The unemployment rate doesn't accurately represent this. I'd say labor force participation rate in males is a more accurate reflection of the underlying issue.
Why?
Male labor force participation rate in the US has declined from 87.5% to 70% from 1950 to present, per federal reserve bank of St. Louis. I've sent them a query to get their exclusionary criteria for the base male labor force pool.
The Bureau of Labor Statistics gives a figure of 71% for males over the age of 16 in 2010. There are many confounding factors here:
I'm disappointed in EY's economic analysis, as it ignores all the frictional costs in hiring. Yes, if you ignore such things, by relative advantage arguments everyone who wants a job has one. Since that is observably not the world we live in, those costs are clearly relevant to the analysis. Also, the wage under that perfectly efficient system may be a penny an hour.
Automation could reduce the cost of hiring.
Take Uber, Sidecar, and Lyft as examples. I can't find any data, but anecdotally these services appear to reduce the cost, and increase the wages, for patrons and drivers respectively by between 20 and 50%, with increased convenience for both. You know it's working when entrenched, competing sectors of the industry are protesting and lobbying.
Eliezer's suggestion about forgotten industries (maids and butlers) seems much more on point if automatic markets can remove hiring friction. Ride sharing has a rapidly...
As a part of my work on the "Can we know what to do about AI?" project for MIRI, I looked at mathematician Norbert Wiener's predictions about the impact of automation on society, and how he acted based on these predictions.
I already wrote about Wiener's "Sorcerer's Apprentice" type concerns about the dangers of automation, which parallel MIRI's concerns and Eliezer's concerns about AI risk. But Wiener was also concerned that automation would cause unemployment.
Coincidentally, immediately after I investigated this, Eliezer wrote The Robots, AI, and Unemployment Anti-FAQ, which argues against the position that Wiener held.
I found a recent paper titled Some Notes on Wiener’s Concerns about the Social Impact of Cybernetics, the Effects of Automation on Labor, and “the Human Use of Human Beings” which summarizes Wiener's views on automation and unemployment and how he acted based on them.
Wiener's prediction
Wiener believed that unless countermeasures were taken, automation would render low-skilled workers unemployable, precipitating an economic depression of far greater magnitude than the Great Depression of the 1930s:
What Wiener did based on his prediction
Wiener believed that the problem that he foresaw was so great that he considered giving top priority to mitigating it:
He attempted to network with labor unions so as to mitigate the problem:
Assessing Wiener's prediction
Wiener was correct that automation would put some workers out of work in the near term:
However, at a macro-level, and over large time scales, automation doesn't seem to have increased unemployment nearly as much as Wiener seems to have believed. The graph of unemployment from 1950 until present gives the impression that at the time when Wiener expressed his concerns, unemployment hovered around 6%, whereas in later decades it's hovered around 7%. It's interesting that there appears to have been a slight increase, but this could be attributable to outsourcing to foreign countries rather than to automation, and the absolute unemployment rate is very low compared with the 20% unemployment rate from the Great Depression.
As Eliezer said in his recent post
Wiener seems not to have assimilated conventional economic theory. Specifically, he seems to have been unattuned to the existence of equilibrating influences. As Robin Hanson wrote in his post on Eventual Futures:
At least with the benefit of hindsight, Wiener's predictions appear naive.
Where did Wiener go wrong?
Wiener seems to have gone wrong in relying on one relatively strong argument as opposed to many weak arguments. The argument "if machines start doing the labor that low skilled workers are qualified to do, then their employers will fire them, and they won't have jobs" may have seemed strong from the inside. But arguments that feel strong from the inside are often wrong.
Wiener could have done better by giving more weight to conventional wisdom, by trying harder to understand why others didn't share his concerns (which might have resulted in more exposure to conventional economic theory), and by doing a more detailed study of the historical impact of technological innovations on employment.
In Chapter 2 of Nate Silver's book "The Signal and the Noise", Silver describes Philip Tetlock's study of expert political judgment, and Tetlock's findings about characteristics of relatively successful political expert predictors. Two characteristics that he highlights as helpful are
If Wiener had approached the question of whether automation will lead to large scale unemployment in a more multidisciplinary and empirical way, he might have made a better prediction.