That is also covered in the podcast from two different angles.
While technology has created jobs, using data from the industrial revolution is not sufficient to deal with the way AI is replacing human labour today. It’s not simply making things easier, it’s making them easier to the point where humans will not need to be involved at all, and it’s going to disproportionately impact the 40+ crowd who don’t have the capability to retrain. You’re going to have more hair dressers, and more bartenders, but that’s the solution for young people who are more and more directed to jobs that stand a lower chance of automation (hair dressers, massage therapists). The problem with that is that the supply of labour is going to outrank the demand for it very quickly, especially when you’re losing large swaths of the workforce in record time.
In addition, this new automation is going to have a devastating impact on small towns and requires people to have a high degree of mobility. In-state relocation (moving from small towns to big cities) is at a serious low, because people simply can not afford to live in the urban areas that are going to be able to handle AI automation much easier.
Yang pointed out that otherwise intelligent people have a dependency on looking to the past to predict the future of AI automation when mother remotely comparable has occurred like it, instead of looking at the present. He was very good in addressing concerns over “why is this time different.”
It was a great episode.
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