What does labor-saving technology do to workers? Does it make them poor? Does it take away their jobs?
Let's review!
First: Most papers do support the idea that technology takes people's jobs.
This needs qualified.
Most types of job-relevant technology do take jobs, but innovation is largely excepted, because, well, introducing a new innovation tends to, instead, give employers money they can use to hire people.
But if technology takes jobs, why do we still have jobs?
Simple: Because through stimulating production and demand, it also reinstates laborers!
This is supported by the overwhelming majority of studies:
This reinstatement effect is largely consistent across types of technology, with innovations still looking a bit odd.
That is the weirdest category of technology besides "other", so roll with it.
Now the operative question is, if workers lose their jobs and end up reinstated in other jobs, what happens to their incomes?
Well, technology introduction tends to boost incomes!
Across types of tech, this result is pretty consistent: studies agree, technology makes us richer!
But, you might ask, whose income is boosted? Because if reinstatement affects far smaller numbers of workers than replacement, some people might still be getting shafted.
Well, the net employment effects of technology are highly ambiguous:
If we look across types of technology the picture I mentioned above for innovation-style technology shows up again: many studies suggest it's good for employment.
The reason impacts on net employment are so ambiguous is because they really have to be qualified.
For example, in general, when robots cause manufacturing employment to fall, there's a compensatory effect on service-sector employment that's at least as large in magnitude:
What makes that impact so interesting is another way it's qualified: It's smaller in industries more at-risk of offshoring.
In other words, industrial robots save American jobs from going overseas.
Industrial robots also contribute directly to reshoring. In other words, when Americans buy robots to do their manufacturing, Mexicans lose their jobs.
The welfare impact for domestic workers is positive. Not so for Mexicans, but that's just how things go.
Overall, labor-saving technology is clearly good, and the longer we delay adopting it, the poorer we will be relative to the world in which we picked it up immediately.
Some of you who are familiar with medicine no doubt do, but if you don't, no worries: This is James Lind, the man most often credited with finding the cure for scurvy.
Scurvy is one of humanity's great historical killers.
It's a gruesome condition that culminates in your life's wounds reappearing on your flesh. If you want a picture, go look it up.
You never hear about it today though, because it's so easy to cure.
This research directly militates against modern blood libel.
If people knew, for example, that Black and White men earned the same amounts on average at the same IQs, they would likely be a lot less convinced by basically-false discrimination narratives blaming Whites.
Add in that the intelligence differences cannot be explained by discrimination—because there *is* measurement invariance—and these sorts of findings are incredibly damning for discrimination-based narratives of racial inequality.
So, said findings must be condemned, proscribed.
The above chart is from the NLSY '79, but it replicates in plenty of other datasets, because it is broadly true.
For example, here are three independent replications:
A lot of the major pieces of civil rights legislation were passed by White elites who were upset at the violence generated by the Great Migration and the riots.
Because of his association with this violence, most people at the time came to dislike MLK.
It's only *after* his death, and with his public beatification that he's come to enjoy a good reputation.
This comic from 1967 is a much better summation of how the public viewed him than what people are generally taught today.
And yes, he was viewed better by Blacks than by Whites.
But remember, at the time, Whites were almost nine-tenths of the population.
Near his death, Whites were maybe one-quarter favorable to MLK, and most of that favorability was weak.
The researcher who put together these numbers was investigated and almost charged with a crime for bringing these numbers to light when she hadn't received permission.
Greater Male Variability rarely makes for an adequate explanation of sex differences in performance.
One exception may be the number of papers published by academics.
If you remove the top 7.5% of men, there's no longer a gap!
The disciplines covered here were ones with relatively equal sex ratios: Education, Nursing & Caring Science, Psychology, Public Health, Sociology, and Social Work.
Because these are stats on professors, this means that if there's greater male variability, it's mostly right-tail
Despite this, the very highest-performing women actually outperformed the very highest-performing men on average, albeit slightly.
The percentiles in this image are for the combined group, so these findings coexist for composition reasons.