One of my favorite lines from the Nicomachean Ethics goes ‘for the things we need to learn before we do them, we learn by doing them’. The world is complex and messy… ‘men become builders by building and lyreplayers by playing the lyre’. How did AI systems become taxi drivers? How will they become office workers?
One view is that they’ll gain those skills by training on high quality data. But where will that data come from? What kinds of data will the economy accumulate? How quickly? Who gains and who loses? And if we train AI systems on tons of data so it becomes superhuman at every job, what will be left for us to do?
Simple macro model with three ingredients:
(1) data is task-specific: coding data is not the same as self-driving data; different tasks might also be differentially verifiable so accumulating data is harder/easier
(2) data accumulates endogenously: if the economy finds it worthwhile to do lots of coding we get lots of coding data
(3) data exhibits spillovers: data on one task might augment the productivity of another e.g., via transfer learning or via overlapping primitive skills (pic: some spillover patterns)
