I think if we notice that a model is not completely aligned but mostly useful, there will be at least one party deploying it. We can even see this with dall-e, which mirrors human biases (nurses=female, CEOs, lawyers, evil person=male) and is slowly being rolled out nonetheless. Therefore I believe that noticing misalignment is not helpful enough to prevent it, and we should put our focus on making it easy to create aligned AI. This is an argument for 9, 18, and 19 being relatively more important.
I think if we notice that a model is not completely aligned but mostly useful, there will be at least one party deploying it. We can even see this with dall-e, which mirrors human biases (nurses=female, CEOs, lawyers, evil person=male) and is slowly being rolled out nonetheless. Therefore I believe that noticing misalignment is not helpful enough to prevent it, and we should put our focus on making it easy to create aligned AI. This is an argument for 9, 18, and 19 being relatively more important.