Actually, the more I think about the “80% of the jobs a human can do” metric, the more I wonder about it.
I mean, a particularly uncharitable interpretation starts counting jobs like “hold this door open”, in which case it’s possible that existing computers can do 80% of the jobs a human can do. (Possibly even without being turned on.)
I mean, a particularly uncharitable interpretation starts counting jobs like “hold this door open”
Well, ‘charitable’ is hard to judge there. That interpretation makes it easier for computers to meet that standard- is the threshold more meaningful when it’s easy or hard? Hard to say.
Even if by jobs he means “things people get paid to do full-time,” you have the question of weighting jobs equally (if even one person gets paid to floss horse teeth, that goes on the list of things an AI has to be able to do) or by composition (only one person doing the job means it’s a tiny fraction of jobs). But the second is a fluid thing, especially as jobs are given to machines rather than people!
Actually, the more I think about the “80% of the jobs a human can do” metric, the more I wonder about it.
I mean, a particularly uncharitable interpretation starts counting jobs like “hold this door open”, in which case it’s possible that existing computers can do 80% of the jobs a human can do. (Possibly even without being turned on.)
Well, ‘charitable’ is hard to judge there. That interpretation makes it easier for computers to meet that standard- is the threshold more meaningful when it’s easy or hard? Hard to say.
Even if by jobs he means “things people get paid to do full-time,” you have the question of weighting jobs equally (if even one person gets paid to floss horse teeth, that goes on the list of things an AI has to be able to do) or by composition (only one person doing the job means it’s a tiny fraction of jobs). But the second is a fluid thing, especially as jobs are given to machines rather than people!