A number of reasonable outer alignment proposals such as iterated amplification, recursive reward modeling and debate use generic objectives such as reinforcement learning (and indeed, none of them would work in practice without sufficiently high data quality), so it seems strange to me to dismiss these objectives.
A number of reasonable outer alignment proposals such as iterated amplification, recursive reward modeling and debate use generic objectives such as reinforcement learning (and indeed, none of them would work in practice without sufficiently high data quality), so it seems strange to me to dismiss these objectives.