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.
I simulated 100,000 people to show how often people are "thrice-exceptional": Smart, stable, and exceptionally hard-working.
I've highlighted these people in red in this chart:
If you reorient the chart to a bird's eye view, it looks like this:
In short, there are not many people who are thrice-exceptional, in the sense of being at least +2 standard deviations in conscientiousness, emotional stability (i.e., inverse neuroticism), and intelligence.
To replicate this, use 42 as the seed and assume linearity and normality
The decline of trust is something worth caring about, and reversing it is something worth doing.
We should not have to live constantly wondering if we're being lied to or scammed. Trust should be possible again.
I don't know how we go about regaining trust and promoting trustworthiness in society.
It feels like there's an immense level of toleration of untrustworthy behavior from everyone: scams are openly funded; academics congratulate their fraudster peers; all content is now slop.
What China's doing—corruption crackdowns and arresting fraudsters—seems laudable, and I think the U.S. and other Western nations should follow suit.
Fraud leads to so many lives being lost and so much progress being halted or delayed.
British fertility abruptly fell after one important court case: the Bradlaugh-Besant trial🧵
You can see its impact very visibly on this chart:
The trial involved Annie Besant (left) and Charles Bradlaugh (right).
These two were atheists—a scandalous position at the time!—and they wanted to promote free-thinking about practically everything that upset the puritanical society of their time.
They were on trial because they tried to sell a book entitled Fruits of Philosophy.
This was an American guide to tons of different aspects of family planning, and included birth control methods, some of which worked, others which did not.
One of the really interesting studies on the psychiatric effects of maltreatment is Danese and Widom's from Nat. Hum. Behavior a few years ago.
They found that only subjective (S), rather than objective (O) maltreatment predicted actually having a mental disorder.
Phrased differently, if people subjectively believed they were abused, that predicted poor mental health, but objectively recorded maltreatment only predicted it if there was also a subjective report.
Some people might 'simply' be more resilient than others.
I think this finding makes sense.
Consider the level of agreement between prospective (P-R) and retrospective (R-P) reports of childhood maltreatment.
A slim majority of people recorded being mistreated later report that they were mistreated when asked to recall.
The Reich Lab article on genetic selection in Europe over the last 10,000 years is finally online, and it includes such interesting results as:
- Intelligence has increased
- People got lighter
- Mental disorders became less common
And more!
They've added some interesting simulation results that show that these changes are unlikely to have happened without directional selection, under a variety of different model assumptions.
They also showed that, despite pigmentation being oligogenic, selection on it was polygenic.
"[S]election for pigmentation had an equal impact on all variants in proportion to effect size."
I still think this is one of the most important recent papers on AI in the job market🧵
The website Freelancer added an option to generate cover letters with AI, and suddenly the quality associated with cover letters stopped predicting the odds of people getting hired!
LLMs do a few things to cover letters.
Firstly, they increase the quality, as measured by how well tailored they are to a given job listing.
Second, they make job applications in expensive, so people start spending less time shooting off applications.
More, rapidly-produced job applications becomes the norm.