Unless somebody can make some sort of extremely convincing argument that by deploying this tech we are taking an existential risk, rather than purely banal ones, it doesn't seem reasonble to prevent deployment.
Unless somebody can make some sort of extremely convincing argument that by deploying this tech we are taking an existential risk, rather than purely banal ones, it doesn't seem reasonble to prevent deployment.
A better example is perhaps pharmaceuticals, many of which we do not actually understand the mechanisms of action. But note those go through extremely rigorous testing for exactly that reason.
Similar issues with molecular biology- we knew how to clone a gene from one organism to another, but that doesn't mean we really knew all the things going on (side effects) or what the large-scale implications are (hence the Asilomar agreement).
Even cars- while engines were understood mechanistically, it took quite some time for people to appreciate why automobile safety glass was necessary.
See the experiences learned during testing nuclear weapons- we tested them because we didn't understand them mechanistcally, at least not fully enough to predict many effects.
We have effectively no mechanistic understanding of frontier ML systems, in the sense that we have no idea how they do what they do and could not e.g. write human-readable code to perform comparable tasks, nor can we predict ahead of time what capabilities such systems will have when they're trained (being able to predict e.g. log-loss is _not_ the same as being able to predict specific capabilities).