If companies like OpenAI and Deepmind have safety teams, it seems to me that they anticipate that speeding up AI capabilities can be very bad, so why don’t they press the brakes on their capabilities research until we come up with more solutions to alignment?
Their leaderships (erroneously) believe the benefits outweigh the risk (i.e. they don’t appreciate the scale of the risk, or just don’t care enough even if they do?).
They worry about losing the race to AGI to competitors who aren’t as aligned (with safety), and they aren’t taking heed of the warnings of Szilárd and Ellsberg re race dynamics. Perhaps if they actually took the lead in publicly (and verifiably) slowing down, that would be enough to slow down the whole field globally, given that they are the leaders. There isn’t really precedence for this for something so globally important, but perhaps the “killing” of the electric car (that delayed development by ~a decade?) is instructive.
If companies like OpenAI and Deepmind have safety teams, it seems to me that they anticipate that speeding up AI capabilities can be very bad, so why don’t they press the brakes on their capabilities research until we come up with more solutions to alignment?
Possible reasons:
Their leaderships (erroneously) believe the benefits outweigh the risk (i.e. they don’t appreciate the scale of the risk, or just don’t care enough even if they do?).
They worry about losing the race to AGI to competitors who aren’t as aligned (with safety), and they aren’t taking heed of the warnings of Szilárd and Ellsberg re race dynamics. Perhaps if they actually took the lead in publicly (and verifiably) slowing down, that would be enough to slow down the whole field globally, given that they are the leaders. There isn’t really precedence for this for something so globally important, but perhaps the “killing” of the electric car (that delayed development by ~a decade?) is instructive.