optimization on the defection cases
I’d be fairly confident (>~80%) that it would catch any particular deployment-time defection attempt from an ASL-4 schemer. This would cut risk from the deployment by >5x when paired with compelling incrimination and a shutdown. This is a substantial risk reduction, and I might even buy this safety case if there weren’t better options for this threat model (e.g. untrusted monitoring). My main concerns are:
- It seems unlikely we would get a feature that meets the above two criteria
- The feature might have too many false positives
- The possibility that the model organisms were sabotaging your eval by coordinating to route their defection attempts through a particular feature (this seems hard at ASL-4 though (but this claim would need an eval)).