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.
Compared to twenty years ago, kids are eating some types of ultraprocessed foods more and some types less🧵
For example, one thing there's proportionally less of is sugar-sweetened beverage consumption. Meanwhile, there's relatively greater sweet snack consumption.
Overall, the ultraprocessed food (UPF) consumption share is up across young ages to similar degrees.
The increase is definitely there, but it isn't dramatic. For example, going from 61% to 67.5% is an 11% increase in twenty years.
The increase in consumption is not differentiated by the sex of children.
In other words, boys and girls are both eating a bit more ultraprocessed food.
People tend to understand it as an indication that earlier generations were a lot less intelligent than we moderns.
Or if they're read up on the literature, they now think things are reversing.
Both are wrong! Take a look at this chart of Norwegian data:
If you don't understand what those tests are like, here are some example questions:
What we see over time with the Flynn Effect (the increase in IQ scores) and the Reverse Flynn Effect (the more recent decrease in IQ scores) is that both are due to something really boring: people interpreting tests differently than they used to.
The study took place in Germany and was centered on the experiences of 107 people aged 21-40 who lived alone and had earnings between €1,100 and €2,600 per month.
The experiment provided them with €1,200 per month for three full years.
Controls (N = 1,580) earned €10 for sticking with the program and another €30 if they made it the whole way.
There was no attrition in the treatment group, but 29% of the control group dropped out by the end of the study.
Many women have found that they get pregnant more easily after getting on GLP-1 drugs.
But women aren't the only ones noticing improved fertility:
There's now clinical trial evidence that GLP-1s improve sperm parameters.
The largest clinical trial published so far on this subject came out in 2023. It involved 110 men aged 18-35 with metabolic hypogonadism being sorted into one of three conditions:
A: The group seeking fatherhood.
B: The group not seeking fatherhood.
C: The group of already-dads.
The men in Group A were explicitly given the fertility drugs urofollitropin three times a week and human chorionic gonadotropin twice a week.