[T]here was a type of employee at the beginning of the Industrial Revolution whose job and livelihood largely vanished in the early twentieth century. This was the horse. The population of working horses actually peaked in England long after the Industrial Revolution, in 1901, when 3.25 million were at work. Though they had been replaced by rail for long-distance haulage and by steam engines for driving machinery, they still plowed fields, hauled wagons and carriages short distances, pulled boats on the canals, toiled in the pits, and carried armies into battle. But the arrival of the internal combustion engine in the late nineteenth century rapidly displaced these workers, so that by 1924 there were fewer than two million. There was always a wage at which all these horses could have remained employed. But that wage was so low that it did not pay for their feed.
-- Greg Clark, A Farewell to Alms
The "Lump of Work fallacy" does seem to be a fallacy. However, that didn't help the horse. Why is that? The invention of "Artificial General Muscles" in the form of the internal combustion engine was a better-than-perfect replacement for all forms of horse labour. We should expect artificial general intelligence technology to do much the same to humans. There is no law in economics that prevents human wages from declining below subsistence. And a perfect substitute for human labour that requires no wages and is more intelligent would certainly vastly lower the value of human labour.
So what? We don't need as many. It doesn't make life any worse (in fact, probably better) for the ones we have now. Those pre-industrial-revolution horses would have been dead by now of old age if not turned into dog food.
We don't do anything. We'll have to take care of them, which is where things like a basic income help. It won't happen all at once instantly, and it's not like our only option is to grind them into soylent green. Horses may get turned into food, but that's because they're horses and not people. We eat animals, so it's not very compelling to say "oh no, we ate all the horses or turned them into glue". Who cares. The point is there are horses now and there will probably continue to be horses. Many of them with a life of mostly leisure and good care instead of being worked to death. Sounds good to me.
As long as we're all clear that you're arguing for a significantly reduced human population, I guess I don't have anything to add. I'm pessimistic that the transition between our current populous life of toil and this idyllic future will be peaceful or pleasant.
Globally yes, locally no. It is not reasonable to discount the fears of a to-be-displaced factory worker in Michigan because their loss is offset by new service industry jobs in New York, even though the net economic effect may be positive. For real examples, laid-off shipbuilders in Liverpool and coal miners in Wales are still largely out of work even while the UK economy has grown since those mass industrial transitions.
Taken to a limit, a sector-wide displacement could have quite severe repercussions for a society. Imagine for example a majority of truck drivers* losing their jobs once self-driving cargo vehicles become available. Assuming they'll be adopted rapidly (for their advantages in safety, fleet efficiency, and reduced transit time due to continuous operation) and the change is quite sudden. Those truckers are now an immediate, acute problem for the country: unemployed, not spending, not earning, heavily invested in training and experience for a now non-existent job, and not (in aggregate) well-suited for other work. They are also a large, angry, nationwide group - a pre-fabricated voting block - ripe for political exploitation.
*I picked this example based on that map of common occupations that was floating round here a few months ago. By far the most popular job by state was "truck driver", so this is potentially a real issue.
"You just beautifully summarized the "Lump of Work fallacy""
The fallacy claims that the number of jobs is a zero-sum game. I'm not saying this at all. While more jobs will be created, because automation is happening at such an exponential rate, there won't be enough jobs replaced.
I have feeling when we do have AI, many of these economic principals will need to be re-written.
More from this article:
"Whereas some argue that immigrants displace domestic workers, others believe this to be a fallacy, arguing that such a view relies on a belief that the number of jobs in the economy is fixed, whereas in reality immigration increases the size of the economy, thus creating more jobs"
Immigration may increase the size of the economy, but if they are hired at let's say 30% of an American working at the same rate, it essentially dilutes the market. Americans now have to compete with someone making much less than them, which will mean a huge pay cut.
With AI, it will mean competing with algorithms/hardware that can probably be purchased for even less than the cost of a worker.
The end game for this will be a class of people owning all of this AI hardware, the poor, and a much smaller middle class of people in-between that have the skills to work on the AI hardware.
What happens to all of the people that aren't educated or don't have the skills in this new economy when all of the jobs they could do to make money have been replaced by AI?
This is a complex issue, and like on most complex issues, there is no simple answer.
The general idea that technology deprecates people is true. It is also true that there is an escape valve in new needs, requiring new jobs, that allows for us to shift occupations and remain employed.
However, there is no law that states that the escape valve will always work, nor that it can work at high rates of job displacement.
Moreover, there are signs of low aggregate demand in developed economies. These signs are appearing now even in developing economies. This means that money is not percolating down into the hands of people, who can't then spend and create demand. There is a huge number of factors at play here (see the note about being a complex problem). Higher worker efficiency causing higher unemployment rates is one such factor. It can't be dismissed outright.
We may be witnessing Marx being right (albeit ahead of its time).
There's a difference between shifting labor around between sectors (e.g. moving agriculture jobs into manufacturing or new industries) and a situation in which, almost instantaneously, every job that a human can do can be outdone by an AI. I think it would be naive to think the advent of superintelligent AI is comparable to relatively incremental advances of the industrial era.
With agricultural automation, the 30% change was filled mostly with new service jobs, not labor jobs. The same goes with A.I. automation - suddenly service jobs that were not possible before become possible. Jobs are not a zero-sum game.
But any new job that is created can be done by the superintelligent AI, and better than humans. Even if somehow a million new service jobs are created, those jobs can be done better by an AI. So where does that leave humans? There would be no place for human labor if we cared about efficiency.
Edit: I see superintelligent AI as not mere automation, but in effect creating an infinite supply of new labor. Humans are diluted out.
Thanks for engaging. I'm not trying to argue for the sake of argument, I'm honestly still stuck on this point. It seems like you have a different understanding of what a super intelligent AI is. To me, that is when there is an AI with all the intellectual faculties of a human except with much faster processing speed and greatly enhanced memory. In this case, there would be nothing a human can do that cannot be done by such an AI (assuming you give some AIs a humanoid robot body). Perhaps the AI could help improve the human species so that we "catch up" to the AI in intellect. I don't see how this is anything like the God of the gaps fallacy, I'm not claiming AI created the universe or any other such claims.
It will be different because automation has never before been able to fulfill all human niches. Automating one job just freed up people to work in other jobs. In particular, automating physical labor freed people up to work in cognitive tasks.
This time it's the entire human niche that will (eventually) be automated - all cognitive tasks as well as all physical ones. That's the difference and why extrapolating from the past doesn't work for AGI.
Actually, Marx was saying the exact same thing about machinery unemploying people that HN is saying every now and then(I don't have a firm opinion on the matter, I just found it amusing to read the same argument made 150 years ago; Marx actually credited a whole slew of other economists with making this argument.)
"...one might infer, as Adam Smith, in whose days modern industry was still in its infancy, did infer, that the accelerated accumulation of capital must turn the balance in favour of the working man, by securing a growing demand for his labour. From this same standpoint many contemporary writers have wondered that English capital having grown in that last twenty years so much quicker than English population, wages should not have been more enhanced. But simultaneously with the progress of accumulation there takes place a progressive change in the composition of capital. That part of the aggregate capital which consists of fixed capital, machinery, raw materials, means of production in all possible forms, progressively increases as compared with the other part of capital, which is laid out in wages or in the purchase of labour. This law has been stated in a more or less accurate manner by Mr. Barton, Ricardo, Sismondi, Professor Richard Jones, Professor Ramsey, Cherbuilliez, and others."
(I personally am not a huge fan of Marx's writings, mainly because of the strong contempt for humanity that I feel emanating from them... incidentally I've recently stumbled upon this one, though.)
A scary analogy in favor of this argument is, a horse cannot economically perform almost any job today, hence most were slaughtered though few were kept for amusement. That happened after horses had a very good run where every improvement in technology increased "horse employment." If a machine exist to outperform a human in any conceivable job, it's not very different (and then you get to the discussion of the political options.)
A counterargument is that up until now this argument was wrong many times, and that we're very far from an AGI, or even from machines beating humans at every possible task.
The difference this time is that real AI will be able to automate all human jobs because it will be able to endlessly create better tools via robots. When the tractor was invented, it wasn't able to drive itself, the combine, the trains, and the grain processing facilities.
The counter that you made relies on transitions in the job market. That requires people learning new skills on large scales. But what if most people can't learn to do the new tasks as quickly as the top few can learn to automate them?
You missed the whole section where he compared unikernals on Xen vs. Linux (or Solaris) on metal. Unikernals have to run on Xen so either way, the best you're going to do is have one-level of abstraction (OS or Hypervisor) between you and your application.
Articles like this that give zero context for the arguments are annoying. A bit from the author describing who they are, what kind of projects are the building, the size of the company, (rough) size of code base, number of engineers would help immensely in evaluating their arguments.
The researchers did a study of Swedish military conscripts (98%) of male population. They tested if high-intelligence is as inheritable as general-intelligence. They found strong evidence that it does as siblings of high-intelligent soldiers also tended to more intelligent than the norm.
Similar levels of intelligence have been seen even in switched-at-birth twin cases where one twin is raised by one family and another by another. The IQ between the twins was in every case more correlated than the IQ of each twin and their family-siblings. Look up the interview with Nancy Segal on YouTube about Twin Studies and IQ.
They controlled for environment by considering the difference between non-twin siblings (< 2 years apart in age), fraternal (two-egg) twins, and identical (single-egg) twins. The correlation in intelligence between non-twin siblings and fraternal twins was similar, and both are significantly lower than the correlation between identical twins. The most plausible explanation for this is the genes that identical twins share.