The traditional argument for AI alignment being hard is that human value is ‘complex’ and‘fragile’.
Presumably, many actors will be investing a lot of resources into building the most capable and competitive ML models in many domains (e.g. models for predicting stock prices). It seems to me that the purpose of the field of AI alignment is to make it easier for actors to build such models in a way that is both safe and competitive. AI alignment seems hard to me because using arbitrarily-scaled-up versions of contemporary ML methods—in a safe and competitive way—seems hard.
Presumably, many actors will be investing a lot of resources into building the most capable and competitive ML models in many domains (e.g. models for predicting stock prices). It seems to me that the purpose of the field of AI alignment is to make it easier for actors to build such models in a way that is both safe and competitive. AI alignment seems hard to me because using arbitrarily-scaled-up versions of contemporary ML methods—in a safe and competitive way—seems hard.