I see a natural equilibrium with a tension: automation (also through AI) causes unit economics to drop and results in cheaper prices. At the same time, salaries for contributors grow because their impact is so high. So you end up with a new equilibrium of much cheaper prices and much higher salaries. What, however, about the people who can’t contribute? IMO the most natural and fair approach is to support (through whatever means) people’s “education”, allowing them to upgrade their skills so that they can contribute. IMO this leads to a new tension: not rich vs poor, or useful vs useless, but people who can up-level their skills vs those who don’t. And I think, at its extreme, it boils down to this: how much plasticity does your brain have? Because every other constraint, society can adapt or accommodate for.
That is a game thoery approach but it completely fails in the face of reality.
The reality is that the floor to become "useful" is relatively low, which means the few billioanires have a large pool of potentially useful people of which they only employ some, leading to no greater salaries due to labour competition.
The other potentially useful workers cannot pool together and compete as the barrier of entry in the sector is prohibitely high.
So a natural moat emerges over cost of setting up a company, workers beg for a job of which they will take for a small wage and a few billioanires control the market.
This is a much closer approximation to the market we currently see
Yeah, that definitely won't work at scale. The bar for what constitutes being "educated" keeps increasing. Previously it was knowing how to code, now it is having an ML PhD, for example. At the same time, AI keeps getting more and more capable, so no matter how much "education" you have, AI will eventually get to you.
In any case, the argument won't work for majority of the population without a college degree. Are you going to have 50+ year old truck drivers upskilling in a fancy new tool to keep a job? And again, how long until that new skill you upgraded them to is now done by AI as well.
There has been extensive debate around that topic since that paper came out. Some points to discuss:
1. Even the article you shared mentions that starting in 2003, earnings has stopped tracking productivity. "Total compensation remains close until 2003, but does not follow 2003’s uptick in productivity growth (behavior which remains a topic for future research)."
2. They use average earnings and not median earnings. Average earnings include people like CEOs. This by consequence shows that inequality among workers has also increased. Check out chart 4 here to see how much smaller median wages are compared to average: (https://www.csls.ca/ipm/23/IPM-23-Mishel-Gee.pdf)
3. Apart from the average vs median difference, the biggest point of contention between that study and more recent ones is the measure of inflation used. The 2007 study you cite uses a measure of inflation that also includes things paid by employers like medical insurance. It turns out that using that one leads to significantly lower inflation. If you use consumer price index, what workers actually pay out of pocket, the difference again becomes larger. Citing page 37 of the study above: "In other words, that the prices of consumer items has risen faster than a broader index of prices that includes net exports, government goods and services, and investment goods. Therefore, for a given increase in income, the purchasing power of the consumer has fallen faster than that of business for investment goods and foreigners for U.S. exports."
The article I shared before plus this other one describe all the discrepancies (https://www.epi.org/productivity-pay-gap/). Specially see chart 10 in the PDF study. That shows all possible variations of how you measure productivity and income. No matter how you look at it, the most substantiated conclusion is that income has NOT matched productivity.
